Merge branch 'beta' into hierarchical_orgs_relations

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
+									final String decoded = Unidecode.decode(title);
-										.decode(title)
+
-										.replaceAll(TITLE_FILTER_REGEX, "");
+									if (StringUtils.contains(decoded, TITLE_TEST)) {
-									return residual.length() > TITLE_FILTER_RESIDUAL_LENGTH;
+										return decoded
+											.replaceAll(TITLE_FILTER_REGEX, "")
+											.length() > TITLE_FILTER_RESIDUAL_LENGTH;
+									}
+									return !decoded
+										.replaceAll("\\W|\\d", "")
+										.isEmpty();
 								})
 							.map(GraphCleaningFunctions::cleanValue)
 							.collect(Collectors.toList()));

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/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/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)
+      pubmedInstance.setAlternateIdentifier(List(alternateIdentifier).asJava)
-    result.setInstance(List(i).asJava)
+    result.setInstance(List(pubmedInstance).asJava)
-    i.getPid.asScala.filter(p => "pmid".equalsIgnoreCase(p.getQualifier.getClassid)).map(p => p.getValue)(collection.breakOut)
+    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)
+      pubmedInstance.setUrl(urlLists.asJava)
-    i.setDateofacceptance(OafMapperUtils.field(GraphCleaningFunctions.cleanDate(article.getDate), dataInfo))
+
-    i.setCollectedfrom(collectedFrom)
+    //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

@@ -0,0 +1,30 @@
+<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>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>

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/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/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/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/java/eu/dnetlib/dhp/oa/dedup/DedupUtility.java

@@ -14,6 +14,9 @@ import org.xml.sax.SAXException;
 
 import com.google.common.collect.Sets;
 
+import eu.dnetlib.dhp.schema.common.ModelConstants;
+import eu.dnetlib.dhp.schema.oaf.DataInfo;
+import eu.dnetlib.dhp.schema.oaf.Relation;
 import eu.dnetlib.dhp.utils.ISLookupClientFactory;
 import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpException;
 import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
@@ -152,4 +155,25 @@ public class DedupUtility {
 		return o1.compareTo(o2);
 	}
 
+	public static Relation createSimRel(String source, String target, String entity) {
+		final Relation r = new Relation();
+		r.setSource(source);
+		r.setTarget(target);
+		r.setSubRelType("dedupSimilarity");
+		r.setRelClass(ModelConstants.IS_SIMILAR_TO);
+		r.setDataInfo(new DataInfo());
+
+		switch (entity) {
+			case "result":
+				r.setRelType(ModelConstants.RESULT_RESULT);
+				break;
+			case "organization":
+				r.setRelType(ModelConstants.ORG_ORG_RELTYPE);
+				break;
+			default:
+				throw new IllegalArgumentException("unmanaged entity type: " + entity);
+		}
+		return r;
+	}
+
 }

dhp-workflows/dhp-dedup-openaire/src/main/java/eu/dnetlib/dhp/oa/dedup/SparkCopyRelationsNoOpenorgs.java

@@ -63,7 +63,9 @@ public class SparkCopyRelationsNoOpenorgs extends AbstractSparkAction {
 			.toJavaRDD()
 			.filter(x -> !isOpenorgs(x));
 
-		log.info("Number of non-Openorgs relations collected: {}", simRels.count());
+		if (log.isDebugEnabled()) {
+			log.debug("Number of non-Openorgs relations collected: {}", simRels.count());
+		}
 
 		spark
 			.createDataset(simRels.rdd(), Encoders.bean(Relation.class))

dhp-workflows/dhp-dedup-openaire/src/main/java/eu/dnetlib/dhp/oa/dedup/SparkCreateSimRels.java

@@ -20,6 +20,7 @@ import org.xml.sax.SAXException;
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser;
 import eu.dnetlib.dhp.oa.dedup.model.Block;
+import eu.dnetlib.dhp.schema.common.ModelConstants;
 import eu.dnetlib.dhp.schema.oaf.DataInfo;
 import eu.dnetlib.dhp.schema.oaf.Relation;
 import eu.dnetlib.dhp.utils.ISLookupClientFactory;
@@ -102,7 +103,7 @@ public class SparkCreateSimRels extends AbstractSparkAction {
 				.createDataset(
 					Deduper
 						.computeRelations(sc, blocks, dedupConf)
-						.map(t -> createSimRel(t._1(), t._2(), entity))
+						.map(t -> DedupUtility.createSimRel(t._1(), t._2(), entity))
 						.repartition(numPartitions)
 						.rdd(),
 					Encoders.bean(Relation.class));
@@ -111,24 +112,4 @@ public class SparkCreateSimRels extends AbstractSparkAction {
 		}
 	}
 
-	private Relation createSimRel(String source, String target, String entity) {
-		final Relation r = new Relation();
-		r.setSource(source);
-		r.setTarget(target);
-		r.setSubRelType("dedupSimilarity");
-		r.setRelClass("isSimilarTo");
-		r.setDataInfo(new DataInfo());
-
-		switch (entity) {
-			case "result":
-				r.setRelType("resultResult");
-				break;
-			case "organization":
-				r.setRelType("organizationOrganization");
-				break;
-			default:
-				throw new IllegalArgumentException("unmanaged entity type: " + entity);
-		}
-		return r;
-	}
 }

dhp-workflows/dhp-dedup-openaire/src/main/java/eu/dnetlib/dhp/oa/dedup/SparkWhitelistSimRels.java

@@ -124,31 +124,12 @@ public class SparkWhitelistSimRels extends AbstractSparkAction {
 
 			Dataset<Relation> whiteListSimRels = whiteListRels2
 				.map(
-					(MapFunction<Tuple2<String, String>, Relation>) r -> createSimRel(r._1(), r._2(), entity),
+					(MapFunction<Tuple2<String, String>, Relation>) r -> DedupUtility
+						.createSimRel(r._1(), r._2(), entity),
 					Encoders.bean(Relation.class));
 
 			saveParquet(whiteListSimRels, outputPath, SaveMode.Append);
 		}
 	}
 
-	private Relation createSimRel(String source, String target, String entity) {
-		final Relation r = new Relation();
-		r.setSource(source);
-		r.setTarget(target);
-		r.setSubRelType("dedupSimilarity");
-		r.setRelClass("isSimilarTo");
-		r.setDataInfo(new DataInfo());
-
-		switch (entity) {
-			case "result":
-				r.setRelType("resultResult");
-				break;
-			case "organization":
-				r.setRelType("organizationOrganization");
-				break;
-			default:
-				throw new IllegalArgumentException("unmanaged entity type: " + entity);
-		}
-		return r;
-	}
 }

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 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).distinct
+//    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) {
+//    if (links.nonEmpty) {
-      instance.setUrl(links.asJava)
+//      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/dump/ResultMapper.java

@@ -43,15 +43,6 @@ public class ResultMapper implements Serializable {
 			try {
 
 				addTypeSpecificInformation(out, input, ort);
-				Optional<List<Measure>> mes = Optional.ofNullable(input.getMeasures());
-				if (mes.isPresent()) {
-					List<KeyValue> measure = new ArrayList<>();
-					mes
-						.get()
-						.forEach(
-							m -> m.getUnit().forEach(u -> measure.add(KeyValue.newInstance(m.getId(), u.getValue()))));
-					out.setMeasures(measure);
-				}
 
 				Optional
 					.ofNullable(input.getAuthor())

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

@@ -96,6 +96,21 @@ object SparkResolveRelation {
       .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
@@ -108,14 +123,7 @@ object SparkResolveRelation {
       JField("classid", JString(pidType)) <- qualifier
     } yield (pidValue, pidType)
 
-    val alternateIds: List[(String, String)] = for {
+    (id, result)
-      JObject(pids) <- json \\ "alternateIdentifier"
-      JField("value", JString(pidValue)) <- pids
-      JField("qualifier", JObject(qualifier)) <- pids
-      JField("classid", JString(pidType)) <- qualifier
-    } yield (pidValue, pidType)
-
-    (id, result ::: alternateIds)
   }
 
 
@@ -128,7 +136,7 @@ object SparkResolveRelation {
     source != null
   }
 
-  private def extractPidResolvedTableFromJsonRDD(spark: SparkSession, graphPath: String, workingPath: String) = {
+  def extractPidResolvedTableFromJsonRDD(spark: SparkSession, graphPath: String, workingPath: String) = {
     import spark.implicits._
 
     val d: RDD[(String, String)] = spark.sparkContext.textFile(s"$graphPath/*")

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"$sourcePath/relation").map(s => mapper.readValue(s, classOf[Relation])).filter(r=> r.getSource.startsWith("50") && r.getTarget.startsWith("50"))
+    val relationSemanticFilter = List("cites", "iscitedby","merges", "ismergedin")
+
+    val rddRelation =spark.sparkContext.textFile(s"$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/resources/eu/dnetlib/dhp/oa/graph/resolution/oozie_app/workflow.xml

@@ -1,9 +1,13 @@
-<workflow-app name="Resolve Relation" xmlns="uri:oozie:workflow:0.5">
+<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"/>
@@ -33,8 +37,36 @@
             <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}
+]

dhp-workflows/dhp-graph-mapper/src/test/java/eu/dnetlib/dhp/oa/graph/clean/GraphCleaningFunctionsTest.java

@@ -8,6 +8,7 @@ import java.io.IOException;
 import java.util.Collection;
 import java.util.List;
 import java.util.Set;
+import java.util.stream.Collectors;
 import java.util.stream.Stream;
 
 import org.apache.commons.io.IOUtils;
@@ -137,9 +138,21 @@ public class GraphCleaningFunctionsTest {
 				.stream()
 				.anyMatch(s -> s.getValue().equals("10.1009/qwerty")));
 
+		assertEquals(5, p_out.getTitle().size());
+
 		Publication p_cleaned = GraphCleaningFunctions.cleanup(p_out);
 
-		assertEquals(1, p_cleaned.getTitle().size());
+		assertEquals(3, p_cleaned.getTitle().size());
+
+		List<String> titles = p_cleaned
+			.getTitle()
+			.stream()
+			.map(StructuredProperty::getValue)
+			.collect(Collectors.toList());
+		assertTrue(titles.contains("omic"));
+		assertTrue(
+			titles.contains("Optical response of strained- and unstrained-silicon cold-electron bolometers test"));
+		assertTrue(titles.contains("｢マキャベリ的知性と心の理論の進化論｣ リチャード・バーン， アンドリュー・ホワイトゥン 編／藤田和生， 山下博志， 友永雅巳 監訳"));
 
 		assertEquals("CLOSED", p_cleaned.getBestaccessright().getClassid());
 		assertNull(p_out.getPublisher());

dhp-workflows/dhp-graph-mapper/src/test/java/eu/dnetlib/dhp/oa/graph/dump/DumpJobTest.java

@@ -331,7 +331,6 @@ public class DumpJobTest {
 		Assertions
 			.assertEquals(
 				Constants.accessRightsCoarMap.get(ModelConstants.ACCESS_RIGHT_OPEN), gr.getBestaccessright().getCode());
-		Assertions.assertEquals(null, gr.getBestaccessright().getOpenAccessRoute());
 
 		Assertions.assertEquals("One Ecosystem", gr.getContainer().getName());
 		Assertions.assertEquals("2367-8194", gr.getContainer().getIssnOnline());

dhp-workflows/dhp-graph-mapper/src/test/java/eu/dnetlib/dhp/oa/graph/resolution/ResolveEntitiesTest.scala

@@ -0,0 +1,187 @@
+package eu.dnetlib.dhp.oa.graph.resolution
+
+
+import com.fasterxml.jackson.databind.ObjectMapper
+import eu.dnetlib.dhp.schema.common.EntityType
+import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils
+import eu.dnetlib.dhp.schema.oaf.{Result, StructuredProperty}
+import org.apache.commons.io.FileUtils
+import org.apache.spark.SparkConf
+import org.apache.spark.sql._
+import org.junit.jupiter.api.Assertions._
+import org.junit.jupiter.api.TestInstance.Lifecycle
+import org.junit.jupiter.api.{AfterAll, BeforeAll, Test, TestInstance}
+
+import java.nio.file.{Files, Path}
+import scala.collection.JavaConverters._
+import scala.io.Source
+
+@TestInstance(Lifecycle.PER_CLASS)
+class ResolveEntitiesTest extends Serializable {
+
+  var workingDir:Path = null
+
+  val FAKE_TITLE = "FAKETITLE"
+  val FAKE_SUBJECT = "FAKESUBJECT"
+
+  var sparkSession:Option[SparkSession] = None
+
+
+  @BeforeAll
+  def setUp() :Unit = {
+    workingDir = Files.createTempDirectory(getClass.getSimpleName)
+
+    val conf = new SparkConf()
+    sparkSession = Some(SparkSession
+      .builder()
+      .config(conf)
+      .appName(getClass.getSimpleName)
+      .master("local[*]").getOrCreate())
+    populateDatasets(sparkSession.get)
+    generateUpdates(sparkSession.get)
+
+  }
+
+
+  @AfterAll
+  def tearDown():Unit = {
+    FileUtils.deleteDirectory(workingDir.toFile)
+    sparkSession.get.stop()
+
+
+  }
+
+
+  def generateUpdates(spark:SparkSession):Unit = {
+    val template = Source.fromInputStream(this.getClass.getResourceAsStream("updates")).mkString
+
+
+    val pids:List[String] = template.lines.map{id =>
+      val r = new Result
+      r.setId(id.toLowerCase.trim)
+      r.setSubject(List(OafMapperUtils.structuredProperty(FAKE_SUBJECT, OafMapperUtils.qualifier("fos","fosCS", "fossSchema", "fossiFIgo"), null)).asJava)
+      r.setTitle(List(OafMapperUtils.structuredProperty(FAKE_TITLE, OafMapperUtils.qualifier("fos","fosCS", "fossSchema", "fossiFIgo"), null)).asJava)
+      r
+    }.map{r =>
+      val mapper = new ObjectMapper()
+
+      mapper.writeValueAsString(r)}.toList
+
+
+    val sc =spark.sparkContext
+
+    println(sc.parallelize(pids).count())
+
+    spark.createDataset(sc.parallelize(pids))(Encoders.STRING).write.mode(SaveMode.Overwrite).option("compression", "gzip").text(s"$workingDir/updates")
+
+
+
+
+
+    import spark.implicits._
+    implicit val resEncoder: Encoder[Result] = Encoders.bean(classOf[Result])
+    val ds = spark.read.text(s"$workingDir/updates").as[String].map{s => val mapper = new ObjectMapper()
+     mapper.readValue(s, classOf[Result])}.collect()
+
+
+
+
+    assertEquals(4, ds.length)
+    ds.foreach{r => assertNotNull(r.getSubject)}
+    ds.foreach{r => assertEquals(1,r.getSubject.size())}
+    ds.foreach{r => assertNotNull(r.getTitle)}
+    ds.foreach{r => assertEquals(1,r.getTitle.size())}
+
+
+
+    ds.flatMap(r => r.getTitle.asScala.map(t => t.getValue)).foreach(t => assertEquals(FAKE_TITLE,t))
+    ds.flatMap(r => r.getSubject.asScala.map(t => t.getValue)).foreach(t => assertEquals(FAKE_SUBJECT,t))
+
+    println("generated Updates")
+  }
+
+
+  def populateDatasets(spark:SparkSession):Unit = {
+    import spark.implicits._
+    val entities =SparkResolveEntities.entities
+
+    entities.foreach{
+      e =>
+        val template = Source.fromInputStream(this.getClass.getResourceAsStream(s"$e")).mkString
+        spark.createDataset(spark.sparkContext.parallelize(template.lines.toList)).as[String].write.option("compression", "gzip").text(s"$workingDir/graph/$e")
+        println(s"Created Dataset $e")
+    }
+    SparkResolveRelation.extractPidResolvedTableFromJsonRDD(spark, s"$workingDir/graph", s"$workingDir/work")
+
+  }
+
+
+  @Test
+  def testResolution():Unit = {
+    val spark:SparkSession = sparkSession.get
+    implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
+    SparkResolveEntities.resolveEntities(spark,s"$workingDir/work", s"$workingDir/updates" )
+
+    val ds = spark.read.load(s"$workingDir/work/resolvedEntities").as[Result]
+
+    assertEquals(3, ds.count())
+
+    ds.collect().foreach{
+      r =>
+      assertTrue(r.getId.startsWith("50"))
+    }
+  }
+
+
+
+
+  private def structuredPContainsValue(l:java.util.List[StructuredProperty], exptectedValue:String):Boolean = {
+    l.asScala.exists(p =>p.getValue!= null && p.getValue.equalsIgnoreCase(exptectedValue))
+  }
+
+  @Test
+  def testUpdate():Unit = {
+    val spark:SparkSession = sparkSession.get
+    import spark.implicits._
+    implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
+    val m = new ObjectMapper()
+    SparkResolveEntities.resolveEntities(spark,s"$workingDir/work", s"$workingDir/updates" )
+    SparkResolveEntities.generateResolvedEntities(spark,s"$workingDir/work",s"$workingDir/graph" )
+
+
+
+    val pubDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/publication").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.publication))
+    val t  = pubDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
+
+
+
+    val datDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/dataset").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.dataset))
+    val td  = datDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
+
+
+    val softDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/software").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.software))
+    val ts  = softDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
+
+
+    val orpDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/otherresearchproduct").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.otherresearchproduct))
+    val to  = orpDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
+
+
+    assertEquals(0, t)
+    assertEquals(2, td)
+    assertEquals(1, ts)
+    assertEquals(0, to)
+
+  }
+
+
+
+
+
+
+
+
+
+
+
+}

dhp-workflows/dhp-graph-mapper/src/test/resources/eu/dnetlib/dhp/oa/graph/clean/result.json

@@ -864,7 +864,7 @@
         "schemeid": "dnet:dataCite_title",
         "schemename": "dnet:dataCite_title"
       },
-      "value": "Optical response of strained- and unstrained-silicon cold-electron bolometers"
+      "value": "Optical response of strained- and unstrained-silicon cold-electron bolometers test"
     },
     {
       "dataInfo": {
@@ -887,6 +887,72 @@
         "schemename": "dnet:dataCite_title"
       },
       "value": "test test 123 test"
+    },
+    {
+      "dataInfo": {
+        "deletedbyinference": false,
+        "inferenceprovenance": "",
+        "inferred": false,
+        "invisible": false,
+        "provenanceaction": {
+          "classid": "sysimport:crosswalk:datasetarchive",
+          "classname": "sysimport:crosswalk:datasetarchive",
+          "schemeid": "dnet:provenanceActions",
+          "schemename": "dnet:provenanceActions"
+        },
+        "trust": "0.9"
+      },
+      "qualifier": {
+        "classid": "main title",
+        "classname": "main title",
+        "schemeid": "dnet:dataCite_title",
+        "schemename": "dnet:dataCite_title"
+      },
+      "value": "omic"
+    },
+    {
+      "dataInfo": {
+        "deletedbyinference": false,
+        "inferenceprovenance": "",
+        "inferred": false,
+        "invisible": false,
+        "provenanceaction": {
+          "classid": "sysimport:crosswalk:datasetarchive",
+          "classname": "sysimport:crosswalk:datasetarchive",
+          "schemeid": "dnet:provenanceActions",
+          "schemename": "dnet:provenanceActions"
+        },
+        "trust": "0.9"
+      },
+      "qualifier": {
+        "classid": "main title",
+        "classname": "main title",
+        "schemeid": "dnet:dataCite_title",
+        "schemename": "dnet:dataCite_title"
+      },
+      "value": "｢マキャベリ的知性と心の理論の進化論｣ リチャード・バーン， アンドリュー・ホワイトゥン 編／藤田和生， 山下博志， 友永雅巳 監訳"
+    },
+    {
+      "dataInfo": {
+        "deletedbyinference": false,
+        "inferenceprovenance": "",
+        "inferred": false,
+        "invisible": false,
+        "provenanceaction": {
+          "classid": "sysimport:crosswalk:datasetarchive",
+          "classname": "sysimport:crosswalk:datasetarchive",
+          "schemeid": "dnet:provenanceActions",
+          "schemename": "dnet:provenanceActions"
+        },
+        "trust": "0.9"
+      },
+      "qualifier": {
+        "classid": "main title",
+        "classname": "main title",
+        "schemeid": "dnet:dataCite_title",
+        "schemename": "dnet:dataCite_title"
+      },
+      "value": "-"
     }
   ]
 }

dhp-workflows/dhp-graph-mapper/src/test/resources/eu/dnetlib/dhp/oa/graph/resolution/updates

@@ -0,0 +1,4 @@
+unresolved::10.17026/dans-x3z-fsq5::doi
+unresolved::10.17026/dans-xsw-qtnx::doi
+unresolved::10.5281/zenodo.1473694::doi
+unresolved::10.17632/fake::doi

dhp-workflows/dhp-stats-update/src/main/resources/eu/dnetlib/dhp/oa/graph/stats/oozie_app/scripts/step20-createMonitorDB.sql

@@ -11,7 +11,7 @@ create view if not exists TARGET.funder as select * from SOURCE.funder;
 create view if not exists TARGET.fundref as select * from SOURCE.fundref;
 create view if not exists TARGET.rndexpenditure as select * from SOURCE.rndexpediture;
 
-create table TARGET.result as
+create table TARGET.result stored as parquet as
     select distinct * from (
         select * from SOURCE.result r where exists (select 1 from SOURCE.result_projects rp join SOURCE.project p on rp.project=p.id where rp.id=r.id)
         union all
@@ -21,61 +21,62 @@ create table TARGET.result as
             'openorgs____::759d59f05d77188faee99b7493b46805',
             'openorgs____::b84450f9864182c67b8611b5593f4250',
             'openorgs____::d41cf6bd4ab1b1362a44397e0b95c975',
-            'openorgs____::eadc8da90a546e98c03f896661a2e4d4') )) foo;
+            'openorgs____::eadc8da90a546e98c03f896661a2e4d4',
+            'openorgs____::d2a09b9d5eabb10c95f9470e172d05d2') )) foo;
 compute stats TARGET.result;
 
-create table TARGET.result_citations as select * from SOURCE.result_citations orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_citations stored as parquet as select * from SOURCE.result_citations orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_citations;
 
-create table TARGET.result_classifications as select * from SOURCE.result_classifications orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_classifications stored as parquet as select * from SOURCE.result_classifications orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_classifications;
 
-create table TARGET.result_concepts as select * from SOURCE.result_concepts orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_concepts stored as parquet as select * from SOURCE.result_concepts orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_concepts;
 
-create table TARGET.result_datasources as select * from SOURCE.result_datasources orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_datasources stored as parquet as select * from SOURCE.result_datasources orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_datasources;
 
-create table TARGET.result_fundercount as select * from SOURCE.result_fundercount orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_fundercount stored as parquet as select * from SOURCE.result_fundercount orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_fundercount;
 
-create table TARGET.result_gold as select * from SOURCE.result_gold orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_gold stored as parquet as select * from SOURCE.result_gold orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_gold;
 
-create table TARGET.result_greenoa as select * from SOURCE.result_greenoa orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_greenoa stored as parquet as select * from SOURCE.result_greenoa orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_greenoa;
 
-create table TARGET.result_languages as select * from SOURCE.result_languages orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_languages stored as parquet as select * from SOURCE.result_languages orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_languages;
 
-create table TARGET.result_licences as select * from SOURCE.result_licenses orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_licences stored as parquet as select * from SOURCE.result_licenses orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_licences;
 
-create table TARGET.result_oids as select * from SOURCE.result_oids orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_oids stored as parquet as select * from SOURCE.result_oids orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_oids;
 
-create table TARGET.result_organization as select * from SOURCE.result_organization orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_organization stored as parquet as select * from SOURCE.result_organization orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_organization;
 
-create table TARGET.result_peerreviewed as select * from SOURCE.result_peerreviewed orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_peerreviewed stored as parquet as select * from SOURCE.result_peerreviewed orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_peerreviewed;
 
-create table TARGET.result_pids as select * from SOURCE.result_pids orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_pids stored as parquet as select * from SOURCE.result_pids orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_pids;
 
-create table TARGET.result_projectcount as select * from SOURCE.result_projectcount orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_projectcount stored as parquet as select * from SOURCE.result_projectcount orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_projectcount;
 
-create table TARGET.result_projects as select * from SOURCE.result_projects orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_projects stored as parquet as select * from SOURCE.result_projects orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_projects;
 
-create table TARGET.result_refereed as select * from SOURCE.result_refereed orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_refereed stored as parquet as select * from SOURCE.result_refereed orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_refereed;
 
-create table TARGET.result_sources as select * from SOURCE.result_sources orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_sources stored as parquet as select * from SOURCE.result_sources orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_sources;
 
-create table TARGET.result_topics as select * from SOURCE.result_topics orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.result_topics stored as parquet as select * from SOURCE.result_topics orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.result_topics;
 
 -- datasources
@@ -84,7 +85,7 @@ create view if not exists TARGET.datasource_oids as select * from SOURCE.datasou
 create view if not exists TARGET.datasource_organizations as select * from SOURCE.datasource_organizations;
 create view if not exists TARGET.datasource_sources as select * from SOURCE.datasource_sources;
 
-create table TARGET.datasource_results as select id as result, datasource as id from TARGET.result_datasources;
+create table TARGET.datasource_results stored as parquet as select id as result, datasource as id from TARGET.result_datasources;
 compute stats TARGET.datasource_results;
 
 -- organizations
@@ -100,7 +101,7 @@ create view if not exists TARGET.project_oids as select * from SOURCE.project_oi
 create view if not exists TARGET.project_organizations as select * from SOURCE.project_organizations;
 create view if not exists TARGET.project_resultcount as select * from SOURCE.project_resultcount;
 
-create table TARGET.project_results as select id as result, project as id from TARGET.result_projects;
+create table TARGET.project_results stored as parquet as select id as result, project as id from TARGET.result_projects;
 compute stats TARGET.project_results;
 
 -- indicators
@@ -121,19 +122,19 @@ create view TARGET.indi_pub_avg_year_content_oa as select * from SOURCE.indi_pub
 create view TARGET.indi_pub_avg_year_context_oa as select * from SOURCE.indi_pub_avg_year_context_oa orig;
 create view TARGET.indi_pub_avg_year_country_oa as select * from SOURCE.indi_pub_avg_year_country_oa orig;
 
-create table TARGET.indi_pub_green_oa as select * from SOURCE.indi_pub_green_oa orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.indi_pub_green_oa stored as parquet as select * from SOURCE.indi_pub_green_oa orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.indi_pub_green_oa;
-create table TARGET.indi_pub_grey_lit as select * from SOURCE.indi_pub_grey_lit orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.indi_pub_grey_lit stored as parquet as select * from SOURCE.indi_pub_grey_lit orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.indi_pub_grey_lit;
-create table TARGET.indi_pub_doi_from_crossref as select * from SOURCE.indi_pub_doi_from_crossref orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.indi_pub_doi_from_crossref stored as parquet as select * from SOURCE.indi_pub_doi_from_crossref orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.indi_pub_doi_from_crossref;
-create table TARGET.indi_pub_gold_oa as select * from SOURCE.indi_pub_gold_oa orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.indi_pub_gold_oa stored as parquet as select * from SOURCE.indi_pub_gold_oa orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.indi_pub_gold_oa;
-create table TARGET.indi_pub_has_abstract as select * from SOURCE.indi_pub_has_abstract orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.indi_pub_has_abstract stored as parquet as select * from SOURCE.indi_pub_has_abstract orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.indi_pub_has_abstract;
-create table TARGET.indi_pub_has_cc_licence as select * from SOURCE.indi_pub_has_cc_licence orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.indi_pub_has_cc_licence stored as parquet as select * from SOURCE.indi_pub_has_cc_licence orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.indi_pub_has_cc_licence;
-create table TARGET.indi_pub_has_cc_licence_url as select * from SOURCE.indi_pub_has_cc_licence_url orig where exists (select 1 from TARGET.result r where r.id=orig.id);
+create table TARGET.indi_pub_has_cc_licence_url stored as parquet as select * from SOURCE.indi_pub_has_cc_licence_url orig where exists (select 1 from TARGET.result r where r.id=orig.id);
 compute stats TARGET.indi_pub_has_cc_licence_url;
 
 create view TARGET.indi_software_avg_year_content_oa as select * from SOURCE.indi_software_avg_year_content_oa orig;
@@ -143,15 +144,15 @@ create view TARGET.indi_software_avg_year_country_oa as select * from SOURCE.ind
 --denorm
 alter table TARGET.result rename to TARGET.res_tmp;
 
-create table TARGET.result_denorm as
+create table TARGET.result_denorm stored as parquet as
     select distinct r.*, rp.project, p.acronym as pacronym, p.title as ptitle, p.funder as pfunder, p.funding_lvl0 as pfunding_lvl0, rd.datasource, d.name as dname, d.type as dtype
     from TARGET.res_tmp r
-    join TARGET.result_projects rp on rp.id=r.id
+    left outer join TARGET.result_projects rp on rp.id=r.id
-    join TARGET.result_datasources rd on rd.id=r.id
+    left outer join TARGET.result_datasources rd on rd.id=r.id
-    join TARGET.project p on p.id=rp.project
+    left outer join TARGET.project p on p.id=rp.project
-    join TARGET.datasource d on d.id=rd.datasource;
+    left outer join TARGET.datasource d on d.id=rd.datasource;
 compute stats TARGET.result_denorm;
 
 alter table TARGET.result_denorm rename to TARGET.result;
 drop table TARGET.res_tmp;
---- done!
+--- done!

dhp-workflows/dhp-stats-update/src/main/resources/eu/dnetlib/dhp/oa/graph/stats/oozie_app/scripts/step7.sql

@@ -126,7 +126,7 @@ FROM ${stats_db_name}.otherresearchproduct_topics;
 CREATE TABLE ${stats_db_name}.result_organization AS
 SELECT substr(r.target, 4) AS id, substr(r.source, 4) AS organization
 FROM ${openaire_db_name}.relation r
-WHERE r.reltype = 'resultOrganization' and r.relclass='hasAuthorInstitution' and r.subreltype='affiliation'
+WHERE r.reltype = 'resultOrganization'
   and r.datainfo.deletedbyinference = false;
 
 CREATE TABLE ${stats_db_name}.result_projects AS

pom.xml

@@ -550,7 +550,7 @@
 				<plugin>
 					<groupId>org.apache.maven.plugins</groupId>
 					<artifactId>maven-site-plugin</artifactId>
-					<version>3.7.1</version>
+					<version>3.9.1</version>
 				</plugin>
 
 				<plugin>
@@ -753,7 +753,7 @@
 		<mockito-core.version>3.3.3</mockito-core.version>
 		<mongodb.driver.version>3.4.2</mongodb.driver.version>
 		<vtd.version>[2.12,3.0)</vtd.version>
-		<dhp-schemas.version>[2.8.21]</dhp-schemas.version>
+		<dhp-schemas.version>[2.8.22]</dhp-schemas.version>
 		<dnet-actionmanager-api.version>[4.0.3]</dnet-actionmanager-api.version>
 		<dnet-actionmanager-common.version>[6.0.5]</dnet-actionmanager-common.version>
 		<dnet-openaire-broker-common.version>[3.1.6]</dnet-openaire-broker-common.version>