Merge pull request 'PR: Bypass Action Set' (#157) from bypass_acstionset into beta

Reviewed-on: D-Net/dnet-hadoop#157
This commit is contained in:
Claudio Atzori 2021-11-12 12:01:05 +01:00
commit 7b81607035
22 changed files with 1627 additions and 3 deletions

View File

@ -0,0 +1,50 @@
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));
}
}

View File

@ -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);
}
}
}

View File

@ -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 eu.dnetlib.dhp.utils.DHPUtils;
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;
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());
}
}

View File

@ -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 eu.dnetlib.dhp.utils.DHPUtils;
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;
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;
}
}

View File

@ -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);
}
}

View File

@ -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);
}
}

View File

@ -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;
}
}

View File

@ -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;
}
}

View File

@ -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;
}
}

View File

@ -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;
}
}

View File

@ -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
}
]

View File

@ -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>

View File

@ -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>

View File

@ -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
}
]

View File

@ -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
}
]

View File

@ -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"));
}
}

View File

@ -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());
}
}

View File

@ -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"}]}]}

View File

@ -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"}

View File

@ -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
1 dedup_wf_001::ddcc7a56fa13e49bcc59c6bdd19ad26c 10.3390/s18072310 engineering and technology nano-technology nanoscience & nanotechnology
2 dedup_wf_001::b76062d56e28224eac56111a4e1e5ecf 10.1111/1365-2656.1283110.17863/cam.24369 social sciences psychology and cognitive sciences NULL
3 dedup_wf_001::bb752acb8f403a25fa7851a302f7b7ac 10.3929/ethz-b-00018758410.1002/chem.201701644 natural sciences NULL NULL
4 dedup_wf_001::2f1435a9201ecf5cbbcb12c9b2d971cd 10.1080/01913123.2017.1367361 medical and health sciences clinical medicine oncology & carcinogenesis
5 dedup_wf_001::fc9e47ec16c67b101724320d4b030514 10.1051/e3sconf/20199207011 natural sciences earth and related environmental sciences environmental sciences
6 dedup_wf_001::caa1e5b4de387cb31751552f4f0f5d72 10.1038/onc.2015.333 medical and health sciences clinical medicine oncology & carcinogenesis
7 dedup_wf_001::c2a98df5637d69bf0524eaf40fe6bf11 10.1093/mnras/staa256 natural sciences physical sciences NULL
8 dedup_wf_001::c221262bdc77cbfd59859a402f0e3991 10.1016/j.jclepro.2018.07.166 engineering and technology other engineering and technologies building & construction
9 doiboost____::d56d9dc21f317b3e009d5b6c8ea87212 10.1103/physrevlett.125.037403 natural sciences physical sciences nuclear & particles physics
10 dedup_wf_001::8a7269c8ee6470b2fb4fd384bc389e08 10.1080/03602532.2017.1316285 natural sciences NULL NULL
11 dedup_wf_001::28342ebbc19833e4e1f4a2b23cf5ee20 10.1001/jamanetworkopen.2019.1868 medical and health sciences other medical science health policy & services
12 dedup_wf_001::c1e1daf2b55dd9ec8e1c7c7458bbc7bc 10.1128/mra.00874-18 natural sciences biological sciences plant biology & botany
13 dedup_wf_001::a2ef4a2720c71907180750e5871298ef 10.1016/j.nancom.2018.03.001 engineering and technology NULL NULL
14 dedup_wf_001::676f46a31519e83a89efcb1c626286fb 10.1112/topo.12174 natural sciences NULL NULL
15 dedup_wf_001::6f2761642f1e39313388e2c4060657dd 10.12688/wellcomeopenres.15846.1 medical and health sciences health sciences NULL
16 dedup_wf_001::e414c1dec599521a9635a60de0f6755b 10.21468/scipostphys.3.1.001 natural sciences physical sciences NULL
17 dedup_wf_001::f3395fe0f330164ea424dc61c86c9a3d 10.1088/1741-4326/ab6c77 natural sciences physical sciences nuclear & particles physics
18 dedup_wf_001::a4f32a97a783117012f1de11797e73f2 10.1109/tpwrs.2019.2944747 engineering and technology electrical engineering, electronic engineering, information engineering electrical & electronic engineering
19 dedup_wf_001::313ae1cd083ae1696d12dd1909f97df8 10.1016/j.expthermflusci.2019.10999410.17863/cam.46212 engineering and technology mechanical engineering mechanical engineering & transports
20 dedup_wf_001::2a300a7d3ca7347791ebcef986bc0682 10.1109/tc.2018.2860012 engineering and technology electrical engineering, electronic engineering, information engineering computer hardware & architecture
21 doiboost____::5b79bd7bd9f87361b4a4abc3cbb2df75 10.1002/mma.6622 natural sciences mathematics numerical & computational mathematics
22 dedup_wf_001::6a3f61f217a2519fbaddea1094e3bfc2 10.1051/radiopro/2020020 natural sciences chemical sciences NULL
23 dedup_wf_001::a3f0430309a639f4234a0e57b10f2dee 10.1007/s12268-019-1003-4 medical and health sciences basic medicine NULL
24 dedup_wf_001::b6b8a3a1cccbee459cf3343485efdb12 10.3390/cancers12010236 medical and health sciences health sciences biochemistry & molecular biology
25 dedup_wf_001::dd06ee7974730e7b09a4f03c83b3f9bd 10.6084/m9.figshare.991261410.6084/m9.figshare.9912614.v110.1080/00268976.2019.1665199 natural sciences chemical sciences physical chemistry
26 dedup_wf_001::027c78bef6f972b5e26dfea55d30fbe3 10.1175/jpo-d-17-0239.1 natural sciences biological sciences marine biology & hydrobiology
27 dedup_wf_001::43edc179aa9e1fbaf582c5203b18b519 10.1007/s13218-020-00674-7 engineering and technology industrial biotechnology industrial engineering & automation
28 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
29 dedup_wf_001::80bc15d69bdc589149631f3439dde5aa 10.1109/ted.2018.2813542 engineering and technology electrical engineering, electronic engineering, information engineering electrical & electronic engineering
30 dedup_wf_001::42c1cfa33e7872944b920cff90f4d99e 10.3989/scimar.04739.25a natural sciences biological sciences NULL
31 dedup_wf_001::9bacdbbaa9da3658b7243d5de8e3ce14 10.3390/su12187503 natural sciences earth and related environmental sciences NULL
32 dedup_wf_001::59e43d3527dcfecb6097fbd5740c8950 10.1016/j.ccell.2018.08.017 medical and health sciences basic medicine biochemistry & molecular biology
33 doiboost____::e024d1b738df3b24bc58fa0228542571 10.1103/physrevresearch.2.023322 natural sciences physical sciences nuclear & particles physics
34 dedup_wf_001::66e9a3237fa8178886d26d3c2d5b9e66 10.1039/c8cp03234c natural sciences NULL NULL
35 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
36 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
37 dedup_wf_001::14ba594e8fd081847bc3f50f56335003 10.1016/j.jclepro.2019.119065 engineering and technology other engineering and technologies building & construction
38 dedup_wf_001::08ac7b33a41bcea2d055ecd8585d632e 10.1111/pce.13392 agricultural and veterinary sciences agriculture, forestry, and fisheries agronomy & agriculture

View File

@ -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;

View File

@ -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());