Merge branch 'beta' into beta

dhp-common/src/main/java/eu/dnetlib/dhp/common/HdfsSupport.java

@@ -28,7 +28,7 @@ public class HdfsSupport {
 	 * @param configuration Configuration of hadoop env
 	 */
 	public static boolean exists(String path, Configuration configuration) {
-		logger.info("Removing path: {}", path);
+		logger.info("Checking existence for path: {}", path);
 		return rethrowAsRuntimeException(
 			() -> {
 				Path f = new Path(path);

dhp-common/src/main/java/eu/dnetlib/dhp/schema/oaf/utils/GraphCleaningFunctions.java

@@ -27,8 +27,11 @@ public class GraphCleaningFunctions extends CleaningFunctions {
 	public static final int ORCID_LEN = 19;
 	public static final String CLEANING_REGEX = "(?:\\n|\\r|\\t)";
 	public static final String INVALID_AUTHOR_REGEX = ".*deactivated.*";
-	public static final String TITLE_FILTER_REGEX = "[.*test.*\\W\\d]";
-	public static final int TITLE_FILTER_RESIDUAL_LENGTH = 10;
+
+	public static final String TITLE_TEST = "test";
+	public static final String TITLE_FILTER_REGEX = String.format("(%s)|\\W|\\d", TITLE_TEST);
+
+	public static final int TITLE_FILTER_RESIDUAL_LENGTH = 5;
 
 	public static <T extends Oaf> T fixVocabularyNames(T value) {
 		if (value instanceof Datasource) {
@@ -195,10 +198,16 @@ public class GraphCleaningFunctions extends CleaningFunctions {
 									final String title = sp
 										.getValue()
 										.toLowerCase();
-									final String residual = Unidecode
-										.decode(title)
-										.replaceAll(TITLE_FILTER_REGEX, "");
-									return residual.length() > TITLE_FILTER_RESIDUAL_LENGTH;
+									final String decoded = Unidecode.decode(title);
+
+									if (StringUtils.contains(decoded, TITLE_TEST)) {
+										return decoded
+											.replaceAll(TITLE_FILTER_REGEX, "")
+											.length() > TITLE_FILTER_RESIDUAL_LENGTH;
+									}
+									return !decoded
+										.replaceAll("\\W|\\d", "")
+										.isEmpty();
 								})
 							.map(GraphCleaningFunctions::cleanValue)
 							.collect(Collectors.toList()));

dhp-common/src/main/java/eu/dnetlib/dhp/utils/DHPUtils.java

@@ -4,19 +4,19 @@ package eu.dnetlib.dhp.utils;
 import java.io.*;
 import java.nio.charset.StandardCharsets;
 import java.security.MessageDigest;
-import java.util.List;
-import java.util.Map;
-import java.util.Properties;
-import java.util.zip.GZIPInputStream;
-import java.util.zip.GZIPOutputStream;
-
-import org.apache.commons.codec.binary.Base64;
-import org.apache.commons.codec.binary.Base64OutputStream;
+import java.util.*;
+import java.util.stream.Collectors;
+
 import org.apache.commons.codec.binary.Hex;
 import org.apache.commons.io.IOUtils;
+import org.apache.commons.lang3.StringUtils;
 import org.apache.hadoop.conf.Configuration;
 import org.apache.hadoop.fs.FileSystem;
 import org.apache.hadoop.fs.Path;
+import org.apache.http.client.methods.CloseableHttpResponse;
+import org.apache.http.client.methods.HttpGet;
+import org.apache.http.impl.client.CloseableHttpClient;
+import org.apache.http.impl.client.HttpClients;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.SaveMode;
 import org.slf4j.Logger;
@@ -26,6 +26,8 @@ import com.fasterxml.jackson.databind.ObjectMapper;
 import com.google.common.collect.Maps;
 import com.jayway.jsonpath.JsonPath;
 
+import eu.dnetlib.dhp.schema.mdstore.MDStoreWithInfo;
+import eu.dnetlib.dhp.schema.oaf.utils.CleaningFunctions;
 import net.minidev.json.JSONArray;
 import scala.collection.JavaConverters;
 import scala.collection.Seq;
@@ -52,10 +54,56 @@ public class DHPUtils {
 		}
 	}
 
+	/**
+	 * Retrieves from the metadata store manager application the list of paths associated with mdstores characterized
+	 * by he given format, layout, interpretation
+	 * @param mdstoreManagerUrl the URL of the mdstore manager service
+	 * @param format the mdstore format
+	 * @param layout the mdstore layout
+	 * @param interpretation the mdstore interpretation
+	 * @param includeEmpty include Empty mdstores
+	 * @return the set of hdfs paths
+	 * @throws IOException in case of HTTP communication issues
+	 */
+	public static Set<String> mdstorePaths(final String mdstoreManagerUrl,
+		final String format,
+		final String layout,
+		final String interpretation,
+		boolean includeEmpty) throws IOException {
+		final String url = mdstoreManagerUrl + "/mdstores/";
+		final ObjectMapper objectMapper = new ObjectMapper();
+
+		final HttpGet req = new HttpGet(url);
+
+		try (final CloseableHttpClient client = HttpClients.createDefault()) {
+			try (final CloseableHttpResponse response = client.execute(req)) {
+				final String json = IOUtils.toString(response.getEntity().getContent());
+				final MDStoreWithInfo[] mdstores = objectMapper.readValue(json, MDStoreWithInfo[].class);
+				return Arrays
+					.stream(mdstores)
+					.filter(md -> md.getFormat().equalsIgnoreCase(format))
+					.filter(md -> md.getLayout().equalsIgnoreCase(layout))
+					.filter(md -> md.getInterpretation().equalsIgnoreCase(interpretation))
+					.filter(md -> StringUtils.isNotBlank(md.getHdfsPath()))
+					.filter(md -> StringUtils.isNotBlank(md.getCurrentVersion()))
+					.filter(md -> includeEmpty || md.getSize() > 0)
+					.map(md -> md.getHdfsPath() + "/" + md.getCurrentVersion() + "/store")
+					.collect(Collectors.toSet());
+			}
+		}
+	}
+
 	public static String generateIdentifier(final String originalId, final String nsPrefix) {
 		return String.format("%s::%s", nsPrefix, DHPUtils.md5(originalId));
 	}
 
+	public static String generateUnresolvedIdentifier(final String pid, final String pidType) {
+
+		final String cleanedPid = CleaningFunctions.normalizePidValue(pidType, pid);
+
+		return String.format("unresolved::%s::%s", cleanedPid, pidType.toLowerCase().trim());
+	}
+
 	public static String getJPathString(final String jsonPath, final String json) {
 		try {
 			Object o = JsonPath.read(json, jsonPath);

dhp-workflows/dhp-actionmanager/src/main/resources/eu/dnetlib/dhp/actionmanager/wf/publication/oozie_app/workflow.xml

@@ -107,7 +107,7 @@
                 --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
                 --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
-                --conf spark.sql.shuffle.partitions=2560
+                --conf spark.sql.shuffle.partitions=5000
             </spark-opts>
             <arg>--inputGraphTablePath</arg><arg>${inputGraphRootPath}/publication</arg>
             <arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Publication</arg>
@@ -159,7 +159,7 @@
                 --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
                 --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
-                --conf spark.sql.shuffle.partitions=2560
+                --conf spark.sql.shuffle.partitions=5000
             </spark-opts>
             <arg>--inputGraphTablePath</arg><arg>${workingDir}/publication</arg>
             <arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Publication</arg>

dhp-workflows/dhp-actionmanager/src/main/resources/eu/dnetlib/dhp/actionmanager/wf/relation/oozie_app/workflow.xml

@@ -99,7 +99,7 @@
                 --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
                 --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
-                --conf spark.sql.shuffle.partitions=2560
+                --conf spark.sql.shuffle.partitions=5000
             </spark-opts>
             <arg>--inputGraphTablePath</arg><arg>${inputGraphRootPath}/relation</arg>
             <arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Relation</arg>

dhp-workflows/dhp-aggregation/pom.xml

@@ -29,6 +29,13 @@
                             <goal>testCompile</goal>
                         </goals>
                     </execution>
+                    <execution>
+                        <id>scala-doc</id>
+                        <phase>process-resources</phase> <!-- or wherever -->
+                        <goals>
+                            <goal>doc</goal>
+                        </goals>
+                    </execution>
                 </executions>
                 <configuration>
                     <scalaVersion>${scala.version}</scalaVersion>

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/Constants.java

@@ -0,0 +1,49 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
+
+import java.util.Optional;
+
+import org.apache.spark.api.java.function.MapFunction;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoders;
+import org.apache.spark.sql.SparkSession;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import eu.dnetlib.dhp.application.ArgumentApplicationParser;
+
+public class Constants {
+
+	public static final String DOI = "doi";
+
+	public static final String UPDATE_DATA_INFO_TYPE = "update";
+	public static final String UPDATE_SUBJECT_FOS_CLASS_ID = "subject:fos";
+	public static final String UPDATE_CLASS_NAME = "Inferred by OpenAIRE";
+	public static final String UPDATE_MEASURE_BIP_CLASS_ID = "measure:bip";
+
+	public static final String FOS_CLASS_ID = "FOS";
+	public static final String FOS_CLASS_NAME = "Fields of Science and Technology classification";
+
+	public static final String NULL = "NULL";
+
+	public static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
+
+	private Constants() {
+	}
+
+	public static Boolean isSparkSessionManaged(ArgumentApplicationParser parser) {
+		return Optional
+			.ofNullable(parser.get("isSparkSessionManaged"))
+			.map(Boolean::valueOf)
+			.orElse(Boolean.TRUE);
+	}
+
+	public static <R> Dataset<R> readPath(
+		SparkSession spark, String inputPath, Class<R> clazz) {
+		return spark
+			.read()
+			.textFile(inputPath)
+			.map((MapFunction<String, R>) value -> OBJECT_MAPPER.readValue(value, clazz), Encoders.bean(clazz));
+	}
+
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/GetFOSData.java

@@ -0,0 +1,77 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
+
+import java.io.IOException;
+import java.io.InputStreamReader;
+import java.io.Serializable;
+import java.util.Objects;
+import java.util.Optional;
+
+import org.apache.commons.io.IOUtils;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.Path;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import eu.dnetlib.dhp.application.ArgumentApplicationParser;
+import eu.dnetlib.dhp.common.collection.GetCSV;
+
+public class GetFOSData implements Serializable {
+
+	private static final Logger log = LoggerFactory.getLogger(GetFOSData.class);
+
+	public static final char DEFAULT_DELIMITER = '\t';
+
+	public static void main(final String[] args) throws Exception {
+		final ArgumentApplicationParser parser = new ArgumentApplicationParser(
+			IOUtils
+				.toString(
+					Objects
+						.requireNonNull(
+							GetFOSData.class
+								.getResourceAsStream(
+									"/eu/dnetlib/dhp/actionmanager/createunresolvedentities/get_fos_parameters.json"))));
+
+		parser.parseArgument(args);
+
+		// the path where the original fos csv file is stored
+		final String sourcePath = parser.get("sourcePath");
+		log.info("sourcePath {}", sourcePath);
+
+		// the path where to put the file as json
+		final String outputPath = parser.get("outputPath");
+		log.info("outputPath {}", outputPath);
+
+		final String hdfsNameNode = parser.get("hdfsNameNode");
+		log.info("hdfsNameNode {}", hdfsNameNode);
+
+		final String classForName = parser.get("classForName");
+		log.info("classForName {}", classForName);
+
+		final char delimiter = Optional
+			.ofNullable(parser.get("delimiter"))
+			.map(s -> s.charAt(0))
+			.orElse(DEFAULT_DELIMITER);
+		log.info("delimiter {}", delimiter);
+
+		Configuration conf = new Configuration();
+		conf.set("fs.defaultFS", hdfsNameNode);
+
+		FileSystem fileSystem = FileSystem.get(conf);
+
+		new GetFOSData().doRewrite(sourcePath, outputPath, classForName, delimiter, fileSystem);
+
+	}
+
+	public void doRewrite(String inputPath, String outputFile, String classForName, char delimiter, FileSystem fs)
+		throws IOException, ClassNotFoundException {
+
+		// reads the csv and writes it as its json equivalent
+		try (InputStreamReader reader = new InputStreamReader(fs.open(new Path(inputPath)))) {
+			GetCSV.getCsv(fs, reader, outputFile, classForName, delimiter);
+		}
+
+	}
+
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/PrepareBipFinder.java

@@ -0,0 +1,145 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
+
+import static eu.dnetlib.dhp.actionmanager.createunresolvedentities.Constants.*;
+import static eu.dnetlib.dhp.actionmanager.createunresolvedentities.Constants.UPDATE_CLASS_NAME;
+import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
+
+import java.io.Serializable;
+import java.util.List;
+import java.util.Optional;
+import java.util.stream.Collectors;
+
+import org.apache.commons.io.IOUtils;
+import org.apache.hadoop.hdfs.client.HdfsUtils;
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.api.java.function.MapFunction;
+import org.apache.spark.sql.Encoders;
+import org.apache.spark.sql.SaveMode;
+import org.apache.spark.sql.SparkSession;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.BipDeserialize;
+import eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.BipScore;
+import eu.dnetlib.dhp.application.ArgumentApplicationParser;
+import eu.dnetlib.dhp.common.HdfsSupport;
+import eu.dnetlib.dhp.schema.common.ModelConstants;
+import eu.dnetlib.dhp.schema.oaf.KeyValue;
+import eu.dnetlib.dhp.schema.oaf.Measure;
+import eu.dnetlib.dhp.schema.oaf.Result;
+import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
+import eu.dnetlib.dhp.utils.DHPUtils;
+
+public class PrepareBipFinder implements Serializable {
+
+	private static final Logger log = LoggerFactory.getLogger(PrepareBipFinder.class);
+	private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
+
+	public static <I extends Result> void main(String[] args) throws Exception {
+
+		String jsonConfiguration = IOUtils
+			.toString(
+				PrepareBipFinder.class
+					.getResourceAsStream(
+						"/eu/dnetlib/dhp/actionmanager/createunresolvedentities/prepare_parameters.json"));
+
+		final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
+
+		parser.parseArgument(args);
+
+		Boolean isSparkSessionManaged = Optional
+			.ofNullable(parser.get("isSparkSessionManaged"))
+			.map(Boolean::valueOf)
+			.orElse(Boolean.TRUE);
+
+		log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
+
+		final String sourcePath = parser.get("sourcePath");
+		log.info("sourcePath {}: ", sourcePath);
+
+		final String outputPath = parser.get("outputPath");
+		log.info("outputPath {}: ", outputPath);
+
+		SparkConf conf = new SparkConf();
+
+		runWithSparkSession(
+			conf,
+			isSparkSessionManaged,
+			spark -> {
+				HdfsSupport.remove(outputPath, spark.sparkContext().hadoopConfiguration());
+				prepareResults(spark, sourcePath, outputPath);
+			});
+	}
+
+	private static <I extends Result> void prepareResults(SparkSession spark, String inputPath, String outputPath) {
+
+		final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
+
+		JavaRDD<BipDeserialize> bipDeserializeJavaRDD = sc
+			.textFile(inputPath)
+			.map(item -> OBJECT_MAPPER.readValue(item, BipDeserialize.class));
+
+		spark
+			.createDataset(bipDeserializeJavaRDD.flatMap(entry -> entry.keySet().stream().map(key -> {
+				BipScore bs = new BipScore();
+				bs.setId(key);
+				bs.setScoreList(entry.get(key));
+				return bs;
+			}).collect(Collectors.toList()).iterator()).rdd(), Encoders.bean(BipScore.class))
+			.map((MapFunction<BipScore, Result>) v -> {
+				Result r = new Result();
+
+				r.setId(DHPUtils.generateUnresolvedIdentifier(v.getId(), DOI));
+				r.setMeasures(getMeasure(v));
+				return r;
+			}, Encoders.bean(Result.class))
+			.write()
+			.mode(SaveMode.Overwrite)
+			.option("compression", "gzip")
+			.json(outputPath + "/bip");
+	}
+
+	private static List<Measure> getMeasure(BipScore value) {
+		return value
+			.getScoreList()
+			.stream()
+			.map(score -> {
+				Measure m = new Measure();
+				m.setId(score.getId());
+				m
+					.setUnit(
+						score
+							.getUnit()
+							.stream()
+							.map(unit -> {
+								KeyValue kv = new KeyValue();
+								kv.setValue(unit.getValue());
+								kv.setKey(unit.getKey());
+								kv
+									.setDataInfo(
+										OafMapperUtils
+											.dataInfo(
+												false,
+												UPDATE_DATA_INFO_TYPE,
+												true,
+												false,
+												OafMapperUtils
+													.qualifier(
+														UPDATE_MEASURE_BIP_CLASS_ID,
+														UPDATE_CLASS_NAME,
+														ModelConstants.DNET_PROVENANCE_ACTIONS,
+														ModelConstants.DNET_PROVENANCE_ACTIONS),
+												""));
+								return kv;
+							})
+							.collect(Collectors.toList()));
+				return m;
+			})
+			.collect(Collectors.toList());
+	}
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/PrepareFOSSparkJob.java

@@ -0,0 +1,133 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
+
+import static eu.dnetlib.dhp.actionmanager.createunresolvedentities.Constants.*;
+import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
+
+import java.io.Serializable;
+import java.util.*;
+import java.util.stream.Collectors;
+
+import org.apache.commons.io.IOUtils;
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.function.FlatMapFunction;
+import org.apache.spark.api.java.function.MapFunction;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoders;
+import org.apache.spark.sql.SaveMode;
+import org.apache.spark.sql.SparkSession;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.FOSDataModel;
+import eu.dnetlib.dhp.application.ArgumentApplicationParser;
+import eu.dnetlib.dhp.schema.common.ModelConstants;
+import eu.dnetlib.dhp.schema.oaf.Result;
+import eu.dnetlib.dhp.schema.oaf.StructuredProperty;
+import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
+import eu.dnetlib.dhp.utils.DHPUtils;
+
+public class PrepareFOSSparkJob implements Serializable {
+	private static final Logger log = LoggerFactory.getLogger(PrepareFOSSparkJob.class);
+
+	public static void main(String[] args) throws Exception {
+
+		String jsonConfiguration = IOUtils
+			.toString(
+				PrepareFOSSparkJob.class
+					.getResourceAsStream(
+						"/eu/dnetlib/dhp/actionmanager/createunresolvedentities/prepare_parameters.json"));
+
+		final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
+
+		parser.parseArgument(args);
+
+		Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
+		log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
+
+		String sourcePath = parser.get("sourcePath");
+		log.info("sourcePath: {}", sourcePath);
+
+		final String outputPath = parser.get("outputPath");
+		log.info("outputPath: {}", outputPath);
+
+		SparkConf conf = new SparkConf();
+		runWithSparkSession(
+			conf,
+			isSparkSessionManaged,
+			spark -> {
+				distributeFOSdois(
+					spark,
+					sourcePath,
+
+					outputPath);
+			});
+	}
+
+	private static void distributeFOSdois(SparkSession spark, String sourcePath, String outputPath) {
+		Dataset<FOSDataModel> fosDataset = readPath(spark, sourcePath, FOSDataModel.class);
+
+		fosDataset.flatMap((FlatMapFunction<FOSDataModel, FOSDataModel>) v -> {
+			List<FOSDataModel> fosList = new ArrayList<>();
+			final String level1 = v.getLevel1();
+			final String level2 = v.getLevel2();
+			final String level3 = v.getLevel3();
+			Arrays
+				.stream(v.getDoi().split("\u0002"))
+				.forEach(d -> fosList.add(FOSDataModel.newInstance(d, level1, level2, level3)));
+			return fosList.iterator();
+		}, Encoders.bean(FOSDataModel.class))
+			.map((MapFunction<FOSDataModel, Result>) value -> {
+				Result r = new Result();
+				r.setId(DHPUtils.generateUnresolvedIdentifier(value.getDoi(), DOI));
+				r.setSubject(getSubjects(value));
+				return r;
+			}, Encoders.bean(Result.class))
+			.write()
+			.mode(SaveMode.Overwrite)
+			.option("compression", "gzip")
+			.json(outputPath + "/fos");
+	}
+
+	private static List<StructuredProperty> getSubjects(FOSDataModel fos) {
+		return Arrays
+			.asList(getSubject(fos.getLevel1()), getSubject(fos.getLevel2()), getSubject(fos.getLevel3()))
+			.stream()
+			.filter(Objects::nonNull)
+			.collect(Collectors.toList());
+	}
+
+	private static StructuredProperty getSubject(String sbj) {
+		if (sbj.equals(NULL))
+			return null;
+		StructuredProperty sp = new StructuredProperty();
+		sp.setValue(sbj);
+		sp
+			.setQualifier(
+				OafMapperUtils
+					.qualifier(
+						FOS_CLASS_ID,
+						FOS_CLASS_NAME,
+						ModelConstants.DNET_SUBJECT_TYPOLOGIES,
+						ModelConstants.DNET_SUBJECT_TYPOLOGIES));
+		sp
+			.setDataInfo(
+				OafMapperUtils
+					.dataInfo(
+						false,
+						UPDATE_DATA_INFO_TYPE,
+						true,
+						false,
+						OafMapperUtils
+							.qualifier(
+								UPDATE_SUBJECT_FOS_CLASS_ID,
+								UPDATE_CLASS_NAME,
+								ModelConstants.DNET_PROVENANCE_ACTIONS,
+								ModelConstants.DNET_PROVENANCE_ACTIONS),
+						""));
+
+		return sp;
+
+	}
+
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/SparkSaveUnresolved.java

@@ -0,0 +1,79 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
+
+import static eu.dnetlib.dhp.actionmanager.createunresolvedentities.Constants.*;
+import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
+
+import java.io.Serializable;
+
+import org.apache.commons.io.IOUtils;
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.function.MapFunction;
+import org.apache.spark.api.java.function.MapGroupsFunction;
+import org.apache.spark.sql.Encoders;
+import org.apache.spark.sql.SaveMode;
+import org.apache.spark.sql.SparkSession;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import eu.dnetlib.dhp.application.ArgumentApplicationParser;
+import eu.dnetlib.dhp.schema.oaf.Result;
+
+public class SparkSaveUnresolved implements Serializable {
+	private static final Logger log = LoggerFactory.getLogger(PrepareFOSSparkJob.class);
+
+	public static void main(String[] args) throws Exception {
+
+		String jsonConfiguration = IOUtils
+			.toString(
+				PrepareFOSSparkJob.class
+					.getResourceAsStream(
+						"/eu/dnetlib/dhp/actionmanager/createunresolvedentities/produce_unresolved_parameters.json"));
+
+		final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
+
+		parser.parseArgument(args);
+
+		Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
+		log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
+
+		String sourcePath = parser.get("sourcePath");
+		log.info("sourcePath: {}", sourcePath);
+
+		final String outputPath = parser.get("outputPath");
+		log.info("outputPath: {}", outputPath);
+
+		SparkConf conf = new SparkConf();
+		runWithSparkSession(
+			conf,
+			isSparkSessionManaged,
+			spark -> {
+				saveUnresolved(
+					spark,
+					sourcePath,
+
+					outputPath);
+			});
+	}
+
+	private static void saveUnresolved(SparkSession spark, String sourcePath, String outputPath) {
+
+		spark
+			.read()
+			.textFile(sourcePath + "/*")
+			.map(
+				(MapFunction<String, Result>) l -> OBJECT_MAPPER.readValue(l, Result.class),
+				Encoders.bean(Result.class))
+			.groupByKey((MapFunction<Result, String>) r -> r.getId(), Encoders.STRING())
+			.mapGroups((MapGroupsFunction<String, Result, Result>) (k, it) -> {
+				Result ret = it.next();
+				it.forEachRemaining(r -> ret.mergeFrom(r));
+				return ret;
+			}, Encoders.bean(Result.class))
+			.write()
+			.mode(SaveMode.Overwrite)
+			.option("compression", "gzip")
+			.json(outputPath);
+	}
+
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/model/BipDeserialize.java

@@ -0,0 +1,28 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities.model;
+
+import java.io.Serializable;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+
+/**
+ * Class that maps the model of the bipFinder! input data.
+ * Only needed for deserialization purposes
+ */
+
+public class BipDeserialize extends HashMap<String, List<Score>> implements Serializable {
+
+	public BipDeserialize() {
+		super();
+	}
+
+	public List<Score> get(String key) {
+
+		if (super.get(key) == null) {
+			return new ArrayList<>();
+		}
+		return super.get(key);
+	}
+
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/model/BipScore.java

@@ -0,0 +1,30 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities.model;
+
+import java.io.Serializable;
+import java.util.List;
+
+/**
+ * Rewriting of the bipFinder input data by extracting the identifier of the result (doi)
+ */
+
+public class BipScore implements Serializable {
+	private String id; // doi
+	private List<Score> scoreList; // unit as given in the inputfile
+
+	public String getId() {
+		return id;
+	}
+
+	public void setId(String id) {
+		this.id = id;
+	}
+
+	public List<Score> getScoreList() {
+		return scoreList;
+	}
+
+	public void setScoreList(List<Score> scoreList) {
+		this.scoreList = scoreList;
+	}
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/model/FOSDataModel.java

@@ -0,0 +1,71 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities.model;
+
+import java.io.Serializable;
+
+import com.opencsv.bean.CsvBindByPosition;
+
+public class FOSDataModel implements Serializable {
+	@CsvBindByPosition(position = 1)
+//    @CsvBindByName(column = "doi")
+	private String doi;
+
+	@CsvBindByPosition(position = 2)
+//    @CsvBindByName(column = "level1")
+	private String level1;
+
+	@CsvBindByPosition(position = 3)
+//    @CsvBindByName(column = "level2")
+	private String level2;
+
+	@CsvBindByPosition(position = 4)
+//    @CsvBindByName(column = "level3")
+	private String level3;
+
+	public FOSDataModel() {
+
+	}
+
+	public FOSDataModel(String doi, String level1, String level2, String level3) {
+		this.doi = doi;
+		this.level1 = level1;
+		this.level2 = level2;
+		this.level3 = level3;
+	}
+
+	public static FOSDataModel newInstance(String d, String level1, String level2, String level3) {
+		return new FOSDataModel(d, level1, level2, level3);
+	}
+
+	public String getDoi() {
+		return doi;
+	}
+
+	public void setDoi(String doi) {
+		this.doi = doi;
+	}
+
+	public String getLevel1() {
+		return level1;
+	}
+
+	public void setLevel1(String level1) {
+		this.level1 = level1;
+	}
+
+	public String getLevel2() {
+		return level2;
+	}
+
+	public void setLevel2(String level2) {
+		this.level2 = level2;
+	}
+
+	public String getLevel3() {
+		return level3;
+	}
+
+	public void setLevel3(String level3) {
+		this.level3 = level3;
+	}
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/model/KeyValue.java

@@ -0,0 +1,26 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities.model;
+
+import java.io.Serializable;
+
+public class KeyValue implements Serializable {
+
+	private String key;
+	private String value;
+
+	public String getKey() {
+		return key;
+	}
+
+	public void setKey(String key) {
+		this.key = key;
+	}
+
+	public String getValue() {
+		return value;
+	}
+
+	public void setValue(String value) {
+		this.value = value;
+	}
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/model/Score.java

@@ -0,0 +1,30 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities.model;
+
+import java.io.Serializable;
+import java.util.List;
+
+/**
+ * represents the score in the input file
+ */
+public class Score implements Serializable {
+
+	private String id;
+	private List<KeyValue> unit;
+
+	public String getId() {
+		return id;
+	}
+
+	public void setId(String id) {
+		this.id = id;
+	}
+
+	public List<KeyValue> getUnit() {
+		return unit;
+	}
+
+	public void setUnit(List<KeyValue> unit) {
+		this.unit = unit;
+	}
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/datacite/ExportActionSetJobNode.scala

@@ -1,41 +0,0 @@
-package eu.dnetlib.dhp.actionmanager.datacite
-
-import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.schema.oaf.Oaf
-import org.apache.hadoop.io.Text
-import org.apache.hadoop.io.compress.GzipCodec
-import org.apache.hadoop.mapred.SequenceFileOutputFormat
-import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
-import org.slf4j.{Logger, LoggerFactory}
-
-import scala.io.Source
-
-object ExportActionSetJobNode {
-
-  val log: Logger = LoggerFactory.getLogger(ExportActionSetJobNode.getClass)
-
-  def main(args: Array[String]): Unit = {
-    val conf = new SparkConf
-    val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/actionmanager/datacite/exportDataset_parameters.json")).mkString)
-    parser.parseArgument(args)
-    val master = parser.get("master")
-    val sourcePath = parser.get("sourcePath")
-    val targetPath = parser.get("targetPath")
-
-    val spark: SparkSession = SparkSession.builder().config(conf)
-      .appName(ExportActionSetJobNode.getClass.getSimpleName)
-      .master(master)
-      .getOrCreate()
-    implicit val resEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
-    implicit val tEncoder:Encoder[(String,String)] = Encoders.tuple(Encoders.STRING,Encoders.STRING)
-
-    spark.read.load(sourcePath).as[Oaf]
-      .map(o =>DataciteToOAFTransformation.toActionSet(o))
-      .filter(o => o!= null)
-      .rdd.map(s => (new Text(s._1), new Text(s._2))).saveAsHadoopFile(s"$targetPath", classOf[Text], classOf[Text], classOf[SequenceFileOutputFormat[Text,Text]], classOf[GzipCodec])
-
-
-  }
-
-}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/datacite/FilterCrossrefEntitiesSpark.scala

@@ -1,46 +0,0 @@
-package eu.dnetlib.dhp.actionmanager.datacite
-
-import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
-import eu.dnetlib.dhp.schema.mdstore.MetadataRecord
-import eu.dnetlib.dhp.schema.oaf.{Oaf, Result}
-import eu.dnetlib.dhp.utils.ISLookupClientFactory
-import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
-import org.slf4j.{Logger, LoggerFactory}
-
-import scala.io.Source
-
-object FilterCrossrefEntitiesSpark {
-
-  val log: Logger = LoggerFactory.getLogger(getClass.getClass)
-
-  def main(args: Array[String]): Unit = {
-    val conf = new SparkConf
-    val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/actionmanager/datacite/filter_crossref_param.json")).mkString)
-    parser.parseArgument(args)
-    val master = parser.get("master")
-    val sourcePath = parser.get("sourcePath")
-    log.info("sourcePath: {}", sourcePath)
-    val targetPath = parser.get("targetPath")
-    log.info("targetPath: {}", targetPath)
-
-
-
-    val spark: SparkSession = SparkSession.builder().config(conf)
-      .appName(getClass.getSimpleName)
-      .master(master)
-      .getOrCreate()
-
-
-
-    implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
-    implicit val resEncoder: Encoder[Result] = Encoders.kryo[Result]
-
-    val d:Dataset[Oaf]= spark.read.load(sourcePath).as[Oaf]
-
-    d.filter(r => r.isInstanceOf[Result]).map(r => r.asInstanceOf[Result]).write.mode(SaveMode.Overwrite).save(targetPath)
-
-  }
-
-}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/opencitations/CreateActionSetSparkJob.java

@@ -0,0 +1,181 @@
+
+package eu.dnetlib.dhp.actionmanager.opencitations;
+
+import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
+
+import java.io.IOException;
+import java.io.Serializable;
+import java.util.*;
+
+import org.apache.commons.cli.ParseException;
+import org.apache.commons.io.IOUtils;
+import org.apache.hadoop.io.Text;
+import org.apache.hadoop.mapred.SequenceFileOutputFormat;
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.function.FilterFunction;
+import org.apache.spark.api.java.function.FlatMapFunction;
+import org.apache.spark.sql.Encoders;
+import org.apache.spark.sql.SparkSession;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import eu.dnetlib.dhp.application.ArgumentApplicationParser;
+import eu.dnetlib.dhp.schema.action.AtomicAction;
+import eu.dnetlib.dhp.schema.common.ModelConstants;
+import eu.dnetlib.dhp.schema.common.ModelSupport;
+import eu.dnetlib.dhp.schema.oaf.*;
+import eu.dnetlib.dhp.schema.oaf.utils.CleaningFunctions;
+import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory;
+import scala.Tuple2;
+
+public class CreateActionSetSparkJob implements Serializable {
+	public static final String OPENCITATIONS_CLASSID = "sysimport:crosswalk:opencitations";
+	public static final String OPENCITATIONS_CLASSNAME = "Imported from OpenCitations";
+	private static final String ID_PREFIX = "50|doi_________::";
+	private static final String TRUST = "0.91";
+
+	private static final Logger log = LoggerFactory.getLogger(CreateActionSetSparkJob.class);
+	private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
+
+	public static void main(final String[] args) throws IOException, ParseException {
+
+		final ArgumentApplicationParser parser = new ArgumentApplicationParser(
+			IOUtils
+				.toString(
+					Objects
+						.requireNonNull(
+							CreateActionSetSparkJob.class
+								.getResourceAsStream(
+									"/eu/dnetlib/dhp/actionmanager/opencitations/as_parameters.json"))));
+
+		parser.parseArgument(args);
+
+		Boolean isSparkSessionManaged = Optional
+			.ofNullable(parser.get("isSparkSessionManaged"))
+			.map(Boolean::valueOf)
+			.orElse(Boolean.TRUE);
+
+		log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
+
+		final String inputPath = parser.get("inputPath");
+		log.info("inputPath {}", inputPath.toString());
+
+		final String outputPath = parser.get("outputPath");
+		log.info("outputPath {}", outputPath);
+
+		final boolean shouldDuplicateRels = Optional
+			.ofNullable(parser.get("shouldDuplicateRels"))
+			.map(Boolean::valueOf)
+			.orElse(Boolean.FALSE);
+
+		SparkConf conf = new SparkConf();
+		runWithSparkSession(
+			conf,
+			isSparkSessionManaged,
+			spark -> {
+				extractContent(spark, inputPath, outputPath, shouldDuplicateRels);
+			});
+
+	}
+
+	private static void extractContent(SparkSession spark, String inputPath, String outputPath,
+		boolean shouldDuplicateRels) {
+		spark
+			.sqlContext()
+			.createDataset(spark.sparkContext().textFile(inputPath + "/*", 6000), Encoders.STRING())
+			.flatMap(
+				(FlatMapFunction<String, Relation>) value -> createRelation(value, shouldDuplicateRels).iterator(),
+				Encoders.bean(Relation.class))
+			.filter((FilterFunction<Relation>) value -> value != null)
+			.toJavaRDD()
+			.map(p -> new AtomicAction(p.getClass(), p))
+			.mapToPair(
+				aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()),
+					new Text(OBJECT_MAPPER.writeValueAsString(aa))))
+			.saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class);
+
+	}
+
+	private static List<Relation> createRelation(String value, boolean duplicate) {
+		String[] line = value.split(",");
+		if (!line[1].startsWith("10.")) {
+			return new ArrayList<>();
+		}
+		List<Relation> relationList = new ArrayList<>();
+
+		String citing = ID_PREFIX + IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", line[1]));
+		final String cited = ID_PREFIX + IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", line[2]));
+
+		relationList
+			.addAll(
+				getRelations(
+					citing,
+					cited));
+
+		if (duplicate && line[1].endsWith(".refs")) {
+			citing = ID_PREFIX + IdentifierFactory
+				.md5(CleaningFunctions.normalizePidValue("doi", line[1].substring(0, line[1].indexOf(".refs"))));
+			relationList.addAll(getRelations(citing, cited));
+		}
+
+		return relationList;
+	}
+
+	private static Collection<Relation> getRelations(String citing, String cited) {
+
+		return Arrays
+			.asList(
+				getRelation(citing, cited, ModelConstants.CITES),
+				getRelation(cited, citing, ModelConstants.IS_CITED_BY));
+	}
+
+	public static Relation getRelation(
+		String source,
+		String target,
+		String relclass) {
+		Relation r = new Relation();
+		r.setCollectedfrom(getCollectedFrom());
+		r.setSource(source);
+		r.setTarget(target);
+		r.setRelClass(relclass);
+		r.setRelType(ModelConstants.RESULT_RESULT);
+		r.setSubRelType(ModelConstants.CITATION);
+		r
+			.setDataInfo(
+				getDataInfo());
+		return r;
+	}
+
+	public static List<KeyValue> getCollectedFrom() {
+		KeyValue kv = new KeyValue();
+		kv.setKey(ModelConstants.OPENOCITATIONS_ID);
+		kv.setValue(ModelConstants.OPENOCITATIONS_NAME);
+
+		return Arrays.asList(kv);
+	}
+
+	public static DataInfo getDataInfo() {
+		DataInfo di = new DataInfo();
+		di.setInferred(false);
+		di.setDeletedbyinference(false);
+		di.setTrust(TRUST);
+
+		di
+			.setProvenanceaction(
+				getQualifier(OPENCITATIONS_CLASSID, OPENCITATIONS_CLASSNAME, ModelConstants.DNET_PROVENANCE_ACTIONS));
+		return di;
+	}
+
+	public static Qualifier getQualifier(String class_id, String class_name,
+		String qualifierSchema) {
+		Qualifier pa = new Qualifier();
+		pa.setClassid(class_id);
+		pa.setClassname(class_name);
+		pa.setSchemeid(qualifierSchema);
+		pa.setSchemename(qualifierSchema);
+		return pa;
+	}
+
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/opencitations/GetOpenCitationsRefs.java

@@ -0,0 +1,93 @@
+
+package eu.dnetlib.dhp.actionmanager.opencitations;
+
+import java.io.*;
+import java.io.Serializable;
+import java.util.Objects;
+import java.util.zip.GZIPOutputStream;
+import java.util.zip.ZipEntry;
+import java.util.zip.ZipInputStream;
+
+import org.apache.commons.cli.ParseException;
+import org.apache.commons.io.IOUtils;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FSDataInputStream;
+import org.apache.hadoop.fs.FSDataOutputStream;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.Path;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import eu.dnetlib.dhp.application.ArgumentApplicationParser;
+
+public class GetOpenCitationsRefs implements Serializable {
+	private static final Logger log = LoggerFactory.getLogger(GetOpenCitationsRefs.class);
+
+	public static void main(final String[] args) throws IOException, ParseException {
+
+		final ArgumentApplicationParser parser = new ArgumentApplicationParser(
+			IOUtils
+				.toString(
+					Objects
+						.requireNonNull(
+							GetOpenCitationsRefs.class
+								.getResourceAsStream(
+									"/eu/dnetlib/dhp/actionmanager/opencitations/input_parameters.json"))));
+
+		parser.parseArgument(args);
+
+		final String[] inputFile = parser.get("inputFile").split(";");
+		log.info("inputFile {}", inputFile.toString());
+
+		final String workingPath = parser.get("workingPath");
+		log.info("workingPath {}", workingPath);
+
+		final String hdfsNameNode = parser.get("hdfsNameNode");
+		log.info("hdfsNameNode {}", hdfsNameNode);
+
+		Configuration conf = new Configuration();
+		conf.set("fs.defaultFS", hdfsNameNode);
+
+		FileSystem fileSystem = FileSystem.get(conf);
+
+		GetOpenCitationsRefs ocr = new GetOpenCitationsRefs();
+
+		for (String file : inputFile) {
+			ocr.doExtract(workingPath + "/Original/" + file, workingPath, fileSystem);
+		}
+
+	}
+
+	private void doExtract(String inputFile, String workingPath, FileSystem fileSystem)
+		throws IOException {
+
+		final Path path = new Path(inputFile);
+
+		FSDataInputStream oc_zip = fileSystem.open(path);
+
+		int count = 1;
+		try (ZipInputStream zis = new ZipInputStream(oc_zip)) {
+			ZipEntry entry = null;
+			while ((entry = zis.getNextEntry()) != null) {
+
+				if (!entry.isDirectory()) {
+					String fileName = entry.getName();
+					fileName = fileName.substring(0, fileName.indexOf("T")) + "_" + count;
+					count++;
+					try (
+						FSDataOutputStream out = fileSystem
+							.create(new Path(workingPath + "/COCI/" + fileName + ".gz"));
+						GZIPOutputStream gzipOs = new GZIPOutputStream(new BufferedOutputStream(out))) {
+
+						IOUtils.copy(zis, gzipOs);
+
+					}
+				}
+
+			}
+
+		}
+
+	}
+
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/collection/CollectionUtils.scala

@@ -0,0 +1,49 @@
+package eu.dnetlib.dhp.collection
+
+import eu.dnetlib.dhp.schema.common.ModelSupport
+import eu.dnetlib.dhp.schema.oaf.{Oaf, OafEntity, Relation}
+
+object CollectionUtils {
+
+  /**
+   * This method in pipeline to the transformation phase,
+   * generates relations in both verse, typically it should be a phase of flatMap
+   *
+   * @param i input OAF
+   * @return
+   * If the input OAF is an entity -> List(i)
+   * If the input OAF is a relation -> List(relation, inverseRelation)
+   *
+   */
+
+  def fixRelations(i: Oaf): List[Oaf] = {
+    if (i.isInstanceOf[OafEntity])
+      return List(i)
+    else {
+      val r: Relation = i.asInstanceOf[Relation]
+      val currentRel = ModelSupport.findRelation(r.getRelClass)
+      if (currentRel != null) {
+
+        // Cleaning relation
+        r.setRelType(currentRel.getRelType)
+        r.setSubRelType(currentRel.getSubReltype)
+        r.setRelClass(currentRel.getRelClass)
+        val inverse = new Relation
+        inverse.setSource(r.getTarget)
+        inverse.setTarget(r.getSource)
+        inverse.setRelType(currentRel.getRelType)
+        inverse.setSubRelType(currentRel.getSubReltype)
+        inverse.setRelClass(currentRel.getInverseRelClass)
+        inverse.setCollectedfrom(r.getCollectedfrom)
+        inverse.setDataInfo(r.getDataInfo)
+        inverse.setProperties(r.getProperties)
+        inverse.setLastupdatetimestamp(r.getLastupdatetimestamp)
+        inverse.setValidated(r.getValidated)
+        inverse.setValidationDate(r.getValidationDate)
+        return List(r, inverse)
+      }
+    }
+    List()
+  }
+
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/datacite/AbstractRestClient.scala

@@ -1,12 +1,10 @@
-package eu.dnetlib.dhp.actionmanager.datacite
+package eu.dnetlib.dhp.datacite
 
 import org.apache.commons.io.IOUtils
 import org.apache.http.client.config.RequestConfig
-import org.apache.http.client.methods.{HttpGet, HttpPost, HttpRequestBase, HttpUriRequest}
+import org.apache.http.client.methods.{HttpGet, HttpPost, HttpUriRequest}
 import org.apache.http.entity.StringEntity
-import org.apache.http.impl.client.{HttpClientBuilder, HttpClients}
-
-import java.io.IOException
+import org.apache.http.impl.client.HttpClientBuilder
 
 
 abstract class AbstractRestClient extends Iterator[String] {

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/datacite/DataciteAPIImporter.scala

@@ -1,7 +1,7 @@
-package eu.dnetlib.dhp.actionmanager.datacite
+package eu.dnetlib.dhp.datacite
 
-import org.json4s.{DefaultFormats, JValue}
 import org.json4s.jackson.JsonMethods.{compact, parse, render}
+import org.json4s.{DefaultFormats, JValue}
 
 class DataciteAPIImporter(timestamp: Long = 0, blocks: Long = 10, until:Long = -1) extends AbstractRestClient {
 

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/datacite/DataciteToOAFTransformation.scala

@@ -1,4 +1,4 @@
-package eu.dnetlib.dhp.actionmanager.datacite
+package eu.dnetlib.dhp.datacite
 
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
@@ -325,8 +325,9 @@ object DataciteToOAFTransformation {
       val grantId = m.matcher(awardUri).replaceAll("$2")
       val targetId = s"$p${DHPUtils.md5(grantId)}"
       List(
-        generateRelation(sourceId, targetId, "isProducedBy", DATACITE_COLLECTED_FROM, dataInfo),
-        generateRelation(targetId, sourceId, "produces", DATACITE_COLLECTED_FROM, dataInfo)
+        generateRelation(sourceId, targetId, "isProducedBy", DATACITE_COLLECTED_FROM, dataInfo)
+// REMOVED INVERSE RELATION since there is a specific method that should generate later
+//        generateRelation(targetId, sourceId, "produces", DATACITE_COLLECTED_FROM, dataInfo)
       )
     }
     else
@@ -580,11 +581,11 @@ object DataciteToOAFTransformation {
         rel.setProperties(List(dateProps).asJava)
 
         rel.setSource(id)
-        rel.setTarget(s"unresolved::${r.relatedIdentifier}::${r.relatedIdentifierType}")
+        rel.setTarget(DHPUtils.generateUnresolvedIdentifier(r.relatedIdentifier,r.relatedIdentifierType))
         rel.setCollectedfrom(List(DATACITE_COLLECTED_FROM).asJava)
-        rel.getCollectedfrom.asScala.map(c => c.getValue)(collection.breakOut)
+        rel.getCollectedfrom.asScala.map(c => c.getValue).toList
         rel
-      })(collection breakOut)
+      }).toList
   }
 
   def generateDataInfo(trust: String): DataInfo = {

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/datacite/GenerateDataciteDatasetSpark.scala

@@ -1,9 +1,14 @@
-package eu.dnetlib.dhp.actionmanager.datacite
+package eu.dnetlib.dhp.datacite
 
+import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
+import eu.dnetlib.dhp.collection.CollectionUtils.fixRelations
+import eu.dnetlib.dhp.common.Constants.MDSTORE_DATA_PATH
+import eu.dnetlib.dhp.common.Constants.MDSTORE_SIZE_PATH
 import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
-import eu.dnetlib.dhp.schema.mdstore.MetadataRecord
+import eu.dnetlib.dhp.schema.mdstore.{MDStoreVersion, MetadataRecord}
 import eu.dnetlib.dhp.schema.oaf.Oaf
+import eu.dnetlib.dhp.utils.DHPUtils.writeHdfsFile
 import eu.dnetlib.dhp.utils.ISLookupClientFactory
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
@@ -17,11 +22,10 @@ object GenerateDataciteDatasetSpark {
 
   def main(args: Array[String]): Unit = {
     val conf = new SparkConf
-    val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/actionmanager/datacite/generate_dataset_params.json")).mkString)
+    val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/datacite/generate_dataset_params.json")).mkString)
     parser.parseArgument(args)
     val master = parser.get("master")
     val sourcePath = parser.get("sourcePath")
-    val targetPath = parser.get("targetPath")
     val exportLinks = "true".equalsIgnoreCase(parser.get("exportLinks"))
     val isLookupUrl: String = parser.get("isLookupUrl")
     log.info("isLookupUrl: {}", isLookupUrl)
@@ -33,16 +37,28 @@ object GenerateDataciteDatasetSpark {
       .master(master)
       .getOrCreate()
 
+    import spark.implicits._
+
     implicit val mrEncoder: Encoder[MetadataRecord] = Encoders.kryo[MetadataRecord]
 
     implicit val resEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
 
-    import spark.implicits._
+    val mdstoreOutputVersion = parser.get("mdstoreOutputVersion")
+    val mapper = new ObjectMapper()
+    val cleanedMdStoreVersion = mapper.readValue(mdstoreOutputVersion, classOf[MDStoreVersion])
+    val outputBasePath = cleanedMdStoreVersion.getHdfsPath
+
+    log.info("outputBasePath: {}", outputBasePath)
+    val targetPath = s"$outputBasePath/$MDSTORE_DATA_PATH"
 
     spark.read.load(sourcePath).as[DataciteType]
       .filter(d => d.isActive)
       .flatMap(d => DataciteToOAFTransformation.generateOAF(d.json, d.timestamp, d.timestamp, vocabularies, exportLinks))
       .filter(d => d != null)
+      .flatMap(i => fixRelations(i)).filter(i => i != null)
       .write.mode(SaveMode.Overwrite).save(targetPath)
+
+    val total_items = spark.read.load(targetPath).as[Oaf].count()
+    writeHdfsFile(spark.sparkContext.hadoopConfiguration, s"$total_items", outputBasePath + MDSTORE_SIZE_PATH)
   }
-}
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/datacite/ImportDatacite.scala

@@ -1,6 +1,5 @@
-package eu.dnetlib.dhp.actionmanager.datacite
+package eu.dnetlib.dhp.datacite
 
-import eu.dnetlib.dhp.actionmanager.datacite.DataciteToOAFTransformation.df_it
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.fs.{FileSystem, LocalFileSystem, Path}
@@ -9,14 +8,14 @@ import org.apache.hadoop.io.{IntWritable, SequenceFile, Text}
 import org.apache.spark.SparkContext
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.expressions.Aggregator
+import org.apache.spark.sql.functions.max
 import org.apache.spark.sql.{Dataset, Encoder, SaveMode, SparkSession}
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
-import org.apache.spark.sql.functions.max
 import org.slf4j.{Logger, LoggerFactory}
 
-import java.time.format.DateTimeFormatter._
-import java.time.{LocalDate, LocalDateTime, ZoneOffset}
+import java.time.format.DateTimeFormatter.ISO_DATE_TIME
+import java.time.{LocalDateTime, ZoneOffset}
 import scala.io.Source
 
 object ImportDatacite {
@@ -138,11 +137,11 @@ object ImportDatacite {
     }
   }
 
-  private def writeSequenceFile(hdfsTargetPath: Path, timestamp: Long, conf: Configuration, bs:Int): Long = {
-    var from:Long = timestamp * 1000
-    val delta:Long = 100000000L
+  private def writeSequenceFile(hdfsTargetPath: Path, timestamp: Long, conf: Configuration, bs: Int): Long = {
+    var from: Long = timestamp * 1000
+    val delta: Long = 100000000L
     var client: DataciteAPIImporter = null
-    val now :Long =System.currentTimeMillis()
+    val now: Long = System.currentTimeMillis()
     var i = 0
     try {
       val writer = SequenceFile.createWriter(conf, SequenceFile.Writer.file(hdfsTargetPath), SequenceFile.Writer.keyClass(classOf[IntWritable]), SequenceFile.Writer.valueClass(classOf[Text]))
@@ -168,7 +167,7 @@ object ImportDatacite {
               start = System.currentTimeMillis
             }
           }
-          println(s"updating from value: $from  -> ${from+delta}")
+          println(s"updating from value: $from  -> ${from + delta}")
           from = from + delta
         }
       } catch {
@@ -183,4 +182,4 @@ object ImportDatacite {
     i
   }
 
-}
+}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/datacite/SparkDownloadUpdateDatacite.scala

@@ -1,18 +1,14 @@
-package eu.dnetlib.dhp.actionmanager.datacite
-
+package eu.dnetlib.dhp.datacite
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.schema.oaf.{Oaf, Result}
-import org.apache.hadoop.conf.Configuration
-import org.apache.hadoop.fs.LocalFileSystem
-import org.apache.hadoop.hdfs.DistributedFileSystem
 import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
 import org.apache.spark.sql.functions.max
+import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
 import org.slf4j.{Logger, LoggerFactory}
 
 import java.text.SimpleDateFormat
-import java.util.{Date, Locale}
+import java.util.Locale
 import scala.io.Source
 
 object SparkDownloadUpdateDatacite {
@@ -21,7 +17,7 @@ object SparkDownloadUpdateDatacite {
   def main(args: Array[String]): Unit = {
 
     val conf = new SparkConf
-    val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/actionmanager/datacite/generate_dataset_params.json")).mkString)
+    val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/datacite/generate_dataset_params.json")).mkString)
     parser.parseArgument(args)
     val master = parser.get("master")
     val sourcePath = parser.get("sourcePath")
@@ -42,9 +38,9 @@ object SparkDownloadUpdateDatacite {
     import spark.implicits._
 
 
-    val maxDate:String = spark.read.load(workingPath).as[Oaf].filter(s => s.isInstanceOf[Result]).map(r => r.asInstanceOf[Result].getDateofcollection).select(max("value")).first().getString(0)
+    val maxDate: String = spark.read.load(workingPath).as[Oaf].filter(s => s.isInstanceOf[Result]).map(r => r.asInstanceOf[Result].getDateofcollection).select(max("value")).first().getString(0)
     val ISO8601FORMAT = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ssZ", Locale.US)
-    val string_to_date =ISO8601FORMAT.parse(maxDate)
+    val string_to_date = ISO8601FORMAT.parse(maxDate)
     val ts = string_to_date.getTime
 
 

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/sx/bio/SparkTransformBioDatabaseToOAF.scala

@@ -3,6 +3,7 @@ package eu.dnetlib.dhp.sx.bio
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.schema.oaf.Oaf
 import BioDBToOAF.ScholixResolved
+import eu.dnetlib.dhp.collection.CollectionUtils
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
@@ -35,13 +36,13 @@ object SparkTransformBioDatabaseToOAF {
     import spark.implicits._
     database.toUpperCase() match {
       case "UNIPROT" =>
-        spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.uniprotToOAF(i))).write.mode(SaveMode.Overwrite).save(targetPath)
+        spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.uniprotToOAF(i))).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
       case "PDB" =>
-        spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.pdbTOOaf(i))).write.mode(SaveMode.Overwrite).save(targetPath)
+        spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.pdbTOOaf(i))).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
       case "SCHOLIX" =>
-        spark.read.load(dbPath).as[ScholixResolved].map(i => BioDBToOAF.scholixResolvedToOAF(i)).write.mode(SaveMode.Overwrite).save(targetPath)
+        spark.read.load(dbPath).as[ScholixResolved].map(i => BioDBToOAF.scholixResolvedToOAF(i)).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
       case "CROSSREF_LINKS" =>
-        spark.createDataset(sc.textFile(dbPath).map(i => BioDBToOAF.crossrefLinksToOaf(i))).write.mode(SaveMode.Overwrite).save(targetPath)
+        spark.createDataset(sc.textFile(dbPath).map(i => BioDBToOAF.crossrefLinksToOaf(i))).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
     }
   }
 

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/sx/bio/ebi/SparkEBILinksToOaf.scala

@@ -5,6 +5,7 @@ import eu.dnetlib.dhp.schema.oaf.Oaf
 import eu.dnetlib.dhp.sx.bio.BioDBToOAF
 import eu.dnetlib.dhp.sx.bio.BioDBToOAF.EBILinkItem
 import BioDBToOAF.EBILinkItem
+import eu.dnetlib.dhp.collection.CollectionUtils
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.sql._
@@ -37,6 +38,7 @@ object SparkEBILinksToOaf {
     ebLinks.flatMap(j => BioDBToOAF.parse_ebi_links(j.links))
       .filter(p => BioDBToOAF.EBITargetLinksFilter(p))
       .flatMap(p => BioDBToOAF.convertEBILinksToOaf(p))
+      .flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null)
       .write.mode(SaveMode.Overwrite).save(targetPath)
   }
 }

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/sx/bio/pubmed/PMArticle.java

@@ -5,94 +5,249 @@ import java.io.Serializable;
 import java.util.ArrayList;
 import java.util.List;
 
+/**
+ * This class represent an instance of Pubmed Article extracted from the native XML
+ *
+ * @author Sandro La Bruzzo
+ */
+
 public class PMArticle implements Serializable {
 
+	/**
+	 * the Pubmed Identifier
+	 */
 	private String pmid;
+	/**
+	 * the DOI
+	 */
 	private String doi;
+	/**
+	 * the Pubmed Date extracted from <PubmedPubDate> Specifies a date significant to either the article's history or the citation's processing.
+	 * All <History> dates will have a <Year>, <Month>, and <Day> elements. Some may have an <Hour>, <Minute>, and <Second> element(s).
+	 */
 	private String date;
+	/**
+	 * This is an 'envelop' element that contains various elements describing the journal cited; i.e., ISSN, Volume, Issue, and PubDate and author name(s), however, it does not contain data itself.
+	 */
 	private PMJournal journal;
+	/**
+	 * The full journal title (taken from NLM cataloging data following NLM rules for how to compile a serial name) is exported in this element. Some characters that are not part of the NLM MEDLINE/PubMed Character Set reside in a relatively small number of full journal titles. The NLM journal title abbreviation is exported in the <MedlineTA> element.
+	 */
 	private String title;
+	/**
+	 * English-language abstracts are taken directly from the published article.
+	 * If the article does not have a published abstract, the National Library of Medicine does not create one,
+	 * thus the record lacks the <Abstract> and <AbstractText> elements. However, in the absence of a formally
+	 * labeled abstract in the published article, text from a substantive "summary", "summary and conclusions" or "conclusions and summary" may be used.
+	 */
 	private String description;
+	/**
+	 * the language in which an article was published is recorded in <Language>.
+	 * All entries are three letter abbreviations stored in lower case, such as eng, fre, ger, jpn, etc. When a single
+	 * record contains more than one language value the XML export program extracts the languages in alphabetic order by the 3-letter language value.
+	 *  Some records provided by collaborating data producers may contain the value und to identify articles whose language is undetermined.
+	 */
 	private String language;
+
+	/**
+	 * NLM controlled vocabulary, Medical Subject Headings (MeSH®), is used to characterize the content of the articles represented by MEDLINE citations.	 *
+	 */
 	private final List<PMSubject> subjects = new ArrayList<>();
+	/**
+	 * This element is used to identify the type of article indexed for MEDLINE;
+	 * it characterizes the nature of the information or the manner in which it is conveyed as well as the type of
+	 * research support received (e.g., Review, Letter, Retracted Publication, Clinical Conference, Research Support, N.I.H., Extramural).
+	 */
 	private final List<PMSubject> publicationTypes = new ArrayList<>();
+	/**
+	 * Personal and collective (corporate) author names published with the article are found in <AuthorList>.
+	 */
 	private List<PMAuthor> authors = new ArrayList<>();
 
-	public List<PMSubject> getPublicationTypes() {
-		return publicationTypes;
-	}
-
+	/**
+	 * <GrantID> contains the research grant or contract number (or both) that designates financial support by any agency of the United States Public Health Service
+	 * or any institute of the National Institutes of Health. Additionally, beginning in late 2005, grant numbers are included for many other US and non-US funding agencies and organizations.
+	 */
 	private final List<PMGrant> grants = new ArrayList<>();
 
-	public List<PMGrant> getGrants() {
-		return grants;
-	}
-
+	/**
+	 * get the DOI
+	 * @return a DOI
+	 */
 	public String getDoi() {
 		return doi;
 	}
 
+	/**
+	 * Set the DOI
+	 * @param doi a DOI
+	 */
 	public void setDoi(String doi) {
 		this.doi = doi;
 	}
 
+	/**
+	 * get the Pubmed Identifier
+	 * @return the PMID
+	 */
 	public String getPmid() {
 		return pmid;
 	}
 
+	/**
+	 * set the Pubmed Identifier
+	 * @param pmid the Pubmed Identifier
+	 */
 	public void setPmid(String pmid) {
 		this.pmid = pmid;
 	}
 
+	/**
+	 * the Pubmed Date extracted from <PubmedPubDate> Specifies a date significant to either the article's history or the citation's processing.
+	 * All <History> dates will have a <Year>, <Month>, and <Day> elements. Some may have an <Hour>, <Minute>, and <Second> element(s).
+	 *
+	 * @return the Pubmed Date
+	 */
 	public String getDate() {
 		return date;
 	}
 
+	/**
+	 * Set the pubmed Date
+	 * @param date
+	 */
 	public void setDate(String date) {
 		this.date = date;
 	}
 
+	/**
+	 * The full journal title (taken from NLM cataloging data following NLM rules for how to compile a serial name) is exported in this element.
+		 * Some characters that are not part of the NLM MEDLINE/PubMed Character Set reside in a relatively small number of full journal titles.
+	 * The NLM journal title abbreviation is exported in the <MedlineTA> element.
+	 *
+	 * @return the pubmed Journal Extracted
+	 */
 	public PMJournal getJournal() {
 		return journal;
 	}
 
+	/**
+	 * Set the mapped pubmed Journal
+	 * @param journal
+	 */
 	public void setJournal(PMJournal journal) {
 		this.journal = journal;
 	}
 
+	/**
+	 * English-language abstracts are taken directly from the published article.
+	 * If the article does not have a published abstract, the National Library of Medicine does not create one,
+	 * thus the record lacks the <Abstract> and <AbstractText> elements. However, in the absence of a formally
+	 * labeled abstract in the published article, text from a substantive "summary", "summary and conclusions" or "conclusions and summary" may be used.
+	 *
+	 *  @return the extracted pubmed Title
+	 */
 	public String getTitle() {
 		return title;
 	}
 
+	/**
+	 * set the pubmed title
+	 * @param title
+	 */
 	public void setTitle(String title) {
 		this.title = title;
 	}
 
+	/**
+	 * English-language abstracts are taken directly from the published article.
+	 * If the article does not have a published abstract, the National Library of Medicine does not create one,
+	 * thus the record lacks the <Abstract> and <AbstractText> elements. However, in the absence of a formally
+	 * labeled abstract in the published article, text from a substantive "summary", "summary and conclusions" or "conclusions and summary" may be used.
+	 *
+	 * @return the Mapped Pubmed Article Abstracts
+	 */
 	public String getDescription() {
 		return description;
 	}
 
+	/**
+	 * Set the Mapped Pubmed Article Abstracts
+	 * @param description
+	 */
 	public void setDescription(String description) {
 		this.description = description;
 	}
 
+	/**
+	 * Personal and collective (corporate) author names published with the article are found in <AuthorList>.
+	 *
+	 * @return get the Mapped Authors lists
+	 */
 	public List<PMAuthor> getAuthors() {
 		return authors;
 	}
 
+	/**
+	 * Set the Mapped Authors lists
+	 * @param authors
+	 */
 	public void setAuthors(List<PMAuthor> authors) {
 		this.authors = authors;
 	}
 
+	/**
+	 * This element is used to identify the type of article indexed for MEDLINE;
+	 * it characterizes the nature of the information or the manner in which it is conveyed as well as the type of
+	 * research support received (e.g., Review, Letter, Retracted Publication, Clinical Conference, Research Support, N.I.H., Extramural).
+	 *
+	 * @return the mapped Subjects
+	 */
 	public List<PMSubject> getSubjects() {
 		return subjects;
 	}
 
+	/**
+	 *
+	 * the language in which an article was published is recorded in <Language>.
+	 * All entries are three letter abbreviations stored in lower case, such as eng, fre, ger, jpn, etc. When a single
+	 * record contains more than one language value the XML export program extracts the languages in alphabetic order by the 3-letter language value.
+	 *  Some records provided by collaborating data producers may contain the value und to identify articles whose language is undetermined.
+	 *
+	 * @return The mapped Language
+	 */
 	public String getLanguage() {
 		return language;
 	}
 
+	/**
+	 *
+	 *  Set The mapped Language
+	 *
+	 * @param language the mapped Language
+	 */
 	public void setLanguage(String language) {
 		this.language = language;
 	}
+
+	/**
+	 *  This element is used to identify the type of article indexed for MEDLINE;
+	 * it characterizes the nature of the information or the manner in which it is conveyed as well as the type of
+	 * research support received (e.g., Review, Letter, Retracted Publication, Clinical Conference, Research Support, N.I.H., Extramural).
+	 *
+	 * @return the mapped Publication Type
+	 */
+	public List<PMSubject> getPublicationTypes() {
+		return publicationTypes;
+	}
+
+	/**
+	 * <GrantID> contains the research grant or contract number (or both) that designates financial support by any agency of the United States Public Health Service
+	 * or any institute of the National Institutes of Health. Additionally, beginning in late 2005, grant numbers are included for many other US and non-US funding agencies and organizations.
+	 * @return the mapped grants
+	 */
+
+	public List<PMGrant> getGrants() {
+		return grants;
+	}
 }

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/sx/bio/pubmed/PMAuthor.java

@@ -3,27 +3,57 @@ package eu.dnetlib.dhp.sx.bio.pubmed;
 
 import java.io.Serializable;
 
+/**
+ * The type Pubmed author.
+ *
+ * @author Sandro La Bruzzo
+ */
 public class PMAuthor implements Serializable {
 
 	private String lastName;
 	private String foreName;
 
+	/**
+	 * Gets last name.
+	 *
+	 * @return the last name
+	 */
 	public String getLastName() {
 		return lastName;
 	}
 
+	/**
+	 * Sets last name.
+	 *
+	 * @param lastName the last name
+	 */
 	public void setLastName(String lastName) {
 		this.lastName = lastName;
 	}
 
+	/**
+	 * Gets fore name.
+	 *
+	 * @return the fore name
+	 */
 	public String getForeName() {
 		return foreName;
 	}
 
+	/**
+	 * Sets fore name.
+	 *
+	 * @param foreName the fore name
+	 */
 	public void setForeName(String foreName) {
 		this.foreName = foreName;
 	}
 
+	/**
+	 * Gets full name.
+	 *
+	 * @return the full name
+	 */
 	public String getFullName() {
 		return String
 			.format("%s, %s", this.foreName != null ? this.foreName : "", this.lastName != null ? this.lastName : "");

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/sx/bio/pubmed/PMGrant.java

@@ -1,41 +1,86 @@
 
 package eu.dnetlib.dhp.sx.bio.pubmed;
 
+/**
+ * The type Pm grant.
+ *
+ * @author Sandro La Bruzzo
+ */
 public class PMGrant {
 
 	private String grantID;
 	private String agency;
 	private String country;
 
+	/**
+	 * Instantiates a new Pm grant.
+	 */
 	public PMGrant() {
 	}
 
+	/**
+	 * Instantiates a new Pm grant.
+	 *
+	 * @param grantID the grant id
+	 * @param agency  the agency
+	 * @param country the country
+	 */
 	public PMGrant(String grantID, String agency, String country) {
 		this.grantID = grantID;
 		this.agency = agency;
 		this.country = country;
 	}
 
+	/**
+	 * Gets grant id.
+	 *
+	 * @return the grant id
+	 */
 	public String getGrantID() {
 		return grantID;
 	}
 
+	/**
+	 * Sets grant id.
+	 *
+	 * @param grantID the grant id
+	 */
 	public void setGrantID(String grantID) {
 		this.grantID = grantID;
 	}
 
+	/**
+	 * Gets agency.
+	 *
+	 * @return the agency
+	 */
 	public String getAgency() {
 		return agency;
 	}
 
+	/**
+	 * Sets agency.
+	 *
+	 * @param agency the agency
+	 */
 	public void setAgency(String agency) {
 		this.agency = agency;
 	}
 
+	/**
+	 * Gets country.
+	 *
+	 * @return the country
+	 */
 	public String getCountry() {
 		return country;
 	}
 
+	/**
+	 * Sets country.
+	 *
+	 * @param country the country
+	 */
 	public void setCountry(String country) {
 		this.country = country;
 	}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/sx/bio/pubmed/PMJournal.java

@@ -3,6 +3,11 @@ package eu.dnetlib.dhp.sx.bio.pubmed;
 
 import java.io.Serializable;
 
+/**
+ * The type Pm journal.
+ *
+ * @author  Sandro La Bruzzo
+ */
 public class PMJournal implements Serializable {
 
 	private String issn;
@@ -11,42 +16,92 @@ public class PMJournal implements Serializable {
 	private String date;
 	private String title;
 
+	/**
+	 * Gets issn.
+	 *
+	 * @return the issn
+	 */
 	public String getIssn() {
 		return issn;
 	}
 
+	/**
+	 * Sets issn.
+	 *
+	 * @param issn the issn
+	 */
 	public void setIssn(String issn) {
 		this.issn = issn;
 	}
 
+	/**
+	 * Gets volume.
+	 *
+	 * @return the volume
+	 */
 	public String getVolume() {
 		return volume;
 	}
 
+	/**
+	 * Sets volume.
+	 *
+	 * @param volume the volume
+	 */
 	public void setVolume(String volume) {
 		this.volume = volume;
 	}
 
+	/**
+	 * Gets issue.
+	 *
+	 * @return the issue
+	 */
 	public String getIssue() {
 		return issue;
 	}
 
+	/**
+	 * Sets issue.
+	 *
+	 * @param issue the issue
+	 */
 	public void setIssue(String issue) {
 		this.issue = issue;
 	}
 
+	/**
+	 * Gets date.
+	 *
+	 * @return the date
+	 */
 	public String getDate() {
 		return date;
 	}
 
+	/**
+	 * Sets date.
+	 *
+	 * @param date the date
+	 */
 	public void setDate(String date) {
 		this.date = date;
 	}
 
+	/**
+	 * Gets title.
+	 *
+	 * @return the title
+	 */
 	public String getTitle() {
 		return title;
 	}
 
+	/**
+	 * Sets title.
+	 *
+	 * @param title the title
+	 */
 	public void setTitle(String title) {
 		this.title = title;
 	}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/sx/bio/pubmed/PMParser.scala

@@ -2,6 +2,12 @@ package eu.dnetlib.dhp.sx.bio.pubmed
 
 import scala.xml.MetaData
 import scala.xml.pull.{EvElemEnd, EvElemStart, EvText, XMLEventReader}
+
+
+/**
+ *
+ * @param xml
+ */
 class PMParser(xml:XMLEventReader) extends Iterator[PMArticle] {
 
   var currentArticle:PMArticle = generateNextArticle()

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/sx/bio/pubmed/PMSubject.java

@@ -1,40 +1,83 @@
 
 package eu.dnetlib.dhp.sx.bio.pubmed;
 
+/**
+ * The type Pubmed subject.
+ */
 public class PMSubject {
 	private String value;
 	private String meshId;
 	private String registryNumber;
 
+	/**
+	 * Instantiates a new Pm subject.
+	 */
 	public PMSubject() {
 	}
 
+	/**
+	 * Instantiates a new Pm subject.
+	 *
+	 * @param value          the value
+	 * @param meshId         the mesh id
+	 * @param registryNumber the registry number
+	 */
 	public PMSubject(String value, String meshId, String registryNumber) {
 		this.value = value;
 		this.meshId = meshId;
 		this.registryNumber = registryNumber;
 	}
 
+	/**
+	 * Gets value.
+	 *
+	 * @return the value
+	 */
 	public String getValue() {
 		return value;
 	}
 
+	/**
+	 * Sets value.
+	 *
+	 * @param value the value
+	 */
 	public void setValue(String value) {
 		this.value = value;
 	}
 
+	/**
+	 * Gets mesh id.
+	 *
+	 * @return the mesh id
+	 */
 	public String getMeshId() {
 		return meshId;
 	}
 
+	/**
+	 * Sets mesh id.
+	 *
+	 * @param meshId the mesh id
+	 */
 	public void setMeshId(String meshId) {
 		this.meshId = meshId;
 	}
 
+	/**
+	 * Gets registry number.
+	 *
+	 * @return the registry number
+	 */
 	public String getRegistryNumber() {
 		return registryNumber;
 	}
 
+	/**
+	 * Sets registry number.
+	 *
+	 * @param registryNumber the registry number
+	 */
 	public void setRegistryNumber(String registryNumber) {
 		this.registryNumber = registryNumber;
 	}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/sx/bio/pubmed/PubMedToOaf.scala

@@ -8,6 +8,9 @@ import scala.collection.JavaConverters._
 
 import java.util.regex.Pattern
 
+/**
+ *
+ */
 object PubMedToOaf {
 
   val SUBJ_CLASS = "keywords"
@@ -15,7 +18,17 @@ object PubMedToOaf {
     "pmid" -> "https://pubmed.ncbi.nlm.nih.gov/",
     "doi" -> "https://dx.doi.org/"
   )
+  val dataInfo: DataInfo = OafMapperUtils.dataInfo(false, null, false, false, ModelConstants.PROVENANCE_ACTION_SET_QUALIFIER, "0.9")
+  val collectedFrom: KeyValue = OafMapperUtils.keyValue(ModelConstants.EUROPE_PUBMED_CENTRAL_ID, "Europe PubMed Central")
+
 
+
+  /**
+   * Cleaning the DOI Applying regex in order to
+   * remove doi starting with URL
+   * @param doi input DOI
+   * @return cleaned DOI
+   */
   def cleanDoi(doi: String): String = {
 
     val regex = "^10.\\d{4,9}\\/[\\[\\]\\-\\<\\>._;()\\/:A-Z0-9]+$"
@@ -30,6 +43,15 @@ object PubMedToOaf {
     null
   }
 
+  /**
+   *
+   * Create an instance of class extends Result
+   * starting from OAF instanceType value
+   *
+   * @param cobjQualifier OAF instance type
+   * @param vocabularies All dnet vocabularies
+   * @return the correct instance
+   */
   def createResult(cobjQualifier: Qualifier, vocabularies: VocabularyGroup): Result = {
     val result_typologies = getVocabularyTerm(ModelConstants.DNET_RESULT_TYPOLOGIES, vocabularies, cobjQualifier.getClassid)
     result_typologies.getClassid match {
@@ -42,6 +64,12 @@ object PubMedToOaf {
     }
   }
 
+  /**
+   *  Mapping the Pubmedjournal info into the OAF Journale
+   *
+   * @param j the pubmedJournal
+   * @return the OAF Journal
+   */
   def mapJournal(j: PMJournal): Journal = {
     if (j == null)
       return null
@@ -49,6 +77,7 @@ object PubMedToOaf {
 
     journal.setDataInfo(dataInfo)
     journal.setName(j.getTitle)
+    journal.setConferencedate(j.getDate)
     journal.setVol(j.getVolume)
     journal.setIssnPrinted(j.getIssn)
     journal.setIss(j.getIssue)
@@ -57,25 +86,43 @@ object PubMedToOaf {
 
   }
 
-
+  /**
+   *
+   * Find vocabulary term into synonyms and term in the vocabulary
+   *
+   * @param vocabularyName the input vocabulary name
+   * @param vocabularies all the vocabularies
+   * @param term the term to find
+   *
+   * @return the cleaned term value
+   */
   def getVocabularyTerm(vocabularyName: String, vocabularies: VocabularyGroup, term: String): Qualifier = {
     val a = vocabularies.getSynonymAsQualifier(vocabularyName, term)
     val b = vocabularies.getTermAsQualifier(vocabularyName, term)
     if (a == null) b else a
   }
 
-  val dataInfo: DataInfo = OafMapperUtils.dataInfo(false, null, false, false, ModelConstants.PROVENANCE_ACTION_SET_QUALIFIER, "0.9")
-  val collectedFrom: KeyValue = OafMapperUtils.keyValue(ModelConstants.EUROPE_PUBMED_CENTRAL_ID, "Europe PubMed Central")
 
+  /**
+   *  Map the Pubmed Article into the OAF instance
+   *
+   *
+   * @param article the pubmed articles
+   * @param vocabularies the vocabularies
+   * @return The OAF instance if the mapping did not fail
+   */
   def convert(article: PMArticle, vocabularies: VocabularyGroup): Result = {
 
     if (article.getPublicationTypes == null)
       return null
-    val i = new Instance
+
+
+    // MAP PMID into  pid with  classid = classname = pmid
     val pidList: List[StructuredProperty] = List(OafMapperUtils.structuredProperty(article.getPmid, PidType.pmid.toString, PidType.pmid.toString, ModelConstants.DNET_PID_TYPES, ModelConstants.DNET_PID_TYPES, dataInfo))
     if (pidList == null)
       return null
 
+    // MAP //ArticleId[./@IdType="doi"]   into  alternateIdentifier with classid = classname = doi
     var alternateIdentifier: StructuredProperty = null
     if (article.getDoi != null) {
       val normalizedPid = cleanDoi(article.getDoi)
@@ -83,43 +130,64 @@ object PubMedToOaf {
         alternateIdentifier = OafMapperUtils.structuredProperty(normalizedPid, PidType.doi.toString, PidType.doi.toString, ModelConstants.DNET_PID_TYPES, ModelConstants.DNET_PID_TYPES, dataInfo)
     }
 
+    // INSTANCE MAPPING
+    //--------------------------------------------------------------------------------------
+
     // If the article contains the typology Journal Article then we apply this type
     //else We have to find a terms that match the vocabulary otherwise we discard it
     val ja = article.getPublicationTypes.asScala.find(s => "Journal Article".equalsIgnoreCase(s.getValue))
+    val pubmedInstance = new Instance
     if (ja.isDefined) {
       val cojbCategory = getVocabularyTerm(ModelConstants.DNET_PUBLICATION_RESOURCE, vocabularies, ja.get.getValue)
-      i.setInstancetype(cojbCategory)
+      pubmedInstance.setInstancetype(cojbCategory)
     } else {
       val i_type = article.getPublicationTypes.asScala
         .map(s => getVocabularyTerm(ModelConstants.DNET_PUBLICATION_RESOURCE, vocabularies, s.getValue))
         .find(q => q != null)
       if (i_type.isDefined)
-        i.setInstancetype(i_type.get)
+        pubmedInstance.setInstancetype(i_type.get)
       else
         return null
     }
-    val result = createResult(i.getInstancetype, vocabularies)
+    val result = createResult(pubmedInstance.getInstancetype, vocabularies)
     if (result == null)
       return result
     result.setDataInfo(dataInfo)
-    i.setPid(pidList.asJava)
+    pubmedInstance.setPid(pidList.asJava)
     if (alternateIdentifier != null)
-      i.setAlternateIdentifier(List(alternateIdentifier).asJava)
-    result.setInstance(List(i).asJava)
-    i.getPid.asScala.filter(p => "pmid".equalsIgnoreCase(p.getQualifier.getClassid)).map(p => p.getValue)(collection.breakOut)
+      pubmedInstance.setAlternateIdentifier(List(alternateIdentifier).asJava)
+    result.setInstance(List(pubmedInstance).asJava)
+    pubmedInstance.getPid.asScala.filter(p => "pmid".equalsIgnoreCase(p.getQualifier.getClassid)).map(p => p.getValue)(collection.breakOut)
+    //CREATE URL From pmid
     val urlLists: List[String] = pidList
       .map(s => (urlMap.getOrElse(s.getQualifier.getClassid, ""), s.getValue))
       .filter(t => t._1.nonEmpty)
       .map(t => t._1 + t._2)
     if (urlLists != null)
-      i.setUrl(urlLists.asJava)
-    i.setDateofacceptance(OafMapperUtils.field(GraphCleaningFunctions.cleanDate(article.getDate), dataInfo))
-    i.setCollectedfrom(collectedFrom)
+      pubmedInstance.setUrl(urlLists.asJava)
+
+    //ASSIGN DateofAcceptance
+    pubmedInstance.setDateofacceptance(OafMapperUtils.field(GraphCleaningFunctions.cleanDate(article.getDate), dataInfo))
+    //ASSIGN COLLECTEDFROM
+    pubmedInstance.setCollectedfrom(collectedFrom)
     result.setPid(pidList.asJava)
+
+    //END INSTANCE MAPPING
+    //--------------------------------------------------------------------------------------
+
+
+    // JOURNAL MAPPING
+    //--------------------------------------------------------------------------------------
     if (article.getJournal != null && result.isInstanceOf[Publication])
       result.asInstanceOf[Publication].setJournal(mapJournal(article.getJournal))
     result.setCollectedfrom(List(collectedFrom).asJava)
+    //END JOURNAL MAPPING
+    //--------------------------------------------------------------------------------------
+
 
+
+    // RESULT MAPPING
+    //--------------------------------------------------------------------------------------
     result.setDateofacceptance(OafMapperUtils.field(GraphCleaningFunctions.cleanDate(article.getDate), dataInfo))
 
     if (article.getTitle == null || article.getTitle.isEmpty)
@@ -159,6 +227,9 @@ object PubMedToOaf {
 
     result.setId(article.getPmid)
 
+
+    // END RESULT MAPPING
+    //--------------------------------------------------------------------------------------
     val id = IdentifierFactory.createIdentifier(result)
     if (article.getPmid.equalsIgnoreCase(id))
       return null

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/createunresolvedentities/get_fos_parameters.json

@@ -0,0 +1,33 @@
+[
+  {
+    "paramName":"s",
+    "paramLongName":"sourcePath",
+    "paramDescription": "the path of the sequencial file to read",
+    "paramRequired": true
+  },
+  {
+    "paramName":"out",
+    "paramLongName":"outputPath",
+    "paramDescription": "the output path",
+    "paramRequired": true
+  },
+
+  {
+    "paramName": "ssm",
+    "paramLongName": "isSparkSessionManaged",
+    "paramDescription": "true if the spark session is managed, false otherwise",
+    "paramRequired": false
+  },
+  {
+    "paramName": "hnn",
+    "paramLongName": "hdfsNameNode",
+    "paramDescription": "the path used to store the HostedByMap",
+    "paramRequired": true
+  },
+  {
+    "paramName": "cfn",
+    "paramLongName": "classForName",
+    "paramDescription": "the path used to store the HostedByMap",
+    "paramRequired": true
+  }
+]

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/createunresolvedentities/oozie_app/config-default.xml

@@ -12,12 +12,19 @@
         <value>true</value>
     </property>
     <property>
-        <name>oozie.action.sharelib.for.spark</name>
-        <value>spark2</value>
+        <name>hiveMetastoreUris</name>
+        <value>thrift://iis-cdh5-test-m3.ocean.icm.edu.pl:9083</value>
+    </property>
+    <property>
+        <name>hiveJdbcUrl</name>
+        <value>jdbc:hive2://iis-cdh5-test-m3.ocean.icm.edu.pl:10000</value>
+    </property>
+    <property>
+        <name>hiveDbName</name>
+        <value>openaire</value>
     </property>
-
     <property>
         <name>oozie.launcher.mapreduce.user.classpath.first</name>
         <value>true</value>
     </property>
-</configuration>
+</configuration>

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/createunresolvedentities/oozie_app/workflow.xml

@@ -0,0 +1,174 @@
+
+<workflow-app name="UnresolvedEntities" xmlns="uri:oozie:workflow:0.5">
+    <parameters>
+        <property>
+            <name>fosPath</name>
+            <description>the input path of the resources to be extended</description>
+        </property>
+
+        <property>
+            <name>bipScorePath</name>
+            <description>the path where to find the bipFinder scores</description>
+        </property>
+        <property>
+            <name>outputPath</name>
+            <description>the path where to store the actionset</description>
+        </property>
+        <property>
+            <name>sparkDriverMemory</name>
+            <description>memory for driver process</description>
+        </property>
+        <property>
+            <name>sparkExecutorMemory</name>
+            <description>memory for individual executor</description>
+        </property>
+        <property>
+            <name>sparkExecutorCores</name>
+            <description>number of cores used by single executor</description>
+        </property>
+        <property>
+            <name>oozieActionShareLibForSpark2</name>
+            <description>oozie action sharelib for spark 2.*</description>
+        </property>
+        <property>
+            <name>spark2ExtraListeners</name>
+            <value>com.cloudera.spark.lineage.NavigatorAppListener</value>
+            <description>spark 2.* extra listeners classname</description>
+        </property>
+        <property>
+            <name>spark2SqlQueryExecutionListeners</name>
+            <value>com.cloudera.spark.lineage.NavigatorQueryListener</value>
+            <description>spark 2.* sql query execution listeners classname</description>
+        </property>
+        <property>
+            <name>spark2YarnHistoryServerAddress</name>
+            <description>spark 2.* yarn history server address</description>
+        </property>
+        <property>
+            <name>spark2EventLogDir</name>
+            <description>spark 2.* event log dir location</description>
+        </property>
+    </parameters>
+
+    <global>
+        <job-tracker>${jobTracker}</job-tracker>
+        <name-node>${nameNode}</name-node>
+        <configuration>
+            <property>
+                <name>mapreduce.job.queuename</name>
+                <value>${queueName}</value>
+            </property>
+            <property>
+                <name>oozie.launcher.mapred.job.queue.name</name>
+                <value>${oozieLauncherQueueName}</value>
+            </property>
+            <property>
+                <name>oozie.action.sharelib.for.spark</name>
+                <value>${oozieActionShareLibForSpark2}</value>
+            </property>
+
+        </configuration>
+    </global>
+    <start to="prepareInfo"/>
+
+    <kill name="Kill">
+        <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
+    </kill>
+
+
+    <fork name="prepareInfo">
+        <path start="prepareBip"/>
+        <path start="getFOS"/>
+    </fork>
+
+    <action name="prepareBip">
+        <spark xmlns="uri:oozie:spark-action:0.2">
+            <master>yarn</master>
+            <mode>cluster</mode>
+            <name>Produces the unresolved from bip finder!</name>
+            <class>eu.dnetlib.dhp.actionmanager.createunresolvedentities.PrepareBipFinder</class>
+            <jar>dhp-aggregation-${projectVersion}.jar</jar>
+            <spark-opts>
+                --executor-memory=${sparkExecutorMemory}
+                --executor-cores=${sparkExecutorCores}
+                --driver-memory=${sparkDriverMemory}
+                --conf spark.extraListeners=${spark2ExtraListeners}
+                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
+                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
+                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
+                --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
+            </spark-opts>
+            <arg>--sourcePath</arg><arg>${bipScorePath}</arg>
+            <arg>--outputPath</arg><arg>${workingDir}/prepared</arg>
+        </spark>
+        <ok to="join"/>
+        <error to="Kill"/>
+    </action>
+
+    <action name="getFOS">
+        <java>
+            <main-class>eu.dnetlib.dhp.actionmanager.createunresolvedentities.GetFOSData</main-class>
+            <arg>--hdfsNameNode</arg><arg>${nameNode}</arg>
+            <arg>--sourcePath</arg><arg>${fosPath}</arg>
+            <arg>--outputPath</arg><arg>${workingDir}/input/fos</arg>
+            <arg>--classForName</arg><arg>eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.FOSDataModel</arg>
+        </java>
+        <ok to="prepareFos"/>
+        <error to="Kill"/>
+    </action>
+
+    <action name="prepareFos">
+        <spark xmlns="uri:oozie:spark-action:0.2">
+            <master>yarn</master>
+            <mode>cluster</mode>
+            <name>Produces the unresolved from FOS!</name>
+            <class>eu.dnetlib.dhp.actionmanager.createunresolvedentities.PrepareFOSSparkJob</class>
+            <jar>dhp-aggregation-${projectVersion}.jar</jar>
+            <spark-opts>
+                --executor-memory=${sparkExecutorMemory}
+                --executor-cores=${sparkExecutorCores}
+                --driver-memory=${sparkDriverMemory}
+                --conf spark.extraListeners=${spark2ExtraListeners}
+                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
+                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
+                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
+                --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
+            </spark-opts>
+            <arg>--sourcePath</arg><arg>${workingDir}/input/fos</arg>
+            <arg>--outputPath</arg><arg>${workingDir}/prepared</arg>
+
+        </spark>
+        <ok to="join"/>
+        <error to="Kill"/>
+    </action>
+
+
+
+    <join name="join" to="produceUnresolved"/>
+
+    <action name="produceUnresolved">
+        <spark xmlns="uri:oozie:spark-action:0.2">
+            <master>yarn</master>
+            <mode>cluster</mode>
+            <name>Saves the result produced for bip and fos by grouping results with the same id</name>
+            <class>eu.dnetlib.dhp.actionmanager.createunresolvedentities.SparkSaveUnresolved</class>
+            <jar>dhp-aggregation-${projectVersion}.jar</jar>
+            <spark-opts>
+                --executor-memory=${sparkExecutorMemory}
+                --executor-cores=${sparkExecutorCores}
+                --driver-memory=${sparkDriverMemory}
+                --conf spark.extraListeners=${spark2ExtraListeners}
+                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
+                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
+                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
+                --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
+            </spark-opts>
+            <arg>--sourcePath</arg><arg>${workingDir}/prepared</arg>
+            <arg>--outputPath</arg><arg>${outputPath}</arg>
+        </spark>
+        <ok to="End"/>
+        <error to="Kill"/>
+    </action>
+
+    <end name="End"/>
+</workflow-app>

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/createunresolvedentities/prepare_parameters.json

@@ -0,0 +1,20 @@
+[
+  {
+    "paramName": "issm",
+    "paramLongName": "isSparkSessionManaged",
+    "paramDescription": "when true will stop SparkSession after job execution",
+    "paramRequired": false
+  },
+  {
+    "paramName": "sp",
+    "paramLongName": "sourcePath",
+    "paramDescription": "the URL from where to get the programme file",
+    "paramRequired": true
+  },
+  {
+    "paramName": "o",
+    "paramLongName": "outputPath",
+    "paramDescription": "the path of the new ActionSet",
+    "paramRequired": true
+  }
+]

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/createunresolvedentities/produce_unresolved_parameters.json

@@ -0,0 +1,20 @@
+[
+  {
+    "paramName": "issm",
+    "paramLongName": "isSparkSessionManaged",
+    "paramDescription": "when true will stop SparkSession after job execution",
+    "paramRequired": false
+  },
+  {
+    "paramName": "sp",
+    "paramLongName": "sourcePath",
+    "paramDescription": "the URL from where to get the programme file",
+    "paramRequired": true
+  },
+  {
+    "paramName": "o",
+    "paramLongName": "outputPath",
+    "paramDescription": "the path of the new ActionSet",
+    "paramRequired": true
+  }
+]

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/datacite/oozie_app/workflow.xml

@@ -1,81 +0,0 @@
-<workflow-app name="Import_Datacite_and_transform_to_OAF" xmlns="uri:oozie:workflow:0.5">
-    <parameters>
-        <property>
-            <name>mainPath</name>
-            <description>the working path of Datacite stores</description>
-        </property>
-        <property>
-            <name>isLookupUrl</name>
-            <description>The IS lookUp service endopoint</description>
-        </property>
-        <property>
-            <name>blocksize</name>
-            <value>100</value>
-            <description>The request block size</description>
-        </property>
-
-    </parameters>
-
-    <start to="ImportDatacite"/>
-
-    <kill name="Kill">
-        <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
-    </kill>
-
-
-    <action name="ImportDatacite">
-        <spark xmlns="uri:oozie:spark-action:0.2">
-            <master>yarn-cluster</master>
-            <mode>cluster</mode>
-            <name>ImportDatacite</name>
-            <class>eu.dnetlib.dhp.actionmanager.datacite.ImportDatacite</class>
-            <jar>dhp-aggregation-${projectVersion}.jar</jar>
-            <spark-opts>
-                --executor-memory=${sparkExecutorMemory}
-                --executor-cores=${sparkExecutorCores}
-                --driver-memory=${sparkDriverMemory}
-                --conf spark.extraListeners=${spark2ExtraListeners}
-                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
-                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
-                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
-            </spark-opts>
-            <arg>--targetPath</arg><arg>${mainPath}/datacite_update</arg>
-            <arg>--dataciteDumpPath</arg><arg>${mainPath}/datacite_dump</arg>
-            <arg>--namenode</arg><arg>${nameNode}</arg>
-            <arg>--master</arg><arg>yarn-cluster</arg>
-            <arg>--blocksize</arg><arg>${blocksize}</arg>
-        </spark>
-        <ok to="TransformJob"/>
-        <error to="Kill"/>
-    </action>
-
-
-    <action name="TransformJob">
-        <spark xmlns="uri:oozie:spark-action:0.2">
-            <master>yarn-cluster</master>
-            <mode>cluster</mode>
-            <name>TransformJob</name>
-            <class>eu.dnetlib.dhp.actionmanager.datacite.GenerateDataciteDatasetSpark</class>
-            <jar>dhp-aggregation-${projectVersion}.jar</jar>
-            <spark-opts>
-                --executor-memory=${sparkExecutorMemory}
-                --executor-cores=${sparkExecutorCores}
-                --driver-memory=${sparkDriverMemory}
-                --conf spark.sql.shuffle.partitions=3840
-                --conf spark.extraListeners=${spark2ExtraListeners}
-                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
-                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
-                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
-            </spark-opts>
-            <arg>--sourcePath</arg><arg>${mainPath}/datacite_dump</arg>
-            <arg>--targetPath</arg><arg>${mainPath}/datacite_oaf</arg>
-            <arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
-            <arg>--exportLinks</arg><arg>false</arg>
-            <arg>--master</arg><arg>yarn-cluster</arg>
-        </spark>
-        <ok to="End"/>
-        <error to="Kill"/>
-    </action>
-
-    <end name="End"/>
-</workflow-app>

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/datacite/scholix/oozie_app/workflow.xml

@@ -1,84 +0,0 @@
-<workflow-app name="Generate_Datacite_and_Crossref_dump_for_Scholexplorer" xmlns="uri:oozie:workflow:0.5">
-    <parameters>
-        <property>
-            <name>datacitePath</name>
-            <description>the path of Datacite spark dataset</description>
-        </property>
-        <property>
-            <name>isLookupUrl</name>
-            <description>The IS lookUp service endopoint</description>
-        </property>
-        <property>
-            <name>crossrefPath</name>
-            <description>the path of Crossref spark dataset</description>
-        </property>
-
-        <property>
-            <name>targetPath</name>
-            <description>the path of Crossref spark dataset</description>
-        </property>
-
-    </parameters>
-
-    <start to="ImportDatacite"/>
-
-    <kill name="Kill">
-        <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
-    </kill>
-
-
-    <action name="ImportDatacite">
-        <spark xmlns="uri:oozie:spark-action:0.2">
-            <master>yarn-cluster</master>
-            <mode>cluster</mode>
-            <name>ImportDatacite</name>
-            <class>eu.dnetlib.dhp.actionmanager.datacite.GenerateDataciteDatasetSpark</class>
-            <jar>dhp-aggregation-${projectVersion}.jar</jar>
-            <spark-opts>
-                --executor-memory=${sparkExecutorMemory}
-                --executor-cores=${sparkExecutorCores}
-                --driver-memory=${sparkDriverMemory}
-                --conf spark.sql.shuffle.partitions=3840
-                --conf spark.extraListeners=${spark2ExtraListeners}
-                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
-                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
-                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
-            </spark-opts>
-            <arg>--sourcePath</arg><arg>${datacitePath}</arg>
-            <arg>--targetPath</arg><arg>${targetPath}/datacite_oaf</arg>
-            <arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
-            <arg>--exportLinks</arg><arg>true</arg>
-            <arg>--master</arg><arg>yarn-cluster</arg>
-        </spark>
-        <ok to="FilterCrossrefEntities"/>
-        <error to="Kill"/>
-    </action>
-
-
-    <action name="FilterCrossrefEntities">
-        <spark xmlns="uri:oozie:spark-action:0.2">
-            <master>yarn-cluster</master>
-            <mode>cluster</mode>
-            <name>FilterCrossrefEntities</name>
-            <class>eu.dnetlib.dhp.actionmanager.datacite.FilterCrossrefEntitiesSpark</class>
-            <jar>dhp-aggregation-${projectVersion}.jar</jar>
-            <spark-opts>
-                --executor-memory=${sparkExecutorMemory}
-                --executor-cores=${sparkExecutorCores}
-                --driver-memory=${sparkDriverMemory}
-                --conf spark.sql.shuffle.partitions=3840
-                --conf spark.extraListeners=${spark2ExtraListeners}
-                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
-                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
-                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
-            </spark-opts>
-            <arg>--sourcePath</arg><arg>${crossrefPath}</arg>
-            <arg>--targetPath</arg><arg>${targetPath}/crossref_oaf</arg>
-            <arg>--master</arg><arg>yarn-cluster</arg>
-        </spark>
-        <ok to="End"/>
-        <error to="Kill"/>
-    </action>
-
-    <end name="End"/>
-</workflow-app>

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/opencitations/as_parameters.json

@@ -0,0 +1,25 @@
+[
+  {
+    "paramName": "ip",
+    "paramLongName": "inputPath",
+    "paramDescription": "the zipped opencitations file",
+    "paramRequired": true
+  },
+  {
+    "paramName": "op",
+    "paramLongName": "outputPath",
+    "paramDescription": "the working path",
+    "paramRequired": true
+  },
+  {
+    "paramName": "issm",
+    "paramLongName": "isSparkSessionManaged",
+    "paramDescription": "the hdfs name node",
+    "paramRequired": false
+  },  {
+  "paramName": "sdr",
+  "paramLongName": "shouldDuplicateRels",
+  "paramDescription": "the hdfs name node",
+  "paramRequired": false
+}
+]

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/opencitations/input_parameters.json

@@ -0,0 +1,20 @@
+[
+  {
+    "paramName": "if",
+    "paramLongName": "inputFile",
+    "paramDescription": "the zipped opencitations file",
+    "paramRequired": true
+  },
+  {
+    "paramName": "wp",
+    "paramLongName": "workingPath",
+    "paramDescription": "the working path",
+    "paramRequired": true
+  },
+  {
+    "paramName": "hnn",
+    "paramLongName": "hdfsNameNode",
+    "paramDescription": "the hdfs name node",
+    "paramRequired": true
+  }
+]

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/opencitations/oozie_app/config-default.xml

@@ -0,0 +1,58 @@
+<configuration>
+    <property>
+        <name>jobTracker</name>
+        <value>yarnRM</value>
+    </property>
+    <property>
+        <name>nameNode</name>
+        <value>hdfs://nameservice1</value>
+    </property>
+    <property>
+        <name>oozie.use.system.libpath</name>
+        <value>true</value>
+    </property>
+    <property>
+        <name>oozie.action.sharelib.for.spark</name>
+        <value>spark2</value>
+    </property>
+    <property>
+        <name>hive_metastore_uris</name>
+        <value>thrift://iis-cdh5-test-m3.ocean.icm.edu.pl:9083</value>
+    </property>
+    <property>
+        <name>spark2YarnHistoryServerAddress</name>
+        <value>http://iis-cdh5-test-gw.ocean.icm.edu.pl:18089</value>
+    </property>
+    <property>
+        <name>spark2ExtraListeners</name>
+        <value>com.cloudera.spark.lineage.NavigatorAppListener</value>
+    </property>
+    <property>
+        <name>spark2SqlQueryExecutionListeners</name>
+        <value>com.cloudera.spark.lineage.NavigatorQueryListener</value>
+    </property>
+    <property>
+        <name>oozie.launcher.mapreduce.user.classpath.first</name>
+        <value>true</value>
+    </property>
+    <property>
+        <name>sparkExecutorNumber</name>
+        <value>4</value>
+    </property>
+    <property>
+        <name>spark2EventLogDir</name>
+        <value>/user/spark/spark2ApplicationHistory</value>
+    </property>
+    <property>
+        <name>sparkDriverMemory</name>
+        <value>15G</value>
+    </property>
+    <property>
+        <name>sparkExecutorMemory</name>
+        <value>6G</value>
+    </property>
+    <property>
+        <name>sparkExecutorCores</name>
+        <value>1</value>
+    </property>
+</configuration>

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/opencitations/oozie_app/download.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+for file in $(echo $1 | tr ";" "\n"); do curl -L $(echo $file | cut -d '@' -f 1 ) | hdfs dfs -put - $2/$(echo $file | cut -d '@' -f 2)  ; done;

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/opencitations/oozie_app/workflow.xml

@@ -0,0 +1,91 @@
+<workflow-app name="OpenCitations Integration" xmlns="uri:oozie:workflow:0.5">
+
+    <global>
+        <job-tracker>${jobTracker}</job-tracker>
+        <name-node>${nameNode}</name-node>
+        <configuration>
+            <property>
+                <name>mapreduce.job.queuename</name>
+                <value>${queueName}</value>
+            </property>
+            <property>
+                <name>oozie.launcher.mapred.job.queue.name</name>
+                <value>${oozieLauncherQueueName}</value>
+            </property>
+            <property>
+                <name>oozie.action.sharelib.for.spark</name>
+                <value>${oozieActionShareLibForSpark2}</value>
+            </property>
+
+        </configuration>
+    </global>
+
+    <start to="resume_from"/>
+
+    <decision name="resume_from">
+        <switch>
+            <case to="download">${wf:conf('resumeFrom') eq 'DownloadDump'}</case>
+            <case to="extract">${wf:conf('resumeFrom') eq 'ExtractContent'}</case>
+            <default to="create_actionset"/> <!-- first action to be done when downloadDump is to be performed -->
+        </switch>
+    </decision>
+
+    <kill name="Kill">
+        <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
+    </kill>
+    <action name="download">
+        <shell xmlns="uri:oozie:shell-action:0.2">
+            <job-tracker>${jobTracker}</job-tracker>
+            <name-node>${nameNode}</name-node>
+            <configuration>
+                <property>
+                    <name>mapred.job.queue.name</name>
+                    <value>${queueName}</value>
+                </property>
+            </configuration>
+            <exec>download.sh</exec>
+            <argument>${filelist}</argument>
+            <argument>${workingPath}/Original</argument>
+            <env-var>HADOOP_USER_NAME=${wf:user()}</env-var>
+            <file>download.sh</file>
+            <capture-output/>
+        </shell>
+        <ok to="extract"/>
+        <error to="Kill"/>
+    </action>
+    <action name="extract">
+        <java>
+            <main-class>eu.dnetlib.dhp.actionmanager.opencitations.GetOpenCitationsRefs</main-class>
+            <arg>--hdfsNameNode</arg><arg>${nameNode}</arg>
+            <arg>--inputFile</arg><arg>${inputFile}</arg>
+            <arg>--workingPath</arg><arg>${workingPath}</arg>
+        </java>
+        <ok to="create_actionset"/>
+        <error to="Kill"/>
+    </action>
+
+    <action name="create_actionset">
+        <spark xmlns="uri:oozie:spark-action:0.2">
+            <master>yarn</master>
+            <mode>cluster</mode>
+            <name>Produces the AS for OC</name>
+            <class>eu.dnetlib.dhp.actionmanager.opencitations.CreateActionSetSparkJob</class>
+            <jar>dhp-aggregation-${projectVersion}.jar</jar>
+            <spark-opts>
+                --executor-memory=${sparkExecutorMemory}
+                --executor-cores=${sparkExecutorCores}
+                --driver-memory=${sparkDriverMemory}
+                --conf spark.extraListeners=${spark2ExtraListeners}
+                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
+                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
+                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
+                --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
+            </spark-opts>
+            <arg>--inputPath</arg><arg>${workingPath}/COCI</arg>
+            <arg>--outputPath</arg><arg>${outputPath}</arg>
+        </spark>
+        <ok to="End"/>
+        <error to="Kill"/>
+    </action>
+    <end name="End"/>
+</workflow-app>

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/opencitations/opencitations_parameters.json

@@ -0,0 +1,8 @@
+[
+  {"paramName":"n",   "paramLongName":"hdfsServerUri",	"paramDescription": "the server uri",   "paramRequired": true},
+  {"paramName":"w",   "paramLongName":"workingPath",	"paramDescription": "the default work path",	"paramRequired": true},
+  {"paramName":"f",   "paramLongName":"opencitationFile",	"paramDescription": "the name of the file",	"paramRequired": true},
+  {"paramName":"issm",   "paramLongName":"isSparkSessionManaged",	"paramDescription": "the name of the activities orcid file",	"paramRequired": false},
+  {"paramName":"o",   "paramLongName":"outputPath",	"paramDescription": "the name of the activities orcid file",	"paramRequired": true}
+
+]

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/datacite/collection/oozie_app/workflow.xml

@@ -1,46 +1,52 @@
-<workflow-app name="Datacite_to_ActionSet_Workflow" xmlns="uri:oozie:workflow:0.5">
+<workflow-app name="Collect_Datacite" xmlns="uri:oozie:workflow:0.5">
     <parameters>
         <property>
-            <name>sourcePath</name>
+            <name>mainPath</name>
             <description>the working path of Datacite stores</description>
         </property>
         <property>
-            <name>outputPath</name>
-            <description>the path of Datacite ActionSet</description>
+            <name>isLookupUrl</name>
+            <description>The IS lookUp service endopoint</description>
         </property>
+        <property>
+            <name>blocksize</name>
+            <value>100</value>
+            <description>The request block size</description>
+        </property>
+
     </parameters>
 
-    <start to="ExportDataset"/>
+    <start to="ImportDatacite"/>
 
     <kill name="Kill">
         <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
     </kill>
 
 
-    <action name="ExportDataset">
+    <action name="ImportDatacite">
         <spark xmlns="uri:oozie:spark-action:0.2">
             <master>yarn-cluster</master>
             <mode>cluster</mode>
-            <name>ExportDataset</name>
-            <class>eu.dnetlib.dhp.actionmanager.datacite.ExportActionSetJobNode</class>
+            <name>ImportDatacite</name>
+            <class>eu.dnetlib.dhp.datacite.ImportDatacite</class>
             <jar>dhp-aggregation-${projectVersion}.jar</jar>
             <spark-opts>
                 --executor-memory=${sparkExecutorMemory}
                 --executor-cores=${sparkExecutorCores}
                 --driver-memory=${sparkDriverMemory}
-                --conf spark.sql.shuffle.partitions=3840
                 --conf spark.extraListeners=${spark2ExtraListeners}
                 --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
                 --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
             </spark-opts>
-            <arg>--sourcePath</arg><arg>${sourcePath}</arg>
-            <arg>--targetPath</arg><arg>${outputPath}</arg>
+            <arg>--targetPath</arg><arg>${mainPath}/datacite_update</arg>
+            <arg>--dataciteDumpPath</arg><arg>${mainPath}/datacite_dump</arg>
+            <arg>--namenode</arg><arg>${nameNode}</arg>
             <arg>--master</arg><arg>yarn-cluster</arg>
+            <arg>--blocksize</arg><arg>${blocksize}</arg>
         </spark>
         <ok to="End"/>
         <error to="Kill"/>
     </action>
-
     <end name="End"/>
 </workflow-app>

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/datacite/generate_dataset_params.json

@@ -7,8 +7,8 @@
   },
 
   {
-    "paramName": "t",
-    "paramLongName": "targetPath",
+    "paramName": "mo",
+    "paramLongName": "mdstoreOutputVersion",
     "paramDescription": "the target mdstore path",
     "paramRequired": true
   },

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/datacite/transformation/oozie_app/workflow.xml

@@ -0,0 +1,126 @@
+<workflow-app name="transform_Datacite" xmlns="uri:oozie:workflow:0.5">
+    <parameters>
+        <property>
+            <name>mainPath</name>
+            <description>the working path of Datacite stores</description>
+        </property>
+        <property>
+            <name>isLookupUrl</name>
+            <description>The IS lookUp service endopoint</description>
+        </property>
+        <property>
+            <name>mdStoreOutputId</name>
+            <description>the identifier of the cleaned MDStore</description>
+        </property>
+        <property>
+            <name>mdStoreManagerURI</name>
+            <description>the path of the cleaned mdstore</description>
+        </property>
+    </parameters>
+
+    <start to="StartTransaction"/>
+
+    <kill name="Kill">
+        <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
+    </kill>
+
+    <action name="StartTransaction">
+        <java>
+            <configuration>
+                <property>
+                    <name>oozie.launcher.mapreduce.user.classpath.first</name>
+                    <value>true</value>
+                </property>
+            </configuration>
+            <main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
+            <arg>--action</arg><arg>NEW_VERSION</arg>
+            <arg>--mdStoreID</arg><arg>${mdStoreOutputId}</arg>
+            <arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
+            <capture-output/>
+        </java>
+        <ok to="TransformJob"/>
+        <error to="EndReadRollBack"/>
+    </action>
+
+    <action name="TransformJob">
+        <spark xmlns="uri:oozie:spark-action:0.2">
+            <master>yarn-cluster</master>
+            <mode>cluster</mode>
+            <name>TransformJob</name>
+            <class>eu.dnetlib.dhp.datacite.GenerateDataciteDatasetSpark</class>
+            <jar>dhp-aggregation-${projectVersion}.jar</jar>
+            <spark-opts>
+                --executor-memory=${sparkExecutorMemory}
+                --executor-cores=${sparkExecutorCores}
+                --driver-memory=${sparkDriverMemory}
+                --conf spark.sql.shuffle.partitions=3840
+                --conf spark.extraListeners=${spark2ExtraListeners}
+                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
+                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
+                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
+            </spark-opts>
+            <arg>--sourcePath</arg><arg>${mainPath}/datacite_dump</arg>
+            <arg>--mdstoreOutputVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
+            <arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
+            <arg>--exportLinks</arg><arg>true</arg>
+            <arg>--master</arg><arg>yarn-cluster</arg>
+        </spark>
+        <ok to="CommitVersion"/>
+        <error to="Kill"/>
+    </action>
+
+    <action name="CommitVersion">
+        <java>
+            <configuration>
+                <property>
+                    <name>oozie.launcher.mapreduce.user.classpath.first</name>
+                    <value>true</value>
+                </property>
+            </configuration>
+            <main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
+            <arg>--action</arg><arg>COMMIT</arg>
+            <arg>--namenode</arg><arg>${nameNode}</arg>
+            <arg>--mdStoreVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
+            <arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
+        </java>
+        <ok to="End"/>
+        <error to="Kill"/>
+    </action>
+
+    <action name="EndReadRollBack">
+        <java>
+            <configuration>
+                <property>
+                    <name>oozie.launcher.mapreduce.user.classpath.first</name>
+                    <value>true</value>
+                </property>
+            </configuration>
+            <main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
+            <arg>--action</arg><arg>READ_UNLOCK</arg>
+            <arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
+            <arg>--readMDStoreId</arg><arg>${wf:actionData('BeginRead')['mdStoreReadLockVersion']}</arg>
+            <capture-output/>
+        </java>
+        <ok to="RollBack"/>
+        <error to="Kill"/>
+    </action>
+
+    <action name="RollBack">
+        <java>
+            <configuration>
+                <property>
+                    <name>oozie.launcher.mapreduce.user.classpath.first</name>
+                    <value>true</value>
+                </property>
+            </configuration>
+            <main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
+            <arg>--action</arg><arg>ROLLBACK</arg>
+            <arg>--mdStoreVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
+            <arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
+        </java>
+        <ok to="Kill"/>
+        <error to="Kill"/>
+    </action>
+
+    <end name="End"/>
+</workflow-app>

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/sx/bio/ebi/oozie_app/workflow.xml

@@ -52,7 +52,7 @@
             <master>yarn-cluster</master>
             <mode>cluster</mode>
             <name>Incremental Download EBI Links</name>
-            <class>eu.dnetllib.dhp.sx.bio.ebi.SparkDownloadEBILinks</class>
+            <class>eu.dnetlib.dhp.sx.bio.ebi.SparkDownloadEBILinks</class>
             <jar>dhp-aggregation-${projectVersion}.jar</jar>
             <spark-opts>
                 --executor-memory=${sparkExecutorMemory}
@@ -85,7 +85,7 @@
             <master>yarn-cluster</master>
             <mode>cluster</mode>
             <name>Create OAF DataSet</name>
-            <class>eu.dnetllib.dhp.sx.bio.ebi.SparkEBILinksToOaf</class>
+            <class>eu.dnetlib.dhp.sx.bio.ebi.SparkEBILinksToOaf</class>
             <jar>dhp-aggregation-${projectVersion}.jar</jar>
             <spark-opts>
                 --executor-memory=${sparkExecutorMemory}

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/sx/bio/pubmed/oozie_app/workflow.xml

@@ -30,7 +30,7 @@
             <master>yarn</master>
             <mode>cluster</mode>
             <name>Convert Baseline to OAF Dataset</name>
-            <class>eu.dnetllib.dhp.sx.bio.ebi.SparkCreateBaselineDataFrame</class>
+            <class>eu.dnetlib.dhp.sx.bio.ebi.SparkCreateBaselineDataFrame</class>
             <jar>dhp-aggregation-${projectVersion}.jar</jar>
             <spark-opts>
                 --executor-memory=${sparkExecutorMemory}

dhp-workflows/dhp-aggregation/src/site/markdown/index.md

@@ -0,0 +1,9 @@
+##DHP-Aggregation
+
+This module defines a set of oozie workflows for the **collection** and **transformation** of metadata records.
+
+Both workflows interact with the Metadata Store Manager (MdSM) to handle the logical transactions required to ensure
+the consistency of the read/write operations on the data as the MdSM in fact keeps track of the logical-physical mapping
+of each MDStore.
+
+It defines [mappings](mappings.md) for transformation of different datasource (See mapping section).

dhp-workflows/dhp-aggregation/src/site/markdown/introduction.md

@@ -0,0 +1,7 @@
+##DHP-Aggregation
+
+This module defines a set of oozie workflows for the **collection** and **transformation** of metadata records.
+
+Both workflows interact with the Metadata Store Manager (MdSM) to handle the logical transactions required to ensure
+the consistency of the read/write operations on the data as the MdSM in fact keeps track of the logical-physical mapping
+of each MDStore.

dhp-workflows/dhp-aggregation/src/site/markdown/mappings.md

@@ -0,0 +1,18 @@
+DHP Aggregation
+===============
+
+DHP-Aggregations contains different mappings from original data format into OAF Data Format, 
+which converge in the graph in different ways:
+
+- Via Action Manager
+- Direct in the MdStore on Hadoop
+
+Below the list of the implemented mapping
+
+
+Mappings
+=======
+
+1. [PubMed](pubmed.md)
+2. [Datacite](datacite.md)
+

dhp-workflows/dhp-aggregation/src/site/markdown/pubmed.md

@@ -0,0 +1,62 @@
+#Pubmed Mapping
+This section describes the mapping implemented for [MEDLINE/PubMed](https://pubmed.ncbi.nlm.nih.gov/).
+
+Collection
+---------
+The native data is collected from [ftp baseline](https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/) containing XML with 
+the following [shcema](https://www.nlm.nih.gov/bsd/licensee/elements_descriptions.html) 
+
+
+Parsing
+-------
+The resposible class of parsing is [PMParser](./scaladocs/#eu.dnetlib.dhp.sx.bio.pubmed.PMParser) that generates 
+an intermediate mapping of PubMed Article defined [here](/apidocs/eu/dnetlib/dhp/sx/bio/pubmed/package-summary.html)
+
+
+Mapping
+-------
+
+The table below describes the mapping from the XML Native to the OAF mapping
+
+
+
+
+
+| Xpath Source | Oaf Field  | Notes       |
+| ----------- | ----------- | ----------- |
+| //PMID      | pid         | classid = classname = pmid
+|  | **Instance Mapping** |      |
+|//PublicationType | InstanceType  | If the article contains the typology **Journal Article** then we apply this type else We have to find a terms that match the vocabulary otherwise we discard it
+|//PMID | instance/PID | Map the pmid also in the pid in the instance |
+| //ArticleId[./@IdType="doi"   | instance/alternateIdentifier  |classid = classname = doi
+|//PMID | instance/URL | prepend to the PMId the base url https://pubmed.ncbi.nlm.nih.gov/
+| //PubmedPubDate | instance/Dateofacceptance | apply the function GraphCleaningFunctions.cleanDate before assign it
+|  FOR ALL INSTANCE | CollectedFrom | datasourceName: *Europe PubMed Central* DatasourceId:   
+|  | **Journal Mapping** |      |
+|//Journal/PubDate| Journal/Conferencedate | map the date of the Journal
+|//Journal/Title| Journal/Name | |
+|//Journal/Volume| Journal/Vol | |
+|//Journal/ISSN| Journal/issPrinted | |
+|//Journal/Issue| Journal/Iss | |
+|  | **Publication Mapping** |      |
+| //PubmedPubDate | Dateofacceptance | apply the function GraphCleaningFunctions.cleanDate before assign it
+| //Title | title | with qualifier ModelConstants.MAIN_TITLE_QUALIFIER
+| //AbstractText | Description ||
+|//Language| Language| cleaning vocabulary -> dnet:languages
+|//DescriptorName| Subject | classId, className = keyword
+|  | **Author Mapping** |      |
+|//Author/LastName| author.Surname| |
+|//Author/ForeName| author.Forename| |
+|//Author/FullName| author.Forename| Concatenation of forname + lastName if exist |
+|FOR ALL AUTHOR | author.rank| sequential number starting from 1|
+
+
+
+
+
+
+
+
+
+
+

dhp-workflows/dhp-aggregation/src/site/site.xml

@@ -0,0 +1,32 @@
+<?xml version="1.0" encoding="ISO-8859-1"?>
+<project xmlns="http://maven.apache.org/DECORATION/1.8.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+         xsi:schemaLocation="http://maven.apache.org/DECORATION/1.8.0 https://maven.apache.org/xsd/decoration-1.8.0.xsd"
+         name="DHP-Aggregation">
+    <skin>
+        <groupId>org.apache.maven.skins</groupId>
+        <artifactId>maven-fluido-skin</artifactId>
+        <version>1.8</version>
+    </skin>
+    <poweredBy>
+        <logo name="OpenAIRE Research Graph" href="https://graph.openaire.eu/"
+              img="https://graph.openaire.eu/assets/common-assets/logo-large-graph.png"/>
+    </poweredBy>
+    <body>
+        <links>
+            <item name="Code" href="https://code-repo.d4science.org/" />
+        </links>
+        <menu name="Documentation">
+            <item name="Mappings" href="mappings.html" collapse="true">
+                <item name="Pubmed" href="pubmed.html"/>
+                <item name="Datacite" href="datacite.html"/>
+            </item>
+            <item name="Release Notes" href="release-notes.html" />
+            <item name="General Information" href="about.html"/>
+
+            <item name="JavaDoc" href="apidocs/" />
+            <item name="ScalaDoc" href="scaladocs/" />
+
+        </menu>
+        <menu ref="reports"/>
+    </body>
+</project>

dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/PrepareTest.java

@@ -0,0 +1,250 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
+
+import static org.junit.jupiter.api.Assertions.*;
+
+import java.io.BufferedReader;
+import java.io.IOException;
+import java.io.InputStreamReader;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.util.stream.Collectors;
+
+import org.apache.commons.io.FileUtils;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.LocalFileSystem;
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.sql.SparkSession;
+import org.junit.jupiter.api.AfterAll;
+import org.junit.jupiter.api.Assertions;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Test;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.FOSDataModel;
+import eu.dnetlib.dhp.common.collection.CollectorException;
+import eu.dnetlib.dhp.schema.oaf.Result;
+
+public class PrepareTest {
+
+	private static final Logger log = LoggerFactory.getLogger(ProduceTest.class);
+
+	private static Path workingDir;
+	private static SparkSession spark;
+	private static LocalFileSystem fs;
+	private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
+
+	@BeforeAll
+	public static void beforeAll() throws IOException {
+		workingDir = Files.createTempDirectory(PrepareTest.class.getSimpleName());
+
+		fs = FileSystem.getLocal(new Configuration());
+		log.info("using work dir {}", workingDir);
+
+		SparkConf conf = new SparkConf();
+		conf.setAppName(ProduceTest.class.getSimpleName());
+
+		conf.setMaster("local[*]");
+		conf.set("spark.driver.host", "localhost");
+		conf.set("hive.metastore.local", "true");
+		conf.set("spark.ui.enabled", "false");
+		conf.set("spark.sql.warehouse.dir", workingDir.toString());
+		conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString());
+
+		spark = SparkSession
+			.builder()
+			.appName(PrepareTest.class.getSimpleName())
+			.config(conf)
+			.getOrCreate();
+	}
+
+	@AfterAll
+	public static void afterAll() throws IOException {
+		FileUtils.deleteDirectory(workingDir.toFile());
+		spark.stop();
+	}
+
+	@Test
+	void bipPrepareTest() throws Exception {
+		final String sourcePath = getClass()
+			.getResource("/eu/dnetlib/dhp/actionmanager/createunresolvedentities/bip/bip.json")
+			.getPath();
+
+		PrepareBipFinder
+			.main(
+				new String[] {
+					"--isSparkSessionManaged", Boolean.FALSE.toString(),
+					"--sourcePath", sourcePath,
+					"--outputPath", workingDir.toString() + "/work"
+
+				});
+
+		final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
+
+		JavaRDD<Result> tmp = sc
+			.textFile(workingDir.toString() + "/work/bip")
+			.map(item -> OBJECT_MAPPER.readValue(item, Result.class));
+
+		Assertions.assertEquals(86, tmp.count());
+
+		String doi1 = "unresolved::10.0000/096020199389707::doi";
+
+		Assertions.assertEquals(1, tmp.filter(r -> r.getId().equals(doi1)).count());
+		Assertions.assertEquals(3, tmp.filter(r -> r.getId().equals(doi1)).collect().get(0).getMeasures().size());
+		Assertions
+			.assertEquals(
+				"6.34596412687e-09", tmp
+					.filter(r -> r.getId().equals(doi1))
+					.collect()
+					.get(0)
+					.getMeasures()
+					.stream()
+					.filter(sl -> sl.getId().equals("influence"))
+					.collect(Collectors.toList())
+					.get(0)
+					.getUnit()
+					.get(0)
+					.getValue());
+		Assertions
+			.assertEquals(
+				"0.641151896994", tmp
+					.filter(r -> r.getId().equals(doi1))
+					.collect()
+					.get(0)
+					.getMeasures()
+					.stream()
+					.filter(sl -> sl.getId().equals("popularity_alt"))
+					.collect(Collectors.toList())
+					.get(0)
+					.getUnit()
+					.get(0)
+					.getValue());
+		Assertions
+			.assertEquals(
+				"2.33375102921e-09", tmp
+					.filter(r -> r.getId().equals(doi1))
+					.collect()
+					.get(0)
+					.getMeasures()
+					.stream()
+					.filter(sl -> sl.getId().equals("popularity"))
+					.collect(Collectors.toList())
+					.get(0)
+					.getUnit()
+					.get(0)
+					.getValue());
+
+	}
+
+	@Test
+	void getFOSFileTest() throws IOException, ClassNotFoundException {
+
+		final String sourcePath = getClass()
+			.getResource("/eu/dnetlib/dhp/actionmanager/createunresolvedentities/fos/h2020_fos_sbs.csv")
+			.getPath();
+		final String outputPath = workingDir.toString() + "/fos.json";
+
+		new GetFOSData()
+			.doRewrite(
+				sourcePath, outputPath, "eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.FOSDataModel",
+				'\t', fs);
+
+		BufferedReader in = new BufferedReader(
+			new InputStreamReader(fs.open(new org.apache.hadoop.fs.Path(outputPath))));
+
+		String line;
+		int count = 0;
+		while ((line = in.readLine()) != null) {
+			FOSDataModel fos = new ObjectMapper().readValue(line, FOSDataModel.class);
+
+			System.out.println(new ObjectMapper().writeValueAsString(fos));
+			count += 1;
+		}
+
+		assertEquals(38, count);
+
+	}
+
+	@Test
+	void fosPrepareTest() throws Exception {
+		final String sourcePath = getClass()
+			.getResource("/eu/dnetlib/dhp/actionmanager/createunresolvedentities/fos/fos.json")
+			.getPath();
+
+		PrepareFOSSparkJob
+			.main(
+				new String[] {
+					"--isSparkSessionManaged", Boolean.FALSE.toString(),
+					"--sourcePath", sourcePath,
+
+					"-outputPath", workingDir.toString() + "/work"
+
+				});
+
+		final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
+
+		JavaRDD<Result> tmp = sc
+			.textFile(workingDir.toString() + "/work/fos")
+			.map(item -> OBJECT_MAPPER.readValue(item, Result.class));
+
+		String doi1 = "unresolved::10.3390/s18072310::doi";
+
+		assertEquals(50, tmp.count());
+		assertEquals(1, tmp.filter(row -> row.getId().equals(doi1)).count());
+		assertTrue(
+			tmp
+				.filter(r -> r.getId().equals(doi1))
+				.flatMap(r -> r.getSubject().iterator())
+				.map(sbj -> sbj.getValue())
+				.collect()
+				.contains("engineering and technology"));
+
+		assertTrue(
+			tmp
+				.filter(r -> r.getId().equals(doi1))
+				.flatMap(r -> r.getSubject().iterator())
+				.map(sbj -> sbj.getValue())
+				.collect()
+				.contains("nano-technology"));
+		assertTrue(
+			tmp
+				.filter(r -> r.getId().equals(doi1))
+				.flatMap(r -> r.getSubject().iterator())
+				.map(sbj -> sbj.getValue())
+				.collect()
+				.contains("nanoscience & nanotechnology"));
+
+		String doi = "unresolved::10.1111/1365-2656.12831::doi";
+		assertEquals(1, tmp.filter(row -> row.getId().equals(doi)).count());
+		assertTrue(
+			tmp
+				.filter(r -> r.getId().equals(doi))
+				.flatMap(r -> r.getSubject().iterator())
+				.map(sbj -> sbj.getValue())
+				.collect()
+				.contains("psychology and cognitive sciences"));
+
+		assertTrue(
+			tmp
+				.filter(r -> r.getId().equals(doi))
+				.flatMap(r -> r.getSubject().iterator())
+				.map(sbj -> sbj.getValue())
+				.collect()
+				.contains("social sciences"));
+		assertFalse(
+			tmp
+				.filter(r -> r.getId().equals(doi))
+				.flatMap(r -> r.getSubject().iterator())
+				.map(sbj -> sbj.getValue())
+				.collect()
+				.contains("NULL"));
+
+	}
+
+}

dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/createunresolvedentities/ProduceTest.java

@@ -0,0 +1,234 @@
+
+package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
+
+import java.io.IOException;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.util.List;
+import java.util.stream.Collectors;
+
+import org.apache.commons.io.FileUtils;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.LocalFileSystem;
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.sql.SparkSession;
+import org.junit.jupiter.api.AfterAll;
+import org.junit.jupiter.api.Assertions;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Test;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import eu.dnetlib.dhp.schema.common.ModelConstants;
+import eu.dnetlib.dhp.schema.oaf.*;
+
+public class ProduceTest {
+	private static final Logger log = LoggerFactory.getLogger(ProduceTest.class);
+
+	private static Path workingDir;
+	private static SparkSession spark;
+	private static LocalFileSystem fs;
+	private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
+	private static final String ID_PREFIX = "50|doi_________";
+
+	@BeforeAll
+	public static void beforeAll() throws IOException {
+		workingDir = Files.createTempDirectory(ProduceTest.class.getSimpleName());
+
+		fs = FileSystem.getLocal(new Configuration());
+		log.info("using work dir {}", workingDir);
+
+		SparkConf conf = new SparkConf();
+		conf.setAppName(ProduceTest.class.getSimpleName());
+
+		conf.setMaster("local[*]");
+		conf.set("spark.driver.host", "localhost");
+		conf.set("hive.metastore.local", "true");
+		conf.set("spark.ui.enabled", "false");
+		conf.set("spark.sql.warehouse.dir", workingDir.toString());
+		conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString());
+
+		spark = SparkSession
+			.builder()
+			.appName(ProduceTest.class.getSimpleName())
+			.config(conf)
+			.getOrCreate();
+	}
+
+	@AfterAll
+	public static void afterAll() throws IOException {
+		FileUtils.deleteDirectory(workingDir.toFile());
+		spark.stop();
+	}
+
+	@Test
+	void produceTest() throws Exception {
+
+		final String bipPath = getClass()
+			.getResource("/eu/dnetlib/dhp/actionmanager/createunresolvedentities/bip/bip.json")
+			.getPath();
+
+		PrepareBipFinder
+			.main(
+				new String[] {
+					"--isSparkSessionManaged", Boolean.FALSE.toString(),
+					"--sourcePath", bipPath,
+					"--outputPath", workingDir.toString() + "/work"
+
+				});
+		final String fosPath = getClass()
+			.getResource("/eu/dnetlib/dhp/actionmanager/createunresolvedentities/fos/fos.json")
+			.getPath();
+
+		PrepareFOSSparkJob
+			.main(
+				new String[] {
+					"--isSparkSessionManaged", Boolean.FALSE.toString(),
+					"--sourcePath", fosPath,
+					"-outputPath", workingDir.toString() + "/work"
+				});
+
+		SparkSaveUnresolved.main(new String[] {
+			"--isSparkSessionManaged", Boolean.FALSE.toString(),
+			"--sourcePath", workingDir.toString() + "/work",
+
+			"-outputPath", workingDir.toString() + "/unresolved"
+
+		});
+
+		final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
+
+		JavaRDD<Result> tmp = sc
+			.textFile(workingDir.toString() + "/unresolved")
+			.map(item -> OBJECT_MAPPER.readValue(item, Result.class));
+
+		Assertions.assertEquals(135, tmp.count());
+
+		Assertions.assertEquals(1, tmp.filter(row -> row.getId().equals("unresolved::10.3390/s18072310::doi")).count());
+
+		Assertions
+			.assertEquals(
+				3, tmp
+					.filter(row -> row.getId().equals("unresolved::10.3390/s18072310::doi"))
+					.collect()
+					.get(0)
+					.getSubject()
+					.size());
+
+		Assertions
+			.assertEquals(
+				3, tmp
+					.filter(row -> row.getId().equals("unresolved::10.3390/s18072310::doi"))
+					.collect()
+					.get(0)
+					.getMeasures()
+					.size());
+
+		List<StructuredProperty> sbjs = tmp
+			.filter(row -> row.getId().equals("unresolved::10.3390/s18072310::doi"))
+			.flatMap(row -> row.getSubject().iterator())
+			.collect();
+
+		sbjs.forEach(sbj -> Assertions.assertEquals("FOS", sbj.getQualifier().getClassid()));
+		sbjs
+			.forEach(
+				sbj -> Assertions
+					.assertEquals(
+						"Fields of Science and Technology classification", sbj.getQualifier().getClassname()));
+		sbjs
+			.forEach(
+				sbj -> Assertions
+					.assertEquals(ModelConstants.DNET_SUBJECT_TYPOLOGIES, sbj.getQualifier().getSchemeid()));
+		sbjs
+			.forEach(
+				sbj -> Assertions
+					.assertEquals(ModelConstants.DNET_SUBJECT_TYPOLOGIES, sbj.getQualifier().getSchemename()));
+
+		sbjs.forEach(sbj -> Assertions.assertEquals(false, sbj.getDataInfo().getDeletedbyinference()));
+		sbjs.forEach(sbj -> Assertions.assertEquals(true, sbj.getDataInfo().getInferred()));
+		sbjs.forEach(sbj -> Assertions.assertEquals(false, sbj.getDataInfo().getInvisible()));
+		sbjs.forEach(sbj -> Assertions.assertEquals("", sbj.getDataInfo().getTrust()));
+		sbjs.forEach(sbj -> Assertions.assertEquals("update", sbj.getDataInfo().getInferenceprovenance()));
+		sbjs
+			.forEach(
+				sbj -> Assertions.assertEquals("subject:fos", sbj.getDataInfo().getProvenanceaction().getClassid()));
+		sbjs
+			.forEach(
+				sbj -> Assertions
+					.assertEquals("Inferred by OpenAIRE", sbj.getDataInfo().getProvenanceaction().getClassname()));
+		sbjs
+			.forEach(
+				sbj -> Assertions
+					.assertEquals(
+						ModelConstants.DNET_PROVENANCE_ACTIONS, sbj.getDataInfo().getProvenanceaction().getSchemeid()));
+		sbjs
+			.forEach(
+				sbj -> Assertions
+					.assertEquals(
+						ModelConstants.DNET_PROVENANCE_ACTIONS,
+						sbj.getDataInfo().getProvenanceaction().getSchemename()));
+
+		sbjs.stream().anyMatch(sbj -> sbj.getValue().equals("engineering and technology"));
+		sbjs.stream().anyMatch(sbj -> sbj.getValue().equals("nano-technology"));
+		sbjs.stream().anyMatch(sbj -> sbj.getValue().equals("nanoscience & nanotechnology"));
+
+		List<Measure> measures = tmp
+			.filter(row -> row.getId().equals("unresolved::10.3390/s18072310::doi"))
+			.flatMap(row -> row.getMeasures().iterator())
+			.collect();
+		Assertions
+			.assertEquals(
+				"7.5597134689e-09", measures
+					.stream()
+					.filter(mes -> mes.getId().equals("influence"))
+					.collect(Collectors.toList())
+					.get(0)
+					.getUnit()
+					.get(0)
+					.getValue());
+
+		Assertions
+			.assertEquals(
+				"4.903880192", measures
+					.stream()
+					.filter(mes -> mes.getId().equals("popularity_alt"))
+					.collect(Collectors.toList())
+					.get(0)
+					.getUnit()
+					.get(0)
+					.getValue());
+
+		Assertions
+			.assertEquals(
+				"1.17977512835e-08", measures
+					.stream()
+					.filter(mes -> mes.getId().equals("popularity"))
+					.collect(Collectors.toList())
+					.get(0)
+					.getUnit()
+					.get(0)
+					.getValue());
+
+		Assertions
+			.assertEquals(
+				49, tmp
+					.filter(row -> !row.getId().equals("unresolved::10.3390/s18072310::doi"))
+					.filter(row -> row.getSubject() != null)
+					.count());
+
+		Assertions
+			.assertEquals(
+				85,
+				tmp
+					.filter(row -> !row.getId().equals("unresolved::10.3390/s18072310::doi"))
+					.filter(r -> r.getMeasures() != null)
+					.count());
+
+	}
+
+}

dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/opencitations/CreateOpenCitationsASTest.java

@@ -0,0 +1,335 @@
+
+package eu.dnetlib.dhp.actionmanager.opencitations;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+import java.io.IOException;
+import java.nio.file.Files;
+import java.nio.file.Path;
+
+import org.apache.commons.io.FileUtils;
+import org.apache.hadoop.io.Text;
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoders;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
+import org.junit.jupiter.api.AfterAll;
+import org.junit.jupiter.api.Assertions;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Test;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import eu.dnetlib.dhp.schema.action.AtomicAction;
+import eu.dnetlib.dhp.schema.common.ModelConstants;
+import eu.dnetlib.dhp.schema.oaf.Publication;
+import eu.dnetlib.dhp.schema.oaf.Relation;
+import eu.dnetlib.dhp.schema.oaf.utils.CleaningFunctions;
+import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory;
+
+public class CreateOpenCitationsASTest {
+
+	private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
+
+	private static SparkSession spark;
+
+	private static Path workingDir;
+	private static final Logger log = LoggerFactory
+		.getLogger(CreateOpenCitationsASTest.class);
+
+	@BeforeAll
+	public static void beforeAll() throws IOException {
+		workingDir = Files
+			.createTempDirectory(CreateOpenCitationsASTest.class.getSimpleName());
+		log.info("using work dir {}", workingDir);
+
+		SparkConf conf = new SparkConf();
+		conf.setAppName(CreateOpenCitationsASTest.class.getSimpleName());
+
+		conf.setMaster("local[*]");
+		conf.set("spark.driver.host", "localhost");
+		conf.set("hive.metastore.local", "true");
+		conf.set("spark.ui.enabled", "false");
+		conf.set("spark.sql.warehouse.dir", workingDir.toString());
+		conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString());
+
+		spark = SparkSession
+			.builder()
+			.appName(CreateOpenCitationsASTest.class.getSimpleName())
+			.config(conf)
+			.getOrCreate();
+	}
+
+	@AfterAll
+	public static void afterAll() throws IOException {
+		FileUtils.deleteDirectory(workingDir.toFile());
+		spark.stop();
+	}
+
+	@Test
+	void testNumberofRelations() throws Exception {
+
+		String inputPath = getClass()
+			.getResource(
+				"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
+			.getPath();
+
+		CreateActionSetSparkJob
+			.main(
+				new String[] {
+					"-isSparkSessionManaged",
+					Boolean.FALSE.toString(),
+					"-shouldDuplicateRels",
+					Boolean.TRUE.toString(),
+					"-inputPath",
+					inputPath,
+					"-outputPath",
+					workingDir.toString() + "/actionSet"
+				});
+
+		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
+
+		JavaRDD<Relation> tmp = sc
+			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
+			.map(aa -> ((Relation) aa.getPayload()));
+
+		assertEquals(60, tmp.count());
+
+		// tmp.foreach(r -> System.out.println(OBJECT_MAPPER.writeValueAsString(r)));
+
+	}
+
+	@Test
+	void testNumberofRelations2() throws Exception {
+
+		String inputPath = getClass()
+			.getResource(
+				"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
+			.getPath();
+
+		CreateActionSetSparkJob
+			.main(
+				new String[] {
+					"-isSparkSessionManaged",
+					Boolean.FALSE.toString(),
+					"-inputPath",
+					inputPath,
+					"-outputPath",
+					workingDir.toString() + "/actionSet"
+				});
+
+		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
+
+		JavaRDD<Relation> tmp = sc
+			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
+			.map(aa -> ((Relation) aa.getPayload()));
+
+		assertEquals(44, tmp.count());
+
+		// tmp.foreach(r -> System.out.println(OBJECT_MAPPER.writeValueAsString(r)));
+
+	}
+
+	@Test
+	void testRelationsCollectedFrom() throws Exception {
+
+		String inputPath = getClass()
+			.getResource(
+				"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
+			.getPath();
+
+		CreateActionSetSparkJob
+			.main(
+				new String[] {
+					"-isSparkSessionManaged",
+					Boolean.FALSE.toString(),
+					"-inputPath",
+					inputPath,
+					"-outputPath",
+					workingDir.toString() + "/actionSet"
+				});
+
+		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
+
+		JavaRDD<Relation> tmp = sc
+			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
+			.map(aa -> ((Relation) aa.getPayload()));
+
+		tmp.foreach(r -> {
+			assertEquals(ModelConstants.OPENOCITATIONS_NAME, r.getCollectedfrom().get(0).getValue());
+			assertEquals(ModelConstants.OPENOCITATIONS_ID, r.getCollectedfrom().get(0).getKey());
+		});
+
+	}
+
+	@Test
+	void testRelationsDataInfo() throws Exception {
+
+		String inputPath = getClass()
+			.getResource(
+				"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
+			.getPath();
+
+		CreateActionSetSparkJob
+			.main(
+				new String[] {
+					"-isSparkSessionManaged",
+					Boolean.FALSE.toString(),
+					"-inputPath",
+					inputPath,
+					"-outputPath",
+					workingDir.toString() + "/actionSet"
+				});
+
+		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
+
+		JavaRDD<Relation> tmp = sc
+			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
+			.map(aa -> ((Relation) aa.getPayload()));
+
+		tmp.foreach(r -> {
+			assertEquals(false, r.getDataInfo().getInferred());
+			assertEquals(false, r.getDataInfo().getDeletedbyinference());
+			assertEquals("0.91", r.getDataInfo().getTrust());
+			assertEquals(
+				CreateActionSetSparkJob.OPENCITATIONS_CLASSID, r.getDataInfo().getProvenanceaction().getClassid());
+			assertEquals(
+				CreateActionSetSparkJob.OPENCITATIONS_CLASSNAME, r.getDataInfo().getProvenanceaction().getClassname());
+			assertEquals(ModelConstants.DNET_PROVENANCE_ACTIONS, r.getDataInfo().getProvenanceaction().getSchemeid());
+			assertEquals(ModelConstants.DNET_PROVENANCE_ACTIONS, r.getDataInfo().getProvenanceaction().getSchemename());
+		});
+
+	}
+
+	@Test
+	void testRelationsSemantics() throws Exception {
+
+		String inputPath = getClass()
+			.getResource(
+				"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
+			.getPath();
+
+		CreateActionSetSparkJob
+			.main(
+				new String[] {
+					"-isSparkSessionManaged",
+					Boolean.FALSE.toString(),
+					"-inputPath",
+					inputPath,
+					"-outputPath",
+					workingDir.toString() + "/actionSet"
+				});
+
+		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
+
+		JavaRDD<Relation> tmp = sc
+			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
+			.map(aa -> ((Relation) aa.getPayload()));
+
+		tmp.foreach(r -> {
+			assertEquals("citation", r.getSubRelType());
+			assertEquals("resultResult", r.getRelType());
+		});
+		assertEquals(22, tmp.filter(r -> r.getRelClass().equals("Cites")).count());
+		assertEquals(22, tmp.filter(r -> r.getRelClass().equals("IsCitedBy")).count());
+
+	}
+
+	@Test
+	void testRelationsSourceTargetPrefix() throws Exception {
+
+		String inputPath = getClass()
+			.getResource(
+				"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
+			.getPath();
+
+		CreateActionSetSparkJob
+			.main(
+				new String[] {
+					"-isSparkSessionManaged",
+					Boolean.FALSE.toString(),
+					"-inputPath",
+					inputPath,
+					"-outputPath",
+					workingDir.toString() + "/actionSet"
+				});
+
+		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
+
+		JavaRDD<Relation> tmp = sc
+			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
+			.map(aa -> ((Relation) aa.getPayload()));
+
+		tmp.foreach(r -> {
+			assertEquals("50|doi_________::", r.getSource().substring(0, 17));
+			assertEquals("50|doi_________::", r.getTarget().substring(0, 17));
+		});
+
+	}
+
+	@Test
+	void testRelationsSourceTargetCouple() throws Exception {
+		final String doi1 = "50|doi_________::"
+			+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1007/s10854-015-3684-x"));
+		final String doi2 = "50|doi_________::"
+			+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1111/j.1551-2916.2008.02408.x"));
+		final String doi3 = "50|doi_________::"
+			+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1007/s10854-014-2114-9"));
+		final String doi4 = "50|doi_________::"
+			+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1016/j.ceramint.2013.09.069"));
+		final String doi5 = "50|doi_________::"
+			+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1007/s10854-009-9913-4"));
+		final String doi6 = "50|doi_________::"
+			+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1016/0038-1098(72)90370-5"));
+
+		String inputPath = getClass()
+			.getResource(
+				"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
+			.getPath();
+
+		CreateActionSetSparkJob
+			.main(
+				new String[] {
+					"-isSparkSessionManaged",
+					Boolean.FALSE.toString(),
+					"-inputPath",
+					inputPath,
+					"-outputPath",
+					workingDir.toString() + "/actionSet"
+				});
+
+		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
+
+		JavaRDD<Relation> tmp = sc
+			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
+			.map(aa -> ((Relation) aa.getPayload()));
+
+		JavaRDD<Relation> check = tmp.filter(r -> r.getSource().equals(doi1) || r.getTarget().equals(doi1));
+
+		assertEquals(10, check.count());
+
+		check.foreach(r -> {
+			if (r.getSource().equals(doi2) || r.getSource().equals(doi3) || r.getSource().equals(doi4) ||
+				r.getSource().equals(doi5) || r.getSource().equals(doi6)) {
+				assertEquals(ModelConstants.IS_CITED_BY, r.getRelClass());
+				assertEquals(doi1, r.getTarget());
+			}
+		});
+
+		assertEquals(5, check.filter(r -> r.getSource().equals(doi1)).count());
+		check.filter(r -> r.getSource().equals(doi1)).foreach(r -> assertEquals(ModelConstants.CITES, r.getRelClass()));
+
+	}
+}

dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/datacite/DataciteToOAFTest.scala

@@ -1,8 +1,7 @@
-package eu.dnetlib.dhp.actionmanager.datacite
+package eu.dnetlib.dhp.datacite
 
 
-import com.fasterxml.jackson.databind.ObjectMapper
-import com.fasterxml.jackson.databind.SerializationFeature
+import com.fasterxml.jackson.databind.{ObjectMapper, SerializationFeature}
 import eu.dnetlib.dhp.aggregation.AbstractVocabularyTest
 import eu.dnetlib.dhp.schema.oaf.Oaf
 import org.junit.jupiter.api.extension.ExtendWith

dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/createunresolvedentities/bip/bip.json

@@ -0,0 +1,86 @@
+{"10.3390/s18072310": [{"id": "influence", "unit": [{"value": "7.5597134689e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "4.903880192", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "1.17977512835e-08", "key": "score"}]}]}
+{"10.0000/096020199389707": [{"id": "influence", "unit": [{"value": "6.34596412687e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.641151896994", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "2.33375102921e-09", "key": "score"}]}]}
+{"10.00000/jpmc.2017.106": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "5.39172290649e-09", "key": "score"}]}]}
+{"10.0000/9781845416881": [{"id": "influence", "unit": [{"value": "5.96492048955e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "1.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "1.12641925838e-08", "key": "score"}]}]}
+{"10.0000/anziamj.v0i0.266": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.76260934675e-10", "key": "score"}]}]}
+{"10.0000/anziamj.v48i0.79": [{"id": "influence", "unit": [{"value": "6.93311506443e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.002176782336", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "1.7668105708e-09", "key": "score"}]}]}
+{"10.0000/anziamj.v50i0.1472": [{"id": "influence", "unit": [{"value": "6.26777280882e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.406656", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.39745193285e-09", "key": "score"}]}]}
+{"10.0000/cja5553": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/czastest.16": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/czastest.17": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.47956715615e-09", "key": "score"}]}]}
+{"10.0000/czastest.18": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.47956715615e-09", "key": "score"}]}]}
+{"10.0000/czastest.20": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/czastest.21": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.47956715615e-09", "key": "score"}]}]}
+{"10.0000/czastest.28": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.47956715615e-09", "key": "score"}]}]}
+{"10.0000/czastest.60": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
+{"10.0000/czt.2019.1.2.15": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v4i02.36": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v4i02.37": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v4i02.38": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v5i01.32": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v6i01.24": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v6i01.27": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v6i02.41": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v6i02.44": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v7i01.40": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v7i01.42": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v7i01.47": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v7i01.51": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v7i01.52": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v7i02.86": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v7i02.88": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v7i02.91": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v8i01.129": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v8i01.180": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "5.39172290649e-09", "key": "score"}]}]}
+{"10.0000/geoekonomi.v8i01.87": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
+{"10.0000/hbv2004w010": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hbv2101w001": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "9.88840807598e-09", "key": "score"}]}]}
+{"10.0000/hbv2101w002": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "9.88840807598e-09", "key": "score"}]}]}
+{"10.0000/hbv2101w003": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "9.88840807598e-09", "key": "score"}]}]}
+{"10.0000/hbv2101w004": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "9.88840807598e-09", "key": "score"}]}]}
+{"10.0000/hbv2101w005": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "9.88840807598e-09", "key": "score"}]}]}
+{"10.0000/hbv2101w006": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "9.88840807598e-09", "key": "score"}]}]}
+{"10.0000/hbv2101w007": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "9.88840807598e-09", "key": "score"}]}]}
+{"10.0000/hbv2102w001": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "9.88840807598e-09", "key": "score"}]}]}
+{"10.0000/hbv2102w010": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "9.88840807598e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v1i1.13207": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v1i1.13208": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "5.39172290649e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v1i1.13209": [{"id": "influence", "unit": [{"value": "6.32078461509e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "1.6", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.3168486939e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v1i1.13210": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v1i1.13211": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "5.39172290649e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v1i1.13212": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "5.39172290649e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v1i2.13231": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i2.28782": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i2.28783": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i2.28784": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i2.28786": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i2.28787": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i2.28788": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i3.28234": [{"id": "influence", "unit": [{"value": "6.40470414877e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.6", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.89465099068e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i3.28236": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i3.28238": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i3.28239": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i3.28242": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v2i3.28243": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "6.26204125721e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v3i4.38186": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v3i4.38187": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v3i4.38190": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v3i4.38207": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v3i4.38209": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v3i5.41163": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v3i5.41166": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v3i5.41167": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v3i5.41168": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v3i5.41229": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i6.36360": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i6.40796": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i6.41153": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i6.42511": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i6.42555": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i6.42752": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i6.42768": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i6.42795": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i7.41295": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i7.42830": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i7.42861": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
+{"10.0000/hoplos.v4i7.43096": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}

dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/createunresolvedentities/fos/fos.json

@@ -0,0 +1,38 @@
+{"doi":"10.3390/s18072310","level1":"engineering and technology","level2":"nano-technology","level3":"nanoscience & nanotechnology"}
+{"doi":"10.1111/1365-2656.12831\u000210.17863/cam.24369","level1":"social sciences","level2":"psychology and cognitive sciences","level3":"NULL"}
+{"doi":"10.3929/ethz-b-000187584\u000210.1002/chem.201701644","level1":"natural sciences","level2":"NULL","level3":"NULL"}
+{"doi":"10.1080/01913123.2017.1367361","level1":"medical and health sciences","level2":"clinical medicine","level3":"oncology & carcinogenesis"}
+{"doi":"10.1051/e3sconf/20199207011","level1":"natural sciences","level2":"earth and related environmental sciences","level3":"environmental sciences"}
+{"doi":"10.1038/onc.2015.333","level1":"medical and health sciences","level2":"clinical medicine","level3":"oncology & carcinogenesis"}
+{"doi":"10.1093/mnras/staa256","level1":"natural sciences","level2":"physical sciences","level3":"NULL"}
+{"doi":"10.1016/j.jclepro.2018.07.166","level1":"engineering and technology","level2":"other engineering and technologies","level3":"building & construction"}
+{"doi":"10.1103/physrevlett.125.037403","level1":"natural sciences","level2":"physical sciences","level3":"nuclear & particles physics"}
+{"doi":"10.1080/03602532.2017.1316285","level1":"natural sciences","level2":"NULL","level3":"NULL"}
+{"doi":"10.1001/jamanetworkopen.2019.1868","level1":"medical and health sciences","level2":"other medical science","level3":"health policy & services"}
+{"doi":"10.1128/mra.00874-18","level1":"natural sciences","level2":"biological sciences","level3":"plant biology & botany"}
+{"doi":"10.1016/j.nancom.2018.03.001","level1":"engineering and technology","level2":"NULL","level3":"NULL"}
+{"doi":"10.1112/topo.12174","level1":"natural sciences","level2":"NULL","level3":"NULL"}
+{"doi":"10.12688/wellcomeopenres.15846.1","level1":"medical and health sciences","level2":"health sciences","level3":"NULL"}
+{"doi":"10.21468/scipostphys.3.1.001","level1":"natural sciences","level2":"physical sciences","level3":"NULL"}
+{"doi":"10.1088/1741-4326/ab6c77","level1":"natural sciences","level2":"physical sciences","level3":"nuclear & particles physics"}
+{"doi":"10.1109/tpwrs.2019.2944747","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"electrical & electronic engineering"}
+{"doi":"10.1016/j.expthermflusci.2019.109994\u000210.17863/cam.46212","level1":"engineering and technology","level2":"mechanical engineering","level3":"mechanical engineering & transports"}
+{"doi":"10.1109/tc.2018.2860012","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"computer hardware & architecture"}
+{"doi":"10.1002/mma.6622","level1":"natural sciences","level2":"mathematics","level3":"numerical & computational mathematics"}
+{"doi":"10.1051/radiopro/2020020","level1":"natural sciences","level2":"chemical sciences","level3":"NULL"}
+{"doi":"10.1007/s12268-019-1003-4","level1":"medical and health sciences","level2":"basic medicine","level3":"NULL"}
+{"doi":"10.3390/cancers12010236","level1":"medical and health sciences","level2":"health sciences","level3":"biochemistry & molecular biology"}
+{"doi":"10.6084/m9.figshare.9912614\u000210.6084/m9.figshare.9912614.v1\u000210.1080/00268976.2019.1665199","level1":"natural sciences","level2":"chemical sciences","level3":"physical chemistry"}
+{"doi":"10.1175/jpo-d-17-0239.1","level1":"natural sciences","level2":"biological sciences","level3":"marine biology & hydrobiology"}
+{"doi":"10.1007/s13218-020-00674-7","level1":"engineering and technology","level2":"industrial biotechnology","level3":"industrial engineering & automation"}
+{"doi":"10.1016/j.psyneuen.2016.02.003\u000210.1016/j.psyneuen.2016.02.00310.7892/boris.78886\u000210.7892/boris.78886","level1":"medical and health sciences","level2":"basic medicine","level3":"NULL"}
+{"doi":"10.1109/ted.2018.2813542","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"electrical & electronic engineering"}
+{"doi":"10.3989/scimar.04739.25a","level1":"natural sciences","level2":"biological sciences","level3":"NULL"}
+{"doi":"10.3390/su12187503","level1":"natural sciences","level2":"earth and related environmental sciences","level3":"NULL"}
+{"doi":"10.1016/j.ccell.2018.08.017","level1":"medical and health sciences","level2":"basic medicine","level3":"biochemistry & molecular biology"}
+{"doi":"10.1103/physrevresearch.2.023322","level1":"natural sciences","level2":"physical sciences","level3":"nuclear & particles physics"}
+{"doi":"10.1039/c8cp03234c","level1":"natural sciences","level2":"NULL","level3":"NULL"}
+{"doi":"10.5281/zenodo.3696557\u000210.5281/zenodo.3696556\u000210.1109/jsac.2016.2545384","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"networking & telecommunications"}
+{"doi":"10.1038/ng.3667\u000210.1038/ng.3667.\u000210.17615/tct6-4m26\u000210.17863/cam.15649","level1":"medical and health sciences","level2":"health sciences","level3":"genetics & heredity"}
+{"doi":"10.1016/j.jclepro.2019.119065","level1":"engineering and technology","level2":"other engineering and technologies","level3":"building & construction"}
+{"doi":"10.1111/pce.13392","level1":"agricultural and veterinary sciences","level2":"agriculture, forestry, and fisheries","level3":"agronomy & agriculture"}

dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/createunresolvedentities/fos/h2020_fos_sbs.csv

@@ -0,0 +1,38 @@
+dedup_wf_001::ddcc7a56fa13e49bcc59c6bdd19ad26c	10.3390/s18072310	engineering and technology	nano-technology	nanoscience & nanotechnology
+dedup_wf_001::b76062d56e28224eac56111a4e1e5ecf	10.1111/1365-2656.1283110.17863/cam.24369	social sciences	psychology and cognitive sciences	NULL
+dedup_wf_001::bb752acb8f403a25fa7851a302f7b7ac	10.3929/ethz-b-00018758410.1002/chem.201701644	natural sciences	NULL	NULL
+dedup_wf_001::2f1435a9201ecf5cbbcb12c9b2d971cd	10.1080/01913123.2017.1367361	medical and health sciences	clinical medicine	oncology & carcinogenesis
+dedup_wf_001::fc9e47ec16c67b101724320d4b030514	10.1051/e3sconf/20199207011	natural sciences	earth and related environmental sciences	environmental sciences
+dedup_wf_001::caa1e5b4de387cb31751552f4f0f5d72	10.1038/onc.2015.333	medical and health sciences	clinical medicine	oncology & carcinogenesis
+dedup_wf_001::c2a98df5637d69bf0524eaf40fe6bf11	10.1093/mnras/staa256	natural sciences	physical sciences	NULL
+dedup_wf_001::c221262bdc77cbfd59859a402f0e3991	10.1016/j.jclepro.2018.07.166	engineering and technology	other engineering and technologies	building & construction
+doiboost____::d56d9dc21f317b3e009d5b6c8ea87212	10.1103/physrevlett.125.037403	natural sciences	physical sciences	nuclear & particles physics
+dedup_wf_001::8a7269c8ee6470b2fb4fd384bc389e08	10.1080/03602532.2017.1316285	natural sciences	NULL	NULL
+dedup_wf_001::28342ebbc19833e4e1f4a2b23cf5ee20	10.1001/jamanetworkopen.2019.1868	medical and health sciences	other medical science	health policy & services
+dedup_wf_001::c1e1daf2b55dd9ec8e1c7c7458bbc7bc	10.1128/mra.00874-18	natural sciences	biological sciences	plant biology & botany
+dedup_wf_001::a2ef4a2720c71907180750e5871298ef	10.1016/j.nancom.2018.03.001	engineering and technology	NULL	NULL
+dedup_wf_001::676f46a31519e83a89efcb1c626286fb	10.1112/topo.12174	natural sciences	NULL	NULL
+dedup_wf_001::6f2761642f1e39313388e2c4060657dd	10.12688/wellcomeopenres.15846.1	medical and health sciences	health sciences	NULL
+dedup_wf_001::e414c1dec599521a9635a60de0f6755b	10.21468/scipostphys.3.1.001	natural sciences	physical sciences	NULL
+dedup_wf_001::f3395fe0f330164ea424dc61c86c9a3d	10.1088/1741-4326/ab6c77	natural sciences	physical sciences	nuclear & particles physics
+dedup_wf_001::a4f32a97a783117012f1de11797e73f2	10.1109/tpwrs.2019.2944747	engineering and technology	electrical engineering, electronic engineering, information engineering	electrical & electronic engineering
+dedup_wf_001::313ae1cd083ae1696d12dd1909f97df8	10.1016/j.expthermflusci.2019.10999410.17863/cam.46212	engineering and technology	mechanical engineering	mechanical engineering & transports
+dedup_wf_001::2a300a7d3ca7347791ebcef986bc0682	10.1109/tc.2018.2860012	engineering and technology	electrical engineering, electronic engineering, information engineering	computer hardware & architecture
+doiboost____::5b79bd7bd9f87361b4a4abc3cbb2df75	10.1002/mma.6622	natural sciences	mathematics	numerical & computational mathematics
+dedup_wf_001::6a3f61f217a2519fbaddea1094e3bfc2	10.1051/radiopro/2020020	natural sciences	chemical sciences	NULL
+dedup_wf_001::a3f0430309a639f4234a0e57b10f2dee	10.1007/s12268-019-1003-4	medical and health sciences	basic medicine	NULL
+dedup_wf_001::b6b8a3a1cccbee459cf3343485efdb12	10.3390/cancers12010236	medical and health sciences	health sciences	biochemistry & molecular biology
+dedup_wf_001::dd06ee7974730e7b09a4f03c83b3f9bd	10.6084/m9.figshare.991261410.6084/m9.figshare.9912614.v110.1080/00268976.2019.1665199	natural sciences	chemical sciences	physical chemistry
+dedup_wf_001::027c78bef6f972b5e26dfea55d30fbe3	10.1175/jpo-d-17-0239.1	natural sciences	biological sciences	marine biology & hydrobiology
+dedup_wf_001::43edc179aa9e1fbaf582c5203b18b519	10.1007/s13218-020-00674-7	engineering and technology	industrial biotechnology	industrial engineering & automation
+dedup_wf_001::e7770e11cd6eb514bb52c07b5a8a80f0	10.1016/j.psyneuen.2016.02.00310.1016/j.psyneuen.2016.02.00310.7892/boris.7888610.7892/boris.78886	medical and health sciences	basic medicine	NULL
+dedup_wf_001::80bc15d69bdc589149631f3439dde5aa	10.1109/ted.2018.2813542	engineering and technology	electrical engineering, electronic engineering, information engineering	electrical & electronic engineering
+dedup_wf_001::42c1cfa33e7872944b920cff90f4d99e	10.3989/scimar.04739.25a	natural sciences	biological sciences	NULL
+dedup_wf_001::9bacdbbaa9da3658b7243d5de8e3ce14	10.3390/su12187503	natural sciences	earth and related environmental sciences	NULL
+dedup_wf_001::59e43d3527dcfecb6097fbd5740c8950	10.1016/j.ccell.2018.08.017	medical and health sciences	basic medicine	biochemistry & molecular biology
+doiboost____::e024d1b738df3b24bc58fa0228542571	10.1103/physrevresearch.2.023322	natural sciences	physical sciences	nuclear & particles physics
+dedup_wf_001::66e9a3237fa8178886d26d3c2d5b9e66	10.1039/c8cp03234c	natural sciences	NULL	NULL
+dedup_wf_001::83737ab4205bae751571bb3b166efa18	10.5281/zenodo.369655710.5281/zenodo.369655610.1109/jsac.2016.2545384	engineering and technology	electrical engineering, electronic engineering, information engineering	networking & telecommunications
+dedup_wf_001::e3f892db413a689e572dd256acad55fe	10.1038/ng.366710.1038/ng.3667.10.17615/tct6-4m2610.17863/cam.15649	medical and health sciences	health sciences	genetics & heredity
+dedup_wf_001::14ba594e8fd081847bc3f50f56335003	10.1016/j.jclepro.2019.119065	engineering and technology	other engineering and technologies	building & construction
+dedup_wf_001::08ac7b33a41bcea2d055ecd8585d632e	10.1111/pce.13392	agricultural and veterinary sciences	agriculture, forestry, and fisheries	agronomy & agriculture

dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles/input1

@@ -0,0 +1,8 @@
+oci,citing,cited,creation,timespan,journal_sc,author_sc
+02001000007362801000805046300010563030608046333-0200101010136193701050501630209010637020000083700020400083733,10.1007/s10854-015-3684-x,10.1111/j.1551-2916.2008.02408.x,2015-09-01,P7Y2M,no,no
+02001000007362801000805046300010563030608046333-02001000007362801000805046300010463020101046309,10.1007/s10854-015-3684-x,10.1007/s10854-014-2114-9,2015-09-01,P1Y2M4D,yes,no
+02001000007362801000805046300010563030608046333-020010001063619371214271022182329370200010337000937000609,10.1007/s10854-015-3684-x,10.1016/j.ceramint.2013.09.069,2015-09-01,P1Y6M,no,no
+02001000007362801000805046300010563030608046333-02001000007362801000805046300000963090901036304,10.1007/s10854-015-3684-x,10.1007/s10854-009-9913-4,2015-09-01,P6Y3M10D,yes,no
+02001000007362801000805046300010563030608046333-02001000106360000030863010009085807025909000307006305,10.1007/s10854-015-3684-x,10.1016/0038-1098(72)90370-5,2015-09-01,P43Y8M,no,no
+02001000007362801000805046300010563030608056309-02001000106361937281010370200010437000937000308,10.1007/s10854-015-3685-9,10.1016/j.saa.2014.09.038,2015-09-03,P0Y7M,no,no
+02001000007362801000805046300010563030608056309-0200100010636193722102912171027370200010537000437000106,10.1007/s10854-015-3685-9,10.1016/j.matchar.2015.04.016,2015-09-03,P0Y2M,no,no

dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles/input2

@@ -0,0 +1,8 @@
+oci,citing,cited,creation,timespan,journal_sc,author_sc
+02001000308362804010509076300010963000003086301-0200100020936020001003227000009010004,10.1038/s41597-019-0038-1,10.1029/2010wr009104,2019-04-15,P8Y1M,no,no
+02001000308362804010509076300010963000003086301-0200100010636280103060463080105025800015900000006006303,10.1038/s41597-019-0038-1,10.1016/s1364-8152(01)00060-3,2019-04-15,P17Y3M,no,no
+02001000308362804010509076300010963000003086301-02001000007362800000407076300010063000401066333,10.1038/s41597-019-0038-1,10.1007/s00477-010-0416-x,2019-04-15,P8Y9M6D,no,no
+02001000308362804010509076300010963000003086301-02001000007362800000700046300010363000905016308,10.1038/s41597-019-0038-1,10.1007/s00704-013-0951-8,2019-04-15,P5Y9M23D,no,no
+02001000308362804010509076300010963000003086301-02001000002361924123705070707,10.1038/s41597-019-0038-1,10.1002/joc.5777,2019-04-15,P0Y8M1D,no,no
+02001000308362804010509076300010963000003086301-02005010904361714282863020263040504076302000108,10.1038/s41597-019-0038-1,10.5194/hess-22-4547-2018,2019-04-15,P0Y7M18D,no,no
+02001000308362804010509076300010963000003086301-02001000002361924123703050404,10.1038/s41597-019-0038-1,10.1002/joc.3544,2019-04-15,P6Y9M6D,no,no

dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles/input3

@@ -0,0 +1,9 @@
+oci,citing,cited,creation,timespan,journal_sc,author_sc
+0200100000236090708010101090307000202023727141528-020050302063600040000010307,10.1002/9781119370222.refs,10.5326/0400137,2020-06-22,P16Y3M,no,no
+0200100000236090708010101090307000202023727141528-0200101010136193701050302630905003337020000073700000301093733,10.1002/9781119370222.refs,10.1111/j.1532-950x.2007.00319.x,2020-06-22,P12Y8M,no,no
+0200100000236090708010101090307000202023727141528-0200101010136312830370102030509,10.1002/9781119370222.refs,10.1111/vsu.12359,2020-06-22,P4Y10M29D,no,no
+0200100000236090708010101090307000202023727141528-020050302063600030900020904,10.1002/9781119370222.refs,10.5326/0390294,2020-06-22,P17Y1M,no,no
+0200100000236090708010101090307000202023727141528-020050302063600040200030701,10.1002/9781119370222.refs,10.5326/0420371,2020-06-22,P13Y9M,no,no
+0200100000236090708010101090307000202023727141528-0200101010136193701050302630905003337020001033701020000003733,10.1002/9781119370222.refs,10.1111/j.1532-950x.2013.12000.x,2020-06-22,P7Y2M,no,no
+0200100000236090708010101090307000202023727141528-020010008003600000408000106093702000006370306070200,10.1002/9781119370222.refs,10.1080/00480169.2006.36720,2020-06-22,P13Y6M,no,no
+0200100000236090708010101090307000202023727141528-0200101010136193701070501630008010337020000063700000003033733,10.1002/9781119370222.refs,10.1111/j.1751-0813.2006.00033.x,2020-06-22,P13Y8M,no,no

dhp-workflows/dhp-dedup-openaire/src/main/resources/eu/dnetlib/dhp/oa/dedup/consistency/oozie_app/workflow.xml

@@ -89,7 +89,7 @@
                 --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
                 --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
-                --conf spark.sql.shuffle.partitions=7680
+                --conf spark.sql.shuffle.partitions=15000
             </spark-opts>
             <arg>--graphBasePath</arg><arg>${graphBasePath}</arg>
             <arg>--o</arg><arg>${graphOutputPath}</arg>
@@ -114,7 +114,7 @@
                 --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
                 --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
-                --conf spark.sql.shuffle.partitions=7680
+                --conf spark.sql.shuffle.partitions=15000
             </spark-opts>
             <arg>--graphInputPath</arg><arg>${graphBasePath}</arg>
             <arg>--outputPath</arg><arg>${workingPath}/grouped_entities</arg>

dhp-workflows/dhp-doiboost/src/main/java/eu/dnetlib/doiboost/crossref/Crossref2Oaf.scala

@@ -70,7 +70,7 @@ case object Crossref2Oaf {
     "reference-book" -> "0002 Book",
     "monograph" -> "0002 Book",
     "journal-article" -> "0001 Article",
-    "dissertation" -> "0006 Doctoral thesis",
+    "dissertation" -> "0044 Thesis",
     "other" -> "0038 Other literature type",
     "peer-review" -> "0015 Review",
     "proceedings" -> "0004 Conference object",
@@ -206,11 +206,16 @@ case object Crossref2Oaf {
     else {
       instance.setDateofacceptance(asField(createdDate.getValue))
     }
-    val s: String = (json \ "URL").extract[String]
-    val links: List[String] = ((for {JString(url) <- json \ "link" \ "URL"} yield url) ::: List(s)).filter(p => p != null).distinct
-    if (links.nonEmpty) {
-      instance.setUrl(links.asJava)
-    }
+    val s: List[String] = List("https://doi.org/" + doi)
+//    val links: List[String] = ((for {JString(url) <- json \ "link" \ "URL"} yield url) ::: List(s)).filter(p => p != null && p.toLowerCase().contains(doi.toLowerCase())).distinct
+//    if (links.nonEmpty) {
+//      instance.setUrl(links.asJava)
+//    }
+    if(s.nonEmpty)
+      {
+        instance.setUrl(s.asJava)
+      }
+
     result.setInstance(List(instance).asJava)
 
     //IMPORTANT

dhp-workflows/dhp-doiboost/src/main/java/eu/dnetlib/doiboost/mag/SparkProcessMAG.scala

@@ -111,26 +111,9 @@ object SparkProcessMAG {
       .map(item => ConversionUtil.updatePubsWithConferenceInfo(item))
       .write
       .mode(SaveMode.Overwrite)
-      .save(s"$workingPath/merge_step_2_conference")
-
-
-    magPubs= spark.read.load(s"$workingPath/merge_step_2_conference").as[Publication]
-      .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
-
-    val paperUrlDataset = spark.read.load(s"$sourcePath/PaperUrls").as[MagPaperUrl].groupBy("PaperId").agg(collect_list(struct("sourceUrl")).as("instances")).as[MagUrl]
-
-
-    logger.info("Phase 5) enrich publication with URL and Instances")
-    magPubs.joinWith(paperUrlDataset, col("_1").equalTo(paperUrlDataset("PaperId")), "left")
-      .map { a: ((String, Publication), MagUrl) => ConversionUtil.addInstances((a._1._2, a._2)) }
-      .write.mode(SaveMode.Overwrite)
       .save(s"$workingPath/merge_step_3")
 
 
-//    logger.info("Phase 6) Enrich Publication with description")
-//    val pa = spark.read.load(s"${parser.get("sourcePath")}/PaperAbstractsInvertedIndex").as[MagPaperAbstract]
-//    pa.map(ConversionUtil.transformPaperAbstract).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/PaperAbstract")
-
     val paperAbstract = spark.read.load((s"$workingPath/PaperAbstract")).as[MagPaperAbstract]
 
 
@@ -162,12 +145,14 @@ object SparkProcessMAG {
       .write.mode(SaveMode.Overwrite)
       .save(s"$workingPath/mag_publication")
 
+    spark.read.load(s"$workingPath/mag_publication").as[Publication]
+      .filter(p => p.getId == null)
+      .groupByKey(p => p.getId)
+      .reduceGroups((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
+      .map(_._2)
+      .write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
 
-    val s:RDD[Publication] = spark.read.load(s"$workingPath/mag_publication").as[Publication]
-      .map(p=>Tuple2(p.getId, p)).rdd.reduceByKey((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
-    .map(_._2)
 
-    spark.createDataset(s).as[Publication].write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
 
   }
 }

dhp-workflows/dhp-doiboost/src/test/java/eu/dnetlib/doiboost/crossref/CrossrefMappingTest.scala

@@ -612,4 +612,26 @@ class CrossrefMappingTest {
 
   }
 
+  @Test
+  def testMultipleURLs() :Unit = {
+    val json = Source.fromInputStream(getClass.getResourceAsStream("multiple_urls.json")).mkString
+
+
+    assertNotNull(json)
+    assertFalse(json.isEmpty);
+
+    val resultList: List[Oaf] = Crossref2Oaf.convert(json)
+
+    assertTrue(resultList.nonEmpty)
+
+
+    val item : Result = resultList.filter(p => p.isInstanceOf[Result]).head.asInstanceOf[Result]
+
+    assertEquals(1, item.getInstance().size())
+    assertEquals(1, item.getInstance().get(0).getUrl().size())
+    assertEquals("https://doi.org/10.1016/j.jas.2019.105013", item.getInstance().get(0).getUrl().get(0))
+    //println(mapper.writeValueAsString(item))
+
+  }
+
 }

dhp-workflows/dhp-doiboost/src/test/resources/eu/dnetlib/doiboost/crossref/multiple_urls.json

@@ -0,0 +1,614 @@
+
+{
+"indexed": {
+"date-parts": [
+[
+2021,
+10,
+31
+]
+],
+"date-time": "2021-10-31T15:48:01Z",
+"timestamp": 1635695281393
+},
+"reference-count": 39,
+"publisher": "Elsevier BV",
+"license": [
+{
+"start": {
+"date-parts": [
+[
+2019,
+12,
+1
+]
+],
+"date-time": "2019-12-01T00:00:00Z",
+"timestamp": 1575158400000
+},
+"content-version": "tdm",
+"delay-in-days": 0,
+"URL": "https://www.elsevier.com/tdm/userlicense/1.0/"
+},
+{
+"start": {
+"date-parts": [
+[
+2019,
+9,
+13
+]
+],
+"date-time": "2019-09-13T00:00:00Z",
+"timestamp": 1568332800000
+},
+"content-version": "vor",
+"delay-in-days": 0,
+"URL": "http://creativecommons.org/licenses/by/4.0/"
+}
+],
+"funder": [
+{
+"DOI": "10.13039/100001182",
+"name": "INSTAP",
+"doi-asserted-by": "publisher"
+},
+{
+"DOI": "10.13039/100014440",
+"name": "Ministry of Science, Innovation and Universities",
+"doi-asserted-by": "publisher",
+"award": [
+"RYC-2016-19637"
+]
+},
+{
+"DOI": "10.13039/100010661",
+"name": "European Union’s Horizon 2020",
+"doi-asserted-by": "publisher",
+"award": [
+"746446"
+]
+}
+],
+"content-domain": {
+"domain": [
+"elsevier.com",
+"sciencedirect.com"
+],
+"crossmark-restriction": true
+},
+"short-container-title": [
+"Journal of Archaeological Science"
+],
+"published-print": {
+"date-parts": [
+[
+2019,
+12
+]
+]
+},
+"DOI": "10.1016/j.jas.2019.105013",
+"type": "journal-article",
+"created": {
+"date-parts": [
+[
+2019,
+9,
+25
+]
+],
+"date-time": "2019-09-25T20:05:08Z",
+"timestamp": 1569441908000
+},
+"page": "105013",
+"update-policy": "http://dx.doi.org/10.1016/elsevier_cm_policy",
+"source": "Crossref",
+"is-referenced-by-count": 21,
+"title": [
+"A brave new world for archaeological survey: Automated machine learning-based potsherd detection using high-resolution drone imagery"
+],
+"prefix": "10.1016",
+"volume": "112",
+"author": [
+{
+"given": "H.A.",
+"family": "Orengo",
+"sequence": "first",
+"affiliation": [
+
+]
+},
+{
+"given": "A.",
+"family": "Garcia-Molsosa",
+"sequence": "additional",
+"affiliation": [
+
+]
+}
+],
+"member": "78",
+"reference": [
+{
+"key": "10.1016/j.jas.2019.105013_bib1",
+"doi-asserted-by": "crossref",
+"first-page": "85",
+"DOI": "10.1080/17538947.2016.1250829",
+"article-title": "Remote sensing heritage in a petabyte-scale: satellite data and heritage Earth Engine© applications",
+"volume": "10",
+"author": "Agapiou",
+"year": "2017",
+"journal-title": "Int. J. Digit. Earth"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib2",
+"series-title": "Extracting Meaning from Ploughsoil Assemblages",
+"first-page": "1",
+"article-title": "Extracting meaning from ploughsoil assemblages: assessments of the past, strategies for the future",
+"author": "Alcock",
+"year": "2000"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib3",
+"series-title": "Side-by-Side Survey. Comparative Regional Studies in the Mediterranean World",
+"first-page": "1",
+"article-title": "Introduction",
+"author": "Alcock",
+"year": "2004"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib4",
+"doi-asserted-by": "crossref",
+"first-page": "93",
+"DOI": "10.1111/j.1538-4632.1995.tb00338.x",
+"article-title": "Local indicators of spatial association—LISA",
+"volume": "27",
+"author": "Anselin",
+"year": "1995",
+"journal-title": "Geogr. Anal."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib5",
+"series-title": "Archaeological Survey",
+"author": "Banning",
+"year": "2002"
+},
+{
+"issue": "1/2",
+"key": "10.1016/j.jas.2019.105013_bib6",
+"doi-asserted-by": "crossref",
+"first-page": "123",
+"DOI": "10.2307/3181488",
+"article-title": "GIS, archaeological survey and landscape archaeology on the island of Kythera, Greece",
+"volume": "29",
+"author": "Bevan",
+"year": "2004",
+"journal-title": "J. Field Archaeol."
+},
+{
+"issue": "1",
+"key": "10.1016/j.jas.2019.105013_bib8",
+"doi-asserted-by": "crossref",
+"first-page": "5",
+"DOI": "10.1023/A:1010933404324",
+"article-title": "Random forests",
+"volume": "45",
+"author": "Breiman",
+"year": "2001",
+"journal-title": "Mach. Learn."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib9",
+"series-title": "Sampling in Contemporary British Archaeology",
+"author": "Cherry",
+"year": "1978"
+},
+{
+"issue": "3",
+"key": "10.1016/j.jas.2019.105013_bib10",
+"doi-asserted-by": "crossref",
+"first-page": "273",
+"DOI": "10.1016/0734-189X(84)90197-X",
+"article-title": "Segmentation of a high-resolution urban scene using texture operators",
+"volume": "25",
+"author": "Conners",
+"year": "1984",
+"journal-title": "Comput. Vis. Graph Image Process"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib11",
+"first-page": "31",
+"article-title": "Old land surfaces and modern ploughsoil: implications of recent work at Maxey, Cambridgeshire",
+"volume": "2",
+"author": "Crowther",
+"year": "1983",
+"journal-title": "Scott. Archaeol. Rev."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib12",
+"series-title": "Settlement Pattern Studies in the Americas: Fifty Years since Virú",
+"first-page": "203",
+"article-title": "Conclusions: the settlement pattern concept from an Americanist perspective",
+"author": "Fish",
+"year": "1999"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib13",
+"doi-asserted-by": "crossref",
+"first-page": "21",
+"DOI": "10.3390/geosciences9010021",
+"article-title": "Remote sensing and historical morphodynamics of alluvial plains. The 1909 indus flood and the city of Dera Gazhi Khan (province of Punjab, Pakistan)",
+"volume": "9",
+"author": "Garcia",
+"year": "2019",
+"journal-title": "Geosciences"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib14",
+"unstructured": "Georgiadis, M.; Garcia-Molsosa, A.; Orengo, H.A.; Kefalidou, E. and Kallintzi, K. In Preparation. APAX Project 2015-2018: A Preliminary Report. (Hesperia)."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib15",
+"series-title": "Geographical Information Systems and Landscape Archaeology",
+"first-page": "35",
+"article-title": "Regional survey and GIS: the boeotia project",
+"author": "Gillings",
+"year": "1999"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib16",
+"doi-asserted-by": "crossref",
+"first-page": "18",
+"DOI": "10.1016/j.rse.2017.06.031",
+"article-title": "Google Earth engine: planetary-scale geospatial analysis for everyone",
+"volume": "202",
+"author": "Gorelick",
+"year": "2017",
+"journal-title": "Remote Sens. Environ."
+},
+{
+"issue": "107",
+"key": "10.1016/j.jas.2019.105013_bib17",
+"doi-asserted-by": "crossref",
+"first-page": "177",
+"DOI": "10.1111/j.0031-868X.2004.00278.x",
+"article-title": "Photogrammetric reconstruction of the great buddha of Bamiyan, Afghanistan",
+"volume": "19",
+"author": "Grün",
+"year": "2004",
+"journal-title": "Photogramm. Rec."
+},
+{
+"issue": "6",
+"key": "10.1016/j.jas.2019.105013_bib18",
+"doi-asserted-by": "crossref",
+"first-page": "610",
+"DOI": "10.1109/TSMC.1973.4309314",
+"article-title": "Textural features for image classification",
+"author": "Haralick",
+"year": "1973",
+"journal-title": "IEEE Trans. Syst., Man, Cybernet., SMC-3"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib19",
+"doi-asserted-by": "crossref",
+"first-page": "76",
+"DOI": "10.1558/jmea.v14i1.76",
+"article-title": "Excavating to excess? Implications of the last decade of archaeology in Israel",
+"volume": "14",
+"author": "Kletter",
+"year": "2001",
+"journal-title": "J. Mediterr. Archaeol."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib20",
+"first-page": "299",
+"article-title": "Testing Google Earth Engine for the automatic identification and vectorization of archaeological features: a case study from Faynan, Jordan",
+"volume": "15",
+"author": "Liss",
+"year": "2017",
+"journal-title": "J. Archaeol. Sci.: Report"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib21",
+"series-title": "Geographical Information Systems and Landscape Archaeology",
+"first-page": "55",
+"article-title": "Towards a methodology for modelling surface survey data: the sangro valley project",
+"author": "Lock",
+"year": "1999"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib22",
+"series-title": "Extracting Meaning from Ploughsoil Assemblages",
+"first-page": "5",
+"article-title": "Methods of collection recording and quantification",
+"author": "Mattingly",
+"year": "2000"
+},
+{
+"issue": "14",
+"key": "10.1016/j.jas.2019.105013_bib23",
+"doi-asserted-by": "crossref",
+"first-page": "E778",
+"DOI": "10.1073/pnas.1115472109",
+"article-title": "Mapping patterns of long-term settlement in Northern Mesopotamia at a large scale",
+"volume": "109",
+"author": "Menze",
+"year": "2012",
+"journal-title": "Proc. Natl. Acad. Sci."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib24",
+"doi-asserted-by": "crossref",
+"first-page": "80",
+"DOI": "10.1016/j.jas.2015.04.002",
+"article-title": "A supervised machine-learning approach towards geochemical predictive modelling in archaeology",
+"volume": "59",
+"author": "Oonk",
+"year": "2015",
+"journal-title": "J. Archaeol. Sci."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib25",
+"doi-asserted-by": "crossref",
+"first-page": "49",
+"DOI": "10.1016/j.isprsjprs.2012.07.005",
+"article-title": "Combining terrestrial stereophotogrammetry, DGPS and GIS-based 3D voxel modelling in the volumetric recording of archaeological features",
+"volume": "76",
+"author": "Orengo",
+"year": "2013",
+"journal-title": "ISPRS J. Photogrammetry Remote Sens."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib26",
+"doi-asserted-by": "crossref",
+"first-page": "100",
+"DOI": "10.1016/j.jas.2015.10.008",
+"article-title": "Photogrammetric re-discovery of the Eastern Thessalian hidden long-term landscapes",
+"volume": "64",
+"author": "Orengo",
+"year": "2015",
+"journal-title": "J. Archaeol. Sci."
+},
+{
+"issue": "3",
+"key": "10.1016/j.jas.2019.105013_bib27",
+"doi-asserted-by": "crossref",
+"first-page": "479",
+"DOI": "10.3764/aja.122.3.0479",
+"article-title": "Towards a definition of Minoan agro-pastoral landscapes: results of the survey at Palaikastro (Crete)",
+"volume": "122",
+"author": "Orengo",
+"year": "2018",
+"journal-title": "Am. J. Archaeol."
+},
+{
+"issue": "7",
+"key": "10.1016/j.jas.2019.105013_bib28",
+"doi-asserted-by": "crossref",
+"first-page": "735",
+"DOI": "10.3390/rs9070735",
+"article-title": "Large-scale, multi-temporal remote sensing of palaeo-river networks: a case study from Northwest India and its implications for the Indus civilisation",
+"volume": "9",
+"author": "Orengo",
+"year": "2017",
+"journal-title": "Remote Sens."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib29",
+"doi-asserted-by": "crossref",
+"first-page": "1361",
+"DOI": "10.1002/esp.4317",
+"article-title": "Multi-scale relief model (MSRM): a new algorithm for the visualization of subtle topographic change of variable size in digital elevation models",
+"volume": "43",
+"author": "Orengo",
+"year": "2018",
+"journal-title": "Earth Surf. Process. Landforms"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib30",
+"series-title": "Submitted to Proceedings of the National Academy of Sciences",
+"article-title": "Living on the edge of the desert: automated detection of archaeological mounds in Cholistan (Pakistan) using machine learning classification of multi-sensor multi-temporal satellite data",
+"author": "Orengo",
+"year": "2019"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib31",
+"first-page": "154",
+"article-title": "How many trees in a random forest?",
+"volume": "vol. 7376",
+"author": "Oshiro",
+"year": "2012"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib32",
+"article-title": "Decision-making in modern surveys",
+"volume": "ume 1",
+"author": "Plog",
+"year": "1978"
+},
+{
+"issue": "4",
+"key": "10.1016/j.jas.2019.105013_bib33",
+"doi-asserted-by": "crossref",
+"first-page": "100",
+"DOI": "10.3390/geosciences7040100",
+"article-title": "From above and on the ground: geospatial methods for recording endangered archaeology in the Middle East and north africa",
+"volume": "7",
+"author": "Rayne",
+"year": "2017",
+"journal-title": "Geosciences"
+},
+{
+"issue": "1",
+"key": "10.1016/j.jas.2019.105013_bib34",
+"doi-asserted-by": "crossref",
+"first-page": "1",
+"DOI": "10.1080/00438243.1978.9979712",
+"article-title": "The design of archaeological surveys",
+"volume": "10",
+"author": "Schiffer",
+"year": "1978",
+"journal-title": "World Archaeol."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib35",
+"series-title": "Experiments in the Collection and Analysis of Archaeological Survey Data: the East Hampshire Survey",
+"author": "Shennan",
+"year": "1985"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib36",
+"doi-asserted-by": "crossref",
+"first-page": "1066",
+"DOI": "10.1016/j.culher.2016.06.006",
+"article-title": "Drones over Mediterranean landscapes. The potential of small UAV's (drones) for site detection and heritage management in archaeological survey projects: a case study from Le Pianelle in the Tappino Valley, Molise (Italy)",
+"volume": "22",
+"author": "Stek",
+"year": "2016",
+"journal-title": "J. Cult. Herit."
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib37",
+"series-title": "Side-by-Side Survey. Comparative Regional Studies in the Mediterranean World",
+"first-page": "65",
+"article-title": "Side-by-side and back to front: exploring intra-regional latitudinal and longitudinal comparability in survey data. Three case studies from Metaponto, southern Italy",
+"author": "Thomson",
+"year": "2004"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib38",
+"series-title": "Digital Discovery. Exploring New Frontiers in Human Heritage. Computer Applications and Quantitative Methods in Archaeology",
+"article-title": "Computer vision and machine learning for archaeology",
+"author": "van der Maaten",
+"year": "2007"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib39",
+"doi-asserted-by": "crossref",
+"first-page": "1114",
+"DOI": "10.1111/j.1475-4754.2012.00667.x",
+"article-title": "Computer vision-based orthophoto mapping of complex archaeological sites: the ancient quarry of Pitaranha (Portugal-Spain)",
+"volume": "54",
+"author": "Verhoeven",
+"year": "2012",
+"journal-title": "Archaeometry"
+},
+{
+"key": "10.1016/j.jas.2019.105013_bib40",
+"series-title": "A Guide for Salvage Archeology",
+"author": "Wendorf",
+"year": "1962"
+}
+],
+"container-title": [
+"Journal of Archaeological Science"
+],
+"original-title": [
+
+],
+"language": "en",
+"link": [
+{
+"URL": "https://api.elsevier.com/content/article/PII:S0305440319301001?httpAccept=text/xml",
+"content-type": "text/xml",
+"content-version": "vor",
+"intended-application": "text-mining"
+},
+{
+"URL": "https://api.elsevier.com/content/article/PII:S0305440319301001?httpAccept=text/plain",
+"content-type": "text/plain",
+"content-version": "vor",
+"intended-application": "text-mining"
+}
+],
+"deposited": {
+"date-parts": [
+[
+2019,
+11,
+25
+]
+],
+"date-time": "2019-11-25T06:46:34Z",
+"timestamp": 1574664394000
+},
+"score": 1,
+"subtitle": [
+
+],
+"short-title": [
+
+],
+"issued": {
+"date-parts": [
+[
+2019,
+12
+]
+]
+},
+"references-count": 39,
+"alternative-id": [
+"S0305440319301001"
+],
+"URL": "http://dx.doi.org/10.1016/j.jas.2019.105013",
+"relation": {
+
+},
+"ISSN": [
+"0305-4403"
+],
+"issn-type": [
+{
+"value": "0305-4403",
+"type": "print"
+}
+],
+"subject": [
+"Archaeology",
+"Archaeology"
+],
+"published": {
+"date-parts": [
+[
+2019,
+12
+]
+]
+},
+"assertion": [
+{
+"value": "Elsevier",
+"name": "publisher",
+"label": "This article is maintained by"
+},
+{
+"value": "A brave new world for archaeological survey: Automated machine learning-based potsherd detection using high-resolution drone imagery",
+"name": "articletitle",
+"label": "Article Title"
+},
+{
+"value": "Journal of Archaeological Science",
+"name": "journaltitle",
+"label": "Journal Title"
+},
+{
+"value": "https://doi.org/10.1016/j.jas.2019.105013",
+"name": "articlelink",
+"label": "CrossRef DOI link to publisher maintained version"
+},
+{
+"value": "article",
+"name": "content_type",
+"label": "Content Type"
+},
+{
+"value": "© 2019 The Authors. Published by Elsevier Ltd.",
+"name": "copyright",
+"label": "Copyright"
+}
+],
+"article-number": "105013"
+}

dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/PropagationConstant.java

@@ -25,6 +25,24 @@ public class PropagationConstant {
 	private PropagationConstant() {
 	}
 
+	public static final String DOI = "doi";
+	public static final String REF_DOI = ".refs";
+
+	public static final String UPDATE_DATA_INFO_TYPE = "update";
+	public static final String UPDATE_SUBJECT_FOS_CLASS_ID = "subject:fos";
+	public static final String UPDATE_CLASS_NAME = "Inferred  by OpenAIRE";
+	public static final String UPDATE_MEASURE_BIP_CLASS_ID = "measure:bip";
+
+	public static final String FOS_CLASS_ID = "FOS";
+	public static final String FOS_CLASS_NAME = "Fields of Science and Technology classification";
+
+	public static final String OPENCITATIONS_CLASSID = "sysimport:crosswalk:opencitations";
+	public static final String OPENCITATIONS_CLASSNAME = "Imported from OpenCitations";
+	public static final String ID_PREFIX = "50|doi_________::";
+	public static final String OC_TRUST = "0.91";
+
+	public final static String NULL = "NULL";
+
 	public static final String INSTITUTIONAL_REPO_TYPE = "pubsrepository::institutional";
 
 	public static final String PROPAGATION_DATA_INFO_TYPE = "propagation";
@@ -75,10 +93,25 @@ public class PropagationConstant {
 
 	public static DataInfo getDataInfo(
 		String inference_provenance, String inference_class_id, String inference_class_name, String qualifierSchema) {
+
+		return getDataInfo(inference_provenance, inference_class_id, inference_class_name, qualifierSchema, "0.85");
+	}
+
+	public static DataInfo getDataInfo(
+		String inference_provenance, String inference_class_id, String inference_class_name, String qualifierSchema,
+		String trust) {
+		return getDataInfo(
+			inference_provenance, inference_class_id, inference_class_name, qualifierSchema, trust, true);
+
+	}
+
+	public static DataInfo getDataInfo(
+		String inference_provenance, String inference_class_id, String inference_class_name, String qualifierSchema,
+		String trust, boolean inferred) {
 		DataInfo di = new DataInfo();
-		di.setInferred(true);
+		di.setInferred(inferred);
 		di.setDeletedbyinference(false);
-		di.setTrust("0.85");
+		di.setTrust(trust);
 		di.setInferenceprovenance(inference_provenance);
 		di.setProvenanceaction(getQualifier(inference_class_id, inference_class_name, qualifierSchema));
 		return di;

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/oa/graph/merge/MergeGraphTableSparkJob.java

@@ -127,13 +127,6 @@ public class MergeGraphTableSparkJob {
 				}
 			}, Encoders.bean(p_clazz))
 			.filter((FilterFunction<P>) Objects::nonNull)
-			.filter((FilterFunction<P>) o -> {
-				HashSet<String> collectedFromNames = Optional
-					.ofNullable(o.getCollectedfrom())
-					.map(c -> c.stream().map(KeyValue::getValue).collect(Collectors.toCollection(HashSet::new)))
-					.orElse(new HashSet<>());
-				return !collectedFromNames.contains("Datacite");
-			})
 			.write()
 			.mode(SaveMode.Overwrite)
 			.option("compression", "gzip")

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/oa/graph/raw/CopyHdfsOafApplication.java

@@ -1,136 +0,0 @@
-
-package eu.dnetlib.dhp.oa.graph.raw;
-
-import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
-
-import java.util.*;
-
-import org.apache.commons.io.IOUtils;
-import org.apache.spark.SparkConf;
-import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.api.java.function.FilterFunction;
-import org.apache.spark.api.java.function.FlatMapFunction;
-import org.apache.spark.api.java.function.MapFunction;
-import org.apache.spark.sql.Dataset;
-import org.apache.spark.sql.Encoders;
-import org.apache.spark.sql.SaveMode;
-import org.apache.spark.sql.SparkSession;
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
-
-import com.clearspring.analytics.util.Lists;
-import com.fasterxml.jackson.databind.ObjectMapper;
-
-import eu.dnetlib.dhp.application.ArgumentApplicationParser;
-import eu.dnetlib.dhp.common.HdfsSupport;
-import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup;
-import eu.dnetlib.dhp.oa.graph.raw.common.AbstractMigrationApplication;
-import eu.dnetlib.dhp.schema.common.EntityType;
-import eu.dnetlib.dhp.schema.common.ModelSupport;
-import eu.dnetlib.dhp.schema.oaf.Oaf;
-import eu.dnetlib.dhp.schema.oaf.Relation;
-import eu.dnetlib.dhp.utils.ISLookupClientFactory;
-import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
-
-public class CopyHdfsOafApplication extends AbstractMigrationApplication {
-
-	private static final Logger log = LoggerFactory.getLogger(CopyHdfsOafApplication.class);
-
-	private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
-
-	public static void main(final String[] args) throws Exception {
-		final ArgumentApplicationParser parser = new ArgumentApplicationParser(
-			IOUtils
-				.toString(
-					CopyHdfsOafApplication.class
-						.getResourceAsStream("/eu/dnetlib/dhp/oa/graph/copy_hdfs_oaf_parameters.json")));
-		parser.parseArgument(args);
-
-		final Boolean isSparkSessionManaged = Optional
-			.ofNullable(parser.get("isSparkSessionManaged"))
-			.map(Boolean::valueOf)
-			.orElse(Boolean.TRUE);
-		log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
-
-		final String mdstoreManagerUrl = parser.get("mdstoreManagerUrl");
-		log.info("mdstoreManagerUrl: {}", mdstoreManagerUrl);
-
-		final String mdFormat = parser.get("mdFormat");
-		log.info("mdFormat: {}", mdFormat);
-
-		final String mdLayout = parser.get("mdLayout");
-		log.info("mdLayout: {}", mdLayout);
-
-		final String mdInterpretation = parser.get("mdInterpretation");
-		log.info("mdInterpretation: {}", mdInterpretation);
-
-		final String hdfsPath = parser.get("hdfsPath");
-		log.info("hdfsPath: {}", hdfsPath);
-
-		final String isLookupUrl = parser.get("isLookupUrl");
-		log.info("isLookupUrl: {}", isLookupUrl);
-
-		final ISLookUpService isLookupService = ISLookupClientFactory.getLookUpService(isLookupUrl);
-		final VocabularyGroup vocs = VocabularyGroup.loadVocsFromIS(isLookupService);
-
-		final Set<String> paths = mdstorePaths(mdstoreManagerUrl, mdFormat, mdLayout, mdInterpretation);
-
-		final SparkConf conf = new SparkConf();
-		runWithSparkSession(conf, isSparkSessionManaged, spark -> processPaths(spark, vocs, hdfsPath, paths));
-	}
-
-	public static void processPaths(final SparkSession spark,
-		final VocabularyGroup vocs,
-		final String outputPath,
-		final Set<String> paths) {
-
-		final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
-
-		log.info("Found {} mdstores", paths.size());
-		paths.forEach(log::info);
-
-		final String[] validPaths = paths
-			.stream()
-			.filter(p -> HdfsSupport.exists(p, sc.hadoopConfiguration()))
-			.toArray(String[]::new);
-		log.info("Non empty mdstores {}", validPaths.length);
-
-		if (validPaths.length > 0) {
-			// load the dataset
-			Dataset<Oaf> oaf = spark
-				.read()
-				.load(validPaths)
-				.as(Encoders.kryo(Oaf.class));
-
-			// dispatch each entity type individually in the respective graph subdirectory in append mode
-			for (Map.Entry<String, Class> e : ModelSupport.oafTypes.entrySet()) {
-				oaf
-					.filter((FilterFunction<Oaf>) o -> o.getClass().getSimpleName().toLowerCase().equals(e.getKey()))
-					.map((MapFunction<Oaf, String>) OBJECT_MAPPER::writeValueAsString, Encoders.bean(e.getValue()))
-					.write()
-					.option("compression", "gzip")
-					.mode(SaveMode.Append)
-					.text(outputPath + "/" + e.getKey());
-			}
-		}
-	}
-
-	private static Relation getInverse(Relation rel, VocabularyGroup vocs) {
-		final Relation inverse = new Relation();
-
-		inverse.setProperties(rel.getProperties());
-		inverse.setValidated(rel.getValidated());
-		inverse.setValidationDate(rel.getValidationDate());
-		inverse.setCollectedfrom(rel.getCollectedfrom());
-		inverse.setDataInfo(rel.getDataInfo());
-		inverse.setLastupdatetimestamp(rel.getLastupdatetimestamp());
-
-		inverse.setSource(rel.getTarget());
-		inverse.setTarget(rel.getSource());
-		inverse.setRelType(rel.getRelType());
-		inverse.setSubRelType(rel.getSubRelType());
-
-		return inverse;
-	}
-
-}

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/oa/graph/raw/CopyHdfsOafSparkApplication.scala

@@ -0,0 +1,74 @@
+package eu.dnetlib.dhp.oa.graph.raw
+
+import com.fasterxml.jackson.databind.ObjectMapper
+import eu.dnetlib.dhp.application.ArgumentApplicationParser
+import eu.dnetlib.dhp.common.HdfsSupport
+import eu.dnetlib.dhp.schema.common.ModelSupport
+import eu.dnetlib.dhp.schema.mdstore.MDStoreWithInfo
+import eu.dnetlib.dhp.schema.oaf.Oaf
+import eu.dnetlib.dhp.utils.DHPUtils
+import org.apache.commons.io.IOUtils
+import org.apache.commons.lang3.StringUtils
+import org.apache.http.client.methods.HttpGet
+import org.apache.http.impl.client.HttpClients
+import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.{SparkConf, SparkContext}
+import org.slf4j.LoggerFactory
+
+import scala.collection.JavaConverters._
+import scala.io.Source
+
+object CopyHdfsOafSparkApplication {
+
+  def main(args: Array[String]): Unit = {
+    val log = LoggerFactory.getLogger(getClass)
+    val conf = new SparkConf()
+    val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/oa/graph/copy_hdfs_oaf_parameters.json")).mkString)
+    parser.parseArgument(args)
+
+    val spark =
+      SparkSession
+        .builder()
+        .config(conf)
+        .appName(getClass.getSimpleName)
+        .master(parser.get("master")).getOrCreate()
+
+    val sc: SparkContext = spark.sparkContext
+
+    val mdstoreManagerUrl = parser.get("mdstoreManagerUrl")
+    log.info("mdstoreManagerUrl: {}", mdstoreManagerUrl)
+
+    val mdFormat = parser.get("mdFormat")
+    log.info("mdFormat: {}", mdFormat)
+
+    val mdLayout = parser.get("mdLayout")
+    log.info("mdLayout: {}", mdLayout)
+
+    val mdInterpretation = parser.get("mdInterpretation")
+    log.info("mdInterpretation: {}", mdInterpretation)
+
+    val hdfsPath = parser.get("hdfsPath")
+    log.info("hdfsPath: {}", hdfsPath)
+
+    implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
+
+    val paths = DHPUtils.mdstorePaths(mdstoreManagerUrl, mdFormat, mdLayout, mdInterpretation, true).asScala
+
+    val validPaths: List[String] = paths.filter(p => HdfsSupport.exists(p, sc.hadoopConfiguration)).toList
+
+    if (validPaths.nonEmpty) {
+      val oaf = spark.read.load(validPaths: _*).as[Oaf]
+      val mapper = new ObjectMapper()
+      val l =ModelSupport.oafTypes.entrySet.asScala.map(e => e.getKey).toList
+      l.foreach(
+        e =>
+          oaf.filter(o => o.getClass.getSimpleName.equalsIgnoreCase(e))
+            .map(s => mapper.writeValueAsString(s))(Encoders.STRING)
+            .write
+            .option("compression", "gzip")
+            .mode(SaveMode.Append)
+            .text(s"$hdfsPath/${e}")
+      )
+    }
+  }
+}

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/oa/graph/raw/MigrateDbEntitiesApplication.java

@@ -186,6 +186,9 @@ public class MigrateDbEntitiesApplication extends AbstractMigrationApplication i
 
 					log.info("Processing Openorgs Merge Rels...");
 					smdbe.execute("queryOpenOrgsSimilarityForProvision.sql", smdbe::processOrgOrgMergeRels);
+
+					log.info("Processing Openorgs Parent/Child Rels...");
+					smdbe.execute("queryParentChildRelsOpenOrgs.sql", smdbe::processOrgOrgParentChildRels);
 					break;
 
 				case openaire_organizations:
@@ -689,6 +692,35 @@ public class MigrateDbEntitiesApplication extends AbstractMigrationApplication i
 		}
 	}
 
+	public List<Oaf> processOrgOrgParentChildRels(final ResultSet rs) {
+		try {
+			final DataInfo info = prepareDataInfo(rs); // TODO
+
+			final String orgId1 = createOpenaireId(20, rs.getString("source"), true);
+			final String orgId2 = createOpenaireId(20, rs.getString("target"), true);
+
+			final List<KeyValue> collectedFrom = listKeyValues(
+				createOpenaireId(10, rs.getString("collectedfromid"), true), rs.getString("collectedfromname"));
+
+			final Relation r = new Relation();
+			r.setRelType(ORG_ORG_RELTYPE);
+			r.setSubRelType(ModelConstants.RELATIONSHIP);
+			r
+				.setRelClass(
+					rs.getString("type").equalsIgnoreCase("parent") ? ModelConstants.IS_PARENT_OF
+						: ModelConstants.IS_CHILD_OF);
+			r.setSource(orgId1);
+			r.setTarget(orgId2);
+			r.setCollectedfrom(collectedFrom);
+			r.setDataInfo(info);
+			r.setLastupdatetimestamp(lastUpdateTimestamp);
+
+			return Arrays.asList(r);
+		} catch (final Exception e) {
+			throw new RuntimeException(e);
+		}
+	}
+
 	public List<Oaf> processOrgOrgSimRels(final ResultSet rs) {
 		try {
 			final DataInfo info = prepareDataInfo(rs); // TODO

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/oa/graph/raw/common/AbstractMigrationApplication.java

@@ -26,6 +26,7 @@ import com.fasterxml.jackson.databind.ObjectMapper;
 
 import eu.dnetlib.dhp.schema.mdstore.MDStoreWithInfo;
 import eu.dnetlib.dhp.schema.oaf.Oaf;
+import eu.dnetlib.dhp.utils.DHPUtils;
 
 public class AbstractMigrationApplication implements Closeable {
 
@@ -71,27 +72,7 @@ public class AbstractMigrationApplication implements Closeable {
 		final String format,
 		final String layout,
 		final String interpretation) throws IOException {
-		final String url = mdstoreManagerUrl + "/mdstores/";
-		final ObjectMapper objectMapper = new ObjectMapper();
-
-		final HttpGet req = new HttpGet(url);
-
-		try (final CloseableHttpClient client = HttpClients.createDefault()) {
-			try (final CloseableHttpResponse response = client.execute(req)) {
-				final String json = IOUtils.toString(response.getEntity().getContent());
-				final MDStoreWithInfo[] mdstores = objectMapper.readValue(json, MDStoreWithInfo[].class);
-				return Arrays
-					.stream(mdstores)
-					.filter(md -> md.getFormat().equalsIgnoreCase(format))
-					.filter(md -> md.getLayout().equalsIgnoreCase(layout))
-					.filter(md -> md.getInterpretation().equalsIgnoreCase(interpretation))
-					.filter(md -> StringUtils.isNotBlank(md.getHdfsPath()))
-					.filter(md -> StringUtils.isNotBlank(md.getCurrentVersion()))
-					.filter(md -> md.getSize() > 0)
-					.map(md -> md.getHdfsPath() + "/" + md.getCurrentVersion() + "/store")
-					.collect(Collectors.toSet());
-			}
-		}
+		return DHPUtils.mdstorePaths(mdstoreManagerUrl, format, layout, interpretation, false);
 	}
 
 	private Configuration getConf() {

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/oa/graph/resolution/SparkResolveEntities.scala

@@ -0,0 +1,107 @@
+package eu.dnetlib.dhp.oa.graph.resolution
+
+import com.fasterxml.jackson.databind.ObjectMapper
+import eu.dnetlib.dhp.application.ArgumentApplicationParser
+import eu.dnetlib.dhp.common.HdfsSupport
+import eu.dnetlib.dhp.schema.common.EntityType
+import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Result, Software, Dataset => OafDataset}
+import org.apache.commons.io.IOUtils
+import org.apache.hadoop.fs.{FileSystem, Path}
+import org.apache.spark.SparkConf
+import org.apache.spark.sql._
+import org.slf4j.{Logger, LoggerFactory}
+
+object SparkResolveEntities {
+
+  val mapper = new ObjectMapper()
+  val entities = List(EntityType.dataset,EntityType.publication, EntityType.software, EntityType.otherresearchproduct)
+
+  def main(args: Array[String]): Unit = {
+    val log: Logger = LoggerFactory.getLogger(getClass)
+    val conf: SparkConf = new SparkConf()
+    val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/oa/graph/resolution/resolve_entities_params.json")))
+    parser.parseArgument(args)
+    val spark: SparkSession =
+      SparkSession
+        .builder()
+        .config(conf)
+        .appName(getClass.getSimpleName)
+        .master(parser.get("master")).getOrCreate()
+
+
+    val graphBasePath = parser.get("graphBasePath")
+    log.info(s"graphBasePath  -> $graphBasePath")
+    val workingPath = parser.get("workingPath")
+    log.info(s"workingPath  -> $workingPath")
+    val unresolvedPath = parser.get("unresolvedPath")
+    log.info(s"unresolvedPath  -> $unresolvedPath")
+
+    val fs = FileSystem.get(spark.sparkContext.hadoopConfiguration)
+    fs.mkdirs(new Path(workingPath))
+
+    resolveEntities(spark, workingPath, unresolvedPath)
+    generateResolvedEntities(spark, workingPath, graphBasePath)
+
+    // TO BE conservative we keep the original entities in the working dir
+    // and save the resolved entities on the graphBasePath
+    //In future these lines of code should be removed
+    entities.foreach {
+      e =>
+        fs.rename(new Path(s"$graphBasePath/$e"), new Path(s"$workingPath/${e}_old"))
+        fs.rename(new Path(s"$workingPath/resolvedGraph/$e"), new Path(s"$graphBasePath/$e"))
+    }
+
+}
+
+
+def resolveEntities(spark: SparkSession, workingPath: String, unresolvedPath: String) = {
+    implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
+    import spark.implicits._
+
+    val rPid: Dataset[(String, String)] = spark.read.load(s"$workingPath/relationResolvedPid").as[(String, String)]
+    val up: Dataset[(String, Result)] = spark.read.text(unresolvedPath).as[String].map(s => mapper.readValue(s, classOf[Result])).map(r => (r.getId, r))(Encoders.tuple(Encoders.STRING, resEncoder))
+
+    rPid.joinWith(up, rPid("_2").equalTo(up("_1")), "inner").map {
+      r =>
+        val result = r._2._2
+        val dnetId = r._1._1
+        result.setId(dnetId)
+        result
+    }.write.mode(SaveMode.Overwrite).save(s"$workingPath/resolvedEntities")
+  }
+
+
+  def deserializeObject(input:String,  entity:EntityType ) :Result = {
+
+   entity match {
+     case EntityType.publication => mapper.readValue(input, classOf[Publication])
+     case EntityType.dataset => mapper.readValue(input, classOf[OafDataset])
+     case EntityType.software=> mapper.readValue(input, classOf[Software])
+     case EntityType.otherresearchproduct=> mapper.readValue(input, classOf[OtherResearchProduct])
+   }
+  }
+
+ def generateResolvedEntities(spark:SparkSession,  workingPath: String, graphBasePath:String) = {
+
+    implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
+    import spark.implicits._
+
+    val re:Dataset[Result] = spark.read.load(s"$workingPath/resolvedEntities").as[Result]
+    entities.foreach {
+      e =>
+
+        spark.read.text(s"$graphBasePath/$e").as[String]
+          .map(s => deserializeObject(s, e))
+          .union(re)
+          .groupByKey(_.getId)
+          .reduceGroups {
+            (x, y) =>
+              x.mergeFrom(y)
+              x
+          }.map(_._2)
+          .filter(r => r.getClass.getSimpleName.toLowerCase != "result")
+          .map(r => mapper.writeValueAsString(r))(Encoders.STRING)
+          .write.mode(SaveMode.Overwrite).option("compression", "gzip").text(s"$workingPath/resolvedGraph/$e")
+    }
+  }
+}

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/oa/graph/resolution/SparkResolveRelation.scala

@@ -0,0 +1,161 @@
+package eu.dnetlib.dhp.oa.graph.resolution
+
+import com.fasterxml.jackson.databind.ObjectMapper
+import eu.dnetlib.dhp.application.ArgumentApplicationParser
+import eu.dnetlib.dhp.common.HdfsSupport
+import eu.dnetlib.dhp.schema.oaf.{Relation, Result}
+import eu.dnetlib.dhp.utils.DHPUtils
+import org.apache.commons.io.IOUtils
+import org.apache.hadoop.fs.{FileSystem, Path}
+import org.apache.spark.SparkConf
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql._
+import org.json4s
+import org.json4s.DefaultFormats
+import org.json4s.JsonAST.{JField, JObject, JString}
+import org.json4s.jackson.JsonMethods.parse
+import org.slf4j.{Logger, LoggerFactory}
+
+object SparkResolveRelation {
+  def main(args: Array[String]): Unit = {
+    val log: Logger = LoggerFactory.getLogger(getClass)
+    val conf: SparkConf = new SparkConf()
+    val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/oa/graph/resolution/resolve_relations_params.json")))
+    parser.parseArgument(args)
+    val spark: SparkSession =
+      SparkSession
+        .builder()
+        .config(conf)
+        .appName(getClass.getSimpleName)
+        .master(parser.get("master")).getOrCreate()
+
+
+    val graphBasePath = parser.get("graphBasePath")
+    log.info(s"graphBasePath  -> $graphBasePath")
+    val workingPath = parser.get("workingPath")
+    log.info(s"workingPath  -> $workingPath")
+
+    implicit val relEncoder: Encoder[Relation] = Encoders.kryo(classOf[Relation])
+    import spark.implicits._
+
+
+    //CLEANING TEMPORARY FOLDER
+    HdfsSupport.remove(workingPath, spark.sparkContext.hadoopConfiguration)
+    val fs = FileSystem.get(spark.sparkContext.hadoopConfiguration)
+    fs.mkdirs(new Path(workingPath))
+
+    extractPidResolvedTableFromJsonRDD(spark, graphBasePath, workingPath)
+
+    val mapper: ObjectMapper = new ObjectMapper()
+
+    val rPid: Dataset[(String, String)] = spark.read.load(s"$workingPath/relationResolvedPid").as[(String, String)]
+
+    val relationDs: Dataset[(String, Relation)] = spark.read.text(s"$graphBasePath/relation").as[String]
+      .map(s => mapper.readValue(s, classOf[Relation])).as[Relation]
+      .map(r => (r.getSource.toLowerCase, r))(Encoders.tuple(Encoders.STRING, relEncoder))
+
+    relationDs.joinWith(rPid, relationDs("_1").equalTo(rPid("_2")), "left").map {
+      m =>
+        val sourceResolved = m._2
+        val currentRelation = m._1._2
+        if (sourceResolved != null && sourceResolved._1 != null && sourceResolved._1.nonEmpty)
+          currentRelation.setSource(sourceResolved._1)
+        currentRelation
+    }.write
+      .mode(SaveMode.Overwrite)
+      .save(s"$workingPath/relationResolvedSource")
+
+
+    val relationSourceResolved: Dataset[(String, Relation)] = spark.read.load(s"$workingPath/relationResolvedSource").as[Relation]
+      .map(r => (r.getTarget.toLowerCase, r))(Encoders.tuple(Encoders.STRING, relEncoder))
+    relationSourceResolved.joinWith(rPid, relationSourceResolved("_1").equalTo(rPid("_2")), "left").map {
+      m =>
+        val targetResolved = m._2
+        val currentRelation = m._1._2
+        if (targetResolved != null && targetResolved._1.nonEmpty)
+          currentRelation.setTarget(targetResolved._1)
+        currentRelation
+    }
+      .write
+      .mode(SaveMode.Overwrite)
+      .save(s"$workingPath/relation_resolved")
+
+
+    // TO BE conservative we keep the original relation in the working dir
+    // and save the relation resolved on the graphBasePath
+    //In future this two line of code should be removed
+
+    fs.rename(new Path(s"$graphBasePath/relation"), new Path(s"$workingPath/relation"))
+
+    spark.read.load(s"$workingPath/relation_resolved").as[Relation]
+      .filter(r => !r.getSource.startsWith("unresolved") && !r.getTarget.startsWith("unresolved"))
+      .map(r => mapper.writeValueAsString(r))
+      .write
+      .option("compression", "gzip")
+      .mode(SaveMode.Overwrite)
+      .text(s"$graphBasePath/relation")
+  }
+
+  def extractInstanceCF(input: String): List[(String, String)] = {
+    implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
+    lazy val json: json4s.JValue = parse(input)
+    val result: List[(String, String)] = for {
+      JObject(iObj) <- json \ "instance"
+      JField("collectedfrom", JObject(cf)) <- iObj
+      JField("instancetype", JObject(instancetype)) <- iObj
+      JField("value", JString(collectedFrom)) <- cf
+      JField("classname", JString(classname)) <- instancetype
+    } yield (classname, collectedFrom)
+
+    result
+
+  }
+
+
+  def extractPidsFromRecord(input: String): (String, List[(String, String)]) = {
+    implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
+    lazy val json: json4s.JValue = parse(input)
+    val id: String = (json \ "id").extract[String]
+    val result: List[(String, String)] = for {
+      JObject(pids) <- json \\ "instance" \ "pid"
+      JField("value", JString(pidValue)) <- pids
+      JField("qualifier", JObject(qualifier)) <- pids
+      JField("classid", JString(pidType)) <- qualifier
+    } yield (pidValue, pidType)
+
+    (id, result)
+  }
+
+
+  private def isRelation(input: String): Boolean = {
+
+    implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
+    lazy val json: json4s.JValue = parse(input)
+    val source = (json \ "source").extractOrElse[String](null)
+
+    source != null
+  }
+
+  def extractPidResolvedTableFromJsonRDD(spark: SparkSession, graphPath: String, workingPath: String) = {
+    import spark.implicits._
+
+    val d: RDD[(String, String)] = spark.sparkContext.textFile(s"$graphPath/*")
+      .filter(i => !isRelation(i))
+      .map(i => extractPidsFromRecord(i))
+      .filter(s => s != null && s._1 != null && s._2 != null && s._2.nonEmpty)
+      .flatMap { p =>
+        p._2.map(pid =>
+          (p._1, DHPUtils.generateUnresolvedIdentifier(pid._1, pid._2))
+        )
+      }.filter(r => r._1 != null || r._2 != null)
+
+    spark.createDataset(d)
+      .groupByKey(_._2)
+      .reduceGroups((x, y) => if (x._1.startsWith("50|doi") || x._1.startsWith("50|pmid")) x else y)
+      .map(s => s._2)
+      .write
+      .mode(SaveMode.Overwrite)
+      .save(s"$workingPath/relationResolvedPid")
+  }
+
+}

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/sx/graph/SparkConvertRDDtoDataset.scala

@@ -59,7 +59,12 @@ object SparkConvertRDDtoDataset {
     log.info("Converting Relation")
 
 
-    val rddRelation =spark.sparkContext.textFile(s"$sourcePath/relation").map(s => mapper.readValue(s, classOf[Relation]))
+    val relationSemanticFilter = List("cites", "iscitedby","merges", "ismergedin")
+
+    val rddRelation =spark.sparkContext.textFile(s"$sourcePath/relation")
+      .map(s => mapper.readValue(s, classOf[Relation]))
+      .filter(r=> r.getSource.startsWith("50") && r.getTarget.startsWith("50"))
+      .filter(r => !relationSemanticFilter.exists(k => k.equalsIgnoreCase(r.getRelClass)))
     spark.createDataset(rddRelation).as[Relation].write.mode(SaveMode.Overwrite).save(s"$relPath")
 
 

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/sx/graph/SparkCreateScholix.scala

@@ -51,10 +51,14 @@ object SparkCreateScholix {
 
     relationDS.joinWith(summaryDS, relationDS("_1").equalTo(summaryDS("_1")), "left")
       .map { input: ((String, Relation), (String, ScholixSummary)) =>
-        val rel: Relation = input._1._2
-        val source: ScholixSummary = input._2._2
-        (rel.getTarget, ScholixUtils.scholixFromSource(rel, source))
+        if (input._1!= null && input._2!= null) {
+          val rel: Relation = input._1._2
+          val source: ScholixSummary = input._2._2
+          (rel.getTarget, ScholixUtils.scholixFromSource(rel, source))
+        }
+        else  null
       }(Encoders.tuple(Encoders.STRING, scholixEncoder))
+      .filter(r => r!= null)
       .write.mode(SaveMode.Overwrite).save(s"$targetPath/scholix_from_source")
 
     val scholixSource: Dataset[(String, Scholix)] = spark.read.load(s"$targetPath/scholix_from_source").as[(String, Scholix)](Encoders.tuple(Encoders.STRING, scholixEncoder))

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/sx/graph/SparkResolveRelation.scala

@@ -1,154 +0,0 @@
-package eu.dnetlib.dhp.sx.graph
-
-import com.fasterxml.jackson.databind.ObjectMapper
-import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.schema.oaf.{Relation, Result}
-import org.apache.commons.io.IOUtils
-import org.apache.hadoop.io.compress.GzipCodec
-import org.apache.spark.SparkConf
-import org.apache.spark.rdd.RDD
-import org.apache.spark.sql._
-import org.json4s
-import org.json4s.DefaultFormats
-import org.json4s.JsonAST.{JField, JObject, JString}
-import org.json4s.jackson.JsonMethods.parse
-import org.slf4j.{Logger, LoggerFactory}
-
-import scala.collection.JavaConverters._
-object SparkResolveRelation {
-  def main(args: Array[String]): Unit = {
-    val log: Logger = LoggerFactory.getLogger(getClass)
-    val conf: SparkConf = new SparkConf()
-    val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/resolve_relations_params.json")))
-    parser.parseArgument(args)
-    val spark: SparkSession =
-      SparkSession
-        .builder()
-        .config(conf)
-        .appName(getClass.getSimpleName)
-        .master(parser.get("master")).getOrCreate()
-
-
-    val relationPath = parser.get("relationPath")
-    log.info(s"sourcePath  -> $relationPath")
-    val entityPath = parser.get("entityPath")
-    log.info(s"entityPath  -> $entityPath")
-    val workingPath = parser.get("workingPath")
-    log.info(s"workingPath  -> $workingPath")
-
-    implicit  val relEncoder: Encoder[Relation] = Encoders.kryo(classOf[Relation])
-    import spark.implicits._
-
-
-    extractPidResolvedTableFromJsonRDD(spark, entityPath, workingPath)
-
-    val mappper = new ObjectMapper()
-
-    val rPid:Dataset[(String,String)] = spark.read.load(s"$workingPath/relationResolvedPid").as[(String,String)]
-
-    val relationDs:Dataset[(String,Relation)] = spark.read.load(relationPath).as[Relation].map(r => (r.getSource.toLowerCase, r))(Encoders.tuple(Encoders.STRING, relEncoder))
-
-    relationDs.joinWith(rPid, relationDs("_1").equalTo(rPid("_2")), "left").map{
-      m =>
-        val sourceResolved = m._2
-        val currentRelation = m._1._2
-        if (sourceResolved!=null && sourceResolved._1!=null && sourceResolved._1.nonEmpty)
-          currentRelation.setSource(sourceResolved._1)
-        currentRelation
-    }.write
-      .mode(SaveMode.Overwrite)
-      .save(s"$workingPath/relationResolvedSource")
-
-
-    val relationSourceResolved:Dataset[(String,Relation)] = spark.read.load(s"$workingPath/relationResolvedSource").as[Relation].map(r => (r.getTarget.toLowerCase, r))(Encoders.tuple(Encoders.STRING, relEncoder))
-    relationSourceResolved.joinWith(rPid, relationSourceResolved("_1").equalTo(rPid("_2")), "left").map{
-      m =>
-        val targetResolved = m._2
-        val currentRelation = m._1._2
-        if (targetResolved!=null && targetResolved._1.nonEmpty)
-          currentRelation.setTarget(targetResolved._1)
-        currentRelation
-    }.filter(r => r.getSource.startsWith("50")&& r.getTarget.startsWith("50"))
-      .write
-      .mode(SaveMode.Overwrite)
-      .save(s"$workingPath/relation_resolved")
-
-    spark.read.load(s"$workingPath/relation_resolved").as[Relation]
-                    .map(r => mappper.writeValueAsString(r))
-                    .rdd.saveAsTextFile(s"$workingPath/relation", classOf[GzipCodec])
-
-  }
-
-
-  def extractPidsFromRecord(input:String):(String,List[(String,String)]) = {
-    implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
-    lazy val json: json4s.JValue = parse(input)
-    val id:String = (json \ "id").extract[String]
-    val result: List[(String,String)] = for {
-      JObject(pids) <- json \ "pid"
-      JField("value", JString(pidValue)) <- pids
-      JField("qualifier", JObject(qualifier)) <- pids
-      JField("classname", JString(pidType)) <- qualifier
-    } yield (pidValue, pidType)
-
-    val alternateIds: List[(String,String)] = for {
-      JObject(pids) <- json \\ "alternateIdentifier"
-      JField("value", JString(pidValue)) <- pids
-      JField("qualifier", JObject(qualifier)) <- pids
-      JField("classname", JString(pidType)) <- qualifier
-    } yield (pidValue, pidType)
-
-    (id,result:::alternateIds)
-  }
-
-  private def extractPidResolvedTableFromJsonRDD(spark: SparkSession, entityPath: String, workingPath: String) = {
-    import spark.implicits._
-
-    val d: RDD[(String,String)] = spark.sparkContext.textFile(s"$entityPath/*")
-      .map(i => extractPidsFromRecord(i))
-      .filter(s => s != null && s._1!= null && s._2!=null && s._2.nonEmpty)
-      .flatMap{ p =>
-                  p._2.map(pid =>
-                    (p._1, convertPidToDNETIdentifier(pid._1, pid._2))
-                  )
-      }.filter(r =>r._1 != null || r._2 != null)
-
-    spark.createDataset(d)
-    .groupByKey(_._2)
-      .reduceGroups((x, y) => if (x._1.startsWith("50|doi") || x._1.startsWith("50|pmid")) x else y)
-      .map(s => s._2)
-      .write
-      .mode(SaveMode.Overwrite)
-      .save(s"$workingPath/relationResolvedPid")
-  }
-
-
-  /*
-    This method should be used once we finally convert everythings in Kryo dataset
-    instead of using rdd of json
-   */
-  private def extractPidResolvedTableFromKryo(spark: SparkSession, entityPath: String, workingPath: String) = {
-    import spark.implicits._
-    implicit val oafEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
-    val entities: Dataset[Result] = spark.read.load(s"$entityPath/*").as[Result]
-    entities.flatMap(e => e.getPid.asScala
-      .map(p =>
-        convertPidToDNETIdentifier(p.getValue, p.getQualifier.getClassid))
-      .filter(s => s != null)
-      .map(s => (s, e.getId))
-    ).groupByKey(_._1)
-      .reduceGroups((x, y) => if (x._2.startsWith("50|doi") || x._2.startsWith("50|pmid")) x else y)
-      .map(s => s._2)
-      .write
-      .mode(SaveMode.Overwrite)
-      .save(s"$workingPath/relationResolvedPid")
-  }
-
-  def convertPidToDNETIdentifier(pid:String, pidType: String):String = {
-    if (pid==null || pid.isEmpty || pidType== null || pidType.isEmpty)
-      null
-    else
-      s"unresolved::${pid.toLowerCase}::${pidType.toLowerCase}"
-  }
-
-}

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/sx/graph/scholix/ScholixUtils.scala

@@ -289,7 +289,7 @@ object ScholixUtils {
     if (r.getInstance() == null || r.getInstance().isEmpty)
       return List()
     r.getInstance().asScala.filter(i => i.getUrl!= null && !i.getUrl.isEmpty)
-
+      .filter(i => i.getPid!= null && i.getUrl != null)
       .flatMap(i => findURLForPID(i.getPid.asScala.toList, i.getUrl.asScala.toList))
       .map(i => new ScholixIdentifier(i._1.getValue, i._1.getQualifier.getClassid, i._2)).distinct.toList
   }

dhp-workflows/dhp-graph-mapper/src/main/resources/eu/dnetlib/dhp/oa/graph/copy_hdfs_oaf_parameters.json

@@ -24,15 +24,15 @@
 		"paramRequired": true
 	},
 	{
-		"paramName": "i",
-		"paramLongName": "mdInterpretation",
-		"paramDescription": "metadata interpretation",
+		"paramName": "m",
+		"paramLongName": "master",
+		"paramDescription": "should be yarn or local",
 		"paramRequired": true
 	},
 	{
-		"paramName": "isu",
-		"paramLongName": "isLookupUrl",
-		"paramDescription": "the url of the ISLookupService",
+		"paramName": "i",
+		"paramLongName": "mdInterpretation",
+		"paramDescription": "metadata interpretation",
 		"paramRequired": true
 	}
 ]

dhp-workflows/dhp-graph-mapper/src/main/resources/eu/dnetlib/dhp/oa/graph/raw_all/oozie_app/workflow.xml

@@ -258,7 +258,7 @@
         <switch>
             <case to="ImportDB">${wf:conf('reuseDB') eq false}</case>
             <case to="reuse_odf">${wf:conf('reuseDB') eq true}</case>
-            <default to="ImportDB_claims"/>
+            <default to="ImportDB"/>
         </switch>
     </decision>
 
@@ -553,7 +553,7 @@
             <master>yarn</master>
             <mode>cluster</mode>
             <name>ImportOAF_hdfs_graph</name>
-            <class>eu.dnetlib.dhp.oa.graph.raw.CopyHdfsOafApplication</class>
+            <class>eu.dnetlib.dhp.oa.graph.raw.CopyHdfsOafSparkApplication</class>
             <jar>dhp-graph-mapper-${projectVersion}.jar</jar>
             <spark-opts>
                 --executor-memory ${sparkExecutorMemory}
@@ -568,8 +568,8 @@
             <arg>--mdstoreManagerUrl</arg><arg>${mdstoreManagerUrl}</arg>
             <arg>--mdFormat</arg><arg>OAF</arg>
             <arg>--mdLayout</arg><arg>store</arg>
+            <arg>--master</arg><arg>yarn</arg>
             <arg>--mdInterpretation</arg><arg>graph</arg>
-            <arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
         </spark>
         <ok to="wait_graphs"/>
         <error to="Kill"/>

dhp-workflows/dhp-graph-mapper/src/main/resources/eu/dnetlib/dhp/oa/graph/resolution/oozie_app/workflow.xml

@@ -0,0 +1,72 @@
+<workflow-app name="Resolve relation and entities" xmlns="uri:oozie:workflow:0.5">
+    <parameters>
+        <property>
+            <name>graphBasePath</name>
+            <description>the path of the graph</description>
+        </property>
+        <property>
+            <name>unresolvedPath</name>
+            <description>the path of the unresolved Entities</description>
+        </property>
+    </parameters>
+
+    <start to="ResolveRelations"/>
+
+    <kill name="Kill">
+        <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
+    </kill>
+
+    <action name="ResolveRelations">
+        <spark xmlns="uri:oozie:spark-action:0.2">
+            <master>yarn</master>
+            <mode>cluster</mode>
+            <name>Resolve Relations in raw graph</name>
+            <class>eu.dnetlib.dhp.oa.graph.resolution.SparkResolveRelation</class>
+            <jar>dhp-graph-mapper-${projectVersion}.jar</jar>
+            <spark-opts>
+                --executor-memory=${sparkExecutorMemory}
+                --executor-cores=${sparkExecutorCores}
+                --driver-memory=${sparkDriverMemory}
+                --conf spark.extraListeners=${spark2ExtraListeners}
+                --conf spark.sql.shuffle.partitions=15000
+                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
+                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
+                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
+            </spark-opts>
+            <arg>--master</arg><arg>yarn</arg>
+            <arg>--graphBasePath</arg><arg>${graphBasePath}</arg>
+            <arg>--workingPath</arg><arg>${workingDir}</arg>
+        </spark>
+        <ok to="ResolveEntities"/>
+        <error to="Kill"/>
+    </action>
+
+    <action name="ResolveEntities">
+        <spark xmlns="uri:oozie:spark-action:0.2">
+            <master>yarn</master>
+            <mode>cluster</mode>
+            <name>Resolve Entities in raw graph</name>
+            <class>eu.dnetlib.dhp.oa.graph.resolution.SparkResolveEntities</class>
+            <jar>dhp-graph-mapper-${projectVersion}.jar</jar>
+            <spark-opts>
+                --executor-memory=${sparkExecutorMemory}
+                --executor-cores=${sparkExecutorCores}
+                --driver-memory=${sparkDriverMemory}
+                --conf spark.extraListeners=${spark2ExtraListeners}
+                --conf spark.sql.shuffle.partitions=10000
+                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
+                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
+                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
+            </spark-opts>
+            <arg>--master</arg><arg>yarn</arg>
+            <arg>--graphBasePath</arg><arg>${graphBasePath}</arg>
+            <arg>--unresolvedPath</arg><arg>${unresolvedPath}</arg>
+            <arg>--workingPath</arg><arg>${workingDir}</arg>
+        </spark>
+        <ok to="End"/>
+        <error to="Kill"/>
+    </action>
+
+    <end name="End"/>
+
+</workflow-app>

dhp-workflows/dhp-graph-mapper/src/main/resources/eu/dnetlib/dhp/oa/graph/resolution/resolve_entities_params.json

@@ -0,0 +1,6 @@
+[
+  {"paramName":"mt",  "paramLongName":"master",       "paramDescription": "should be local or yarn",    "paramRequired": true},
+  {"paramName":"w",   "paramLongName":"workingPath",  "paramDescription": "the source Path",            "paramRequired": true},
+  {"paramName":"u",   "paramLongName":"unresolvedPath",  "paramDescription": "the source Path",            "paramRequired": true},
+  {"paramName":"g",   "paramLongName":"graphBasePath",   "paramDescription": "the path of the raw graph",  "paramRequired": true}
+]