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Merge pull request 'doidoost_dismiss' (#418) from doidoost_dismiss into beta 

Reviewed-on: D-Net/dnet-hadoop#418
This commit is contained in:
Claudio Atzori 2024-04-17 12:01:11 +02:00
parent 0db7e4ae9a ac8747582c
commit b554c41cc7
34 changed files with 14712 additions and 2185 deletions
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24
dhp-common/src/main/java/eu/dnetlib/dhp/schema/oaf/utils/DoiCleaningRule.java
View File

@ -1,6 +1,8 @@
package eu.dnetlib.dhp.schema.oaf.utils; package eu.dnetlib.dhp.schema.oaf.utils;
import org.apache.commons.lang3.StringUtils;
public class DoiCleaningRule { public class DoiCleaningRule {
public static String clean(final String doi) { public static String clean(final String doi) {
@ -11,4 +13,26 @@ public class DoiCleaningRule {
.replaceFirst(CleaningFunctions.DOI_PREFIX_REGEX, CleaningFunctions.DOI_PREFIX); .replaceFirst(CleaningFunctions.DOI_PREFIX_REGEX, CleaningFunctions.DOI_PREFIX);
} }
public static String normalizeDoi(final String input) {
if (input == null)
return null;
final String replaced = input
.replaceAll("\\n|\\r|\\t|\\s", "")
.toLowerCase()
.replaceFirst(CleaningFunctions.DOI_PREFIX_REGEX, CleaningFunctions.DOI_PREFIX);
if (StringUtils.isEmpty(replaced))
return null;
if (!replaced.contains("10."))
return null;
final String ret = replaced.substring(replaced.indexOf("10."));
if (!ret.startsWith(CleaningFunctions.DOI_PREFIX))
return null;
return ret;
}
} }

12
dhp-common/src/main/scala/eu/dnetlib/dhp/application/SparkScalaApplication.scala
View File

@ -1,5 +1,8 @@
package eu.dnetlib.dhp.application package eu.dnetlib.dhp.application
import eu.dnetlib.dhp.common.Constants
import eu.dnetlib.dhp.utils.DHPUtils.writeHdfsFile
import scala.io.Source import scala.io.Source
/** This is the main Interface SparkApplication /** This is the main Interface SparkApplication
@ -70,4 +73,13 @@ abstract class AbstractScalaApplication(
.getOrCreate() .getOrCreate()
} }
def reportTotalSize(targetPath: String, outputBasePath: String): Unit = {
val total_items = spark.read.text(targetPath).count()
writeHdfsFile(
spark.sparkContext.hadoopConfiguration,
s"$total_items",
outputBasePath + Constants.MDSTORE_SIZE_PATH
)
}
} }

32
dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/collection/crossref/convert_crossref_dump_to_oaf_params.json Normal file
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@ -0,0 +1,32 @@
[
{
"paramName": "m",
"paramLongName": "master",
"paramDescription": "the master name",
"paramRequired": true
},
{
"paramName": "s",
"paramLongName": "sourcePath",
"paramDescription": "The base path of Crossref DUMP",
"paramRequired": true
},
{
"paramName": "uw",
"paramLongName": "unpaywallPath",
"paramDescription": "The base path of unpaywall DUMP",
"paramRequired": true
},
{
"paramName": "mov",
"paramLongName": "mdstoreOutputVersion",
"paramDescription": "The mdstore Output Version",
"paramRequired": false
},
{
"paramName": "i",
"paramLongName": "isLookupUrl",
"paramDescription": "the Information System Service LookUp URL",
"paramRequired": true
}
]

916
dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/collection/crossref/irish_funder.json Normal file
View File

@ -0,0 +1,916 @@
[
{
"id": "100007630",
"uri": "http://dx.doi.org/10.13039/100007630",
"name": "College of Engineering and Informatics, National University of Ireland, Galway",
"synonym": []
},
{
"id": "100007731",
"uri": "http://dx.doi.org/10.13039/100007731",
"name": "Endo International",
"synonym": []
},
{
"id": "100008099",
"uri": "http://dx.doi.org/10.13039/100008099",
"name": "Food Safety Authority of Ireland",
"synonym": []
},
{
"id": "100008124",
"uri": "http://dx.doi.org/10.13039/100008124",
"name": "Department of Jobs, Enterprise and Innovation",
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{
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"name": "Department of Foreign Affairs and Trade, Ireland",
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{
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"uri": "http://dx.doi.org/10.13039/100009099",
"name": "Irish Aid",
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"uri": "http://dx.doi.org/10.13039/100009770",
"name": "National University of Ireland",
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{
"id": "501100018839",
"uri": "http://dx.doi.org/10.13039/501100018839",
"name": "Irish Centre for High-End Computing",
"synonym": []
},
{
"id": "501100019905",
"uri": "http://dx.doi.org/10.13039/501100019905",
"name": "Galway University Foundation",
"synonym": []
},
{
"id": "501100020036",
"uri": "http://dx.doi.org/10.13039/501100020036",
"name": "Dystonia Ireland",
"synonym": []
},
{
"id": "501100020221",
"uri": "http://dx.doi.org/10.13039/501100020221",
"name": "Irish Motor Neurone Disease Association",
"synonym": []
},
{
"id": "501100020270",
"uri": "http://dx.doi.org/10.13039/501100020270",
"name": "Advanced Materials and Bioengineering Research",
"synonym": []
},
{
"id": "501100020403",
"uri": "http://dx.doi.org/10.13039/501100020403",
"name": "Irish Composites Centre",
"synonym": []
},
{
"id": "501100020425",
"uri": "http://dx.doi.org/10.13039/501100020425",
"name": "Irish Thoracic Society",
"synonym": []
},
{
"id": "501100021102",
"uri": "http://dx.doi.org/10.13039/501100021102",
"name": "Waterford Institute of Technology",
"synonym": []
},
{
"id": "501100021110",
"uri": "http://dx.doi.org/10.13039/501100021110",
"name": "Irish MPS Society",
"synonym": []
},
{
"id": "501100021525",
"uri": "http://dx.doi.org/10.13039/501100021525",
"name": "Insight SFI Research Centre for Data Analytics",
"synonym": []
},
{
"id": "501100021694",
"uri": "http://dx.doi.org/10.13039/501100021694",
"name": "Elan Pharma International",
"synonym": []
},
{
"id": "501100021838",
"uri": "http://dx.doi.org/10.13039/501100021838",
"name": "Royal College of Physicians of Ireland",
"synonym": []
},
{
"id": "501100022542",
"uri": "http://dx.doi.org/10.13039/501100022542",
"name": "Breakthrough Cancer Research",
"synonym": []
},
{
"id": "501100022610",
"uri": "http://dx.doi.org/10.13039/501100022610",
"name": "Breast Cancer Ireland",
"synonym": []
},
{
"id": "501100022728",
"uri": "http://dx.doi.org/10.13039/501100022728",
"name": "Munster Technological University",
"synonym": []
},
{
"id": "501100022729",
"uri": "http://dx.doi.org/10.13039/501100022729",
"name": "Institute of Technology, Tralee",
"synonym": []
},
{
"id": "501100023273",
"uri": "http://dx.doi.org/10.13039/501100023273",
"name": "HRB Clinical Research Facility Galway",
"synonym": []
},
{
"id": "501100023378",
"uri": "http://dx.doi.org/10.13039/501100023378",
"name": "Lauritzson Foundation",
"synonym": []
},
{
"id": "501100023551",
"uri": "http://dx.doi.org/10.13039/501100023551",
"name": "Cystic Fibrosis Ireland",
"synonym": []
},
{
"id": "501100023970",
"uri": "http://dx.doi.org/10.13039/501100023970",
"name": "Tyndall National Institute",
"synonym": []
},
{
"id": "501100024094",
"uri": "http://dx.doi.org/10.13039/501100024094",
"name": "Raidi\u00f3 Teilif\u00eds \u00c9ireann",
"synonym": []
},
{
"id": "501100024242",
"uri": "http://dx.doi.org/10.13039/501100024242",
"name": "Synthesis and Solid State Pharmaceutical Centre",
"synonym": []
},
{
"id": "501100024313",
"uri": "http://dx.doi.org/10.13039/501100024313",
"name": "Irish Rugby Football Union",
"synonym": []
},
{
"id": "100007490",
"uri": "http://dx.doi.org/10.13039/100007490",
"name": "Bausch and Lomb Ireland",
"synonym": []
},
{
"id": "100007819",
"uri": "http://dx.doi.org/10.13039/100007819",
"name": "Allergan",
"synonym": []
},
{
"id": "100010547",
"uri": "http://dx.doi.org/10.13039/100010547",
"name": "Irish Youth Justice Service",
"synonym": []
},
{
"id": "100012733",
"uri": "http://dx.doi.org/10.13039/100012733",
"name": "National Parks and Wildlife Service",
"synonym": []
},
{
"id": "100015278",
"uri": "http://dx.doi.org/10.13039/100015278",
"name": "Pfizer Healthcare Ireland",
"synonym": []
},
{
"id": "100017144",
"uri": "http://dx.doi.org/10.13039/100017144",
"name": "Shell E and P Ireland",
"synonym": []
},
{
"id": "100022895",
"uri": "http://dx.doi.org/10.13039/100022895",
"name": "Health Research Institute, University of Limerick",
"synonym": []
},
{
"id": "501100001599",
"uri": "http://dx.doi.org/10.13039/501100001599",
"name": "National Council for Forest Research and Development",
"synonym": []
},
{
"id": "501100006554",
"uri": "http://dx.doi.org/10.13039/501100006554",
"name": "IDA Ireland",
"synonym": []
},
{
"id": "501100011626",
"uri": "http://dx.doi.org/10.13039/501100011626",
"name": "Energy Policy Research Centre, Economic and Social Research Institute",
"synonym": []
},
{
"id": "501100014531",
"uri": "http://dx.doi.org/10.13039/501100014531",
"name": "Physical Education and Sport Sciences Department, University of Limerick",
"synonym": []
},
{
"id": "501100014745",
"uri": "http://dx.doi.org/10.13039/501100014745",
"name": "APC Microbiome Institute",
"synonym": []
},
{
"id": "501100014826",
"uri": "http://dx.doi.org/10.13039/501100014826",
"name": "ADAPT - Centre for Digital Content Technology",
"synonym": []
},
{
"id": "501100020570",
"uri": "http://dx.doi.org/10.13039/501100020570",
"name": "College of Medicine, Nursing and Health Sciences, National University of Ireland, Galway",
"synonym": []
},
{
"id": "501100020871",
"uri": "http://dx.doi.org/10.13039/501100020871",
"name": "Bernal Institute, University of Limerick",
"synonym": []
},
{
"id": "501100023852",
"uri": "http://dx.doi.org/10.13039/501100023852",
"name": "Moore Institute for Research in the Humanities and Social Studies, University of Galway",
"synonym": []
}
]

44
dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/collection/crossref/oozie_app/config-default.xml Normal file
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<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>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</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>spark2YarnHistoryServerAddress</name>
<value>http://iis-cdh5-test-gw.ocean.icm.edu.pl:18089 </value>
</property>
<property>
<name>spark2EventLogDir</name>
<value>/user/spark/spark2ApplicationHistory</value>
</property>
</configuration>

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dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/collection/crossref/oozie_app/workflow.xml Normal file
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<workflow-app name="generate_crossref_Datasource" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>sourcePath</name>
<description>The base path of Crossref DUMP </description>
</property>
<property>
<name>unpaywallPath</name>
<description>The base path of unpaywall DUMP </description>
</property>
<property>
<name>isLookupUrl</name>
<description>The Information service Lookup URL</description>
</property>
<property>
<name>mdStoreOutputId</name>
<description>the identifier of the cleaned MDStore</description>
</property>
<property>
<name>mdStoreManagerURI</name>
<description>the path of the cleaned mdstore</description>
</property>
</parameters>
<start to="StartTransaction"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="StartTransaction">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>NEW_VERSION</arg>
<arg>--mdStoreID</arg><arg>${mdStoreOutputId}</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
<capture-output/>
</java>
<ok to="generateOAF"/>
<error to="EndReadRollBack"/>
</action>
<action name="generateOAF">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Crossref TO OAF</name>
<class>eu.dnetlib.dhp.collection.crossref.SparkMapDumpIntoOAF</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.executor.memoryOverhead=2g
--conf spark.sql.shuffle.partitions=3000
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${sourcePath}</arg>
<arg>--unpaywallPath</arg><arg>${unpaywallPath}</arg>
<arg>--mdstoreOutputVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
<arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
<arg>--master</arg><arg>yarn</arg>
</spark>
<ok to="CommitVersion"/>
<error to="RollBack"/>
</action>
<action name="CommitVersion">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>COMMIT</arg>
<arg>--namenode</arg><arg>${nameNode}</arg>
<arg>--mdStoreVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
</java>
<ok to="End"/>
<error to="Kill"/>
</action>
<action name="EndReadRollBack">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>READ_UNLOCK</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
<arg>--readMDStoreId</arg><arg>${wf:actionData('BeginRead')['mdStoreReadLockVersion']}</arg>
<capture-output/>
</java>
<ok to="RollBack"/>
<error to="Kill"/>
</action>
<action name="RollBack">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>ROLLBACK</arg>
<arg>--mdStoreVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
</java>
<ok to="Kill"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

21
dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/collection/mag/convert_MAG_to_OAF_properties.json Normal file
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[
{
"paramName": "m",
"paramLongName": "master",
"paramDescription": "the master name",
"paramRequired": true
},
{
"paramName": "mo",
"paramLongName": "mdstoreOutputVersion",
"paramDescription": "The mdstore output",
"paramRequired": true
},
{
"paramName": "ma",
"paramLongName": "magBasePath",
"paramDescription": "The mag Base path",
"paramRequired": false
}
]

15
dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/collection/mag/create_MAG_denormalized_table_properties.json Normal file
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[
{
"paramName": "m",
"paramLongName": "master",
"paramDescription": "the master name",
"paramRequired": true
},
{
"paramName": "mp",
"paramLongName": "magBasePath",
"paramDescription": "The base path of MAG DUMP CSV Tables",
"paramRequired": true
}
]

21
dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/collection/mag/create_organization_AS.json Normal file
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[
{
"paramName": "m",
"paramLongName": "master",
"paramDescription": "the master name",
"paramRequired": true
},
{
"paramName": "o",
"paramLongName": "outputPath",
"paramDescription": "The as output Path",
"paramRequired": true
},
{
"paramName": "ma",
"paramLongName": "magBasePath",
"paramDescription": "The mag Base path",
"paramRequired": false
}
]

23
dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/collection/mag/oozie_app/config-default.xml Normal file
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<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>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>

160
dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/collection/mag/oozie_app/workflow.xml Normal file
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<workflow-app name="generate_MAG_Datasource" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>magBasePath</name>
<description>The base path of MAG DUMP CSV Tables</description>
</property>
<property>
<name>mdStoreOutputId</name>
<description>the identifier of the cleaned MDStore</description>
</property>
<property>
<name>mdStoreManagerURI</name>
<description>the path of the cleaned mdstore</description>
</property>
<property>
<name>resume_from</name>
<value>generateOAF</value>
<description>start Node</description>
</property>
</parameters>
<start to="resume_from"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<decision name="resume_from">
<switch>
<case to="generateTable">${wf:conf('resume_from') eq 'generateTable'}</case>
<default to="StartTransaction"/> <!-- first action to be done when downloadDump is to be performed -->
</switch>
</decision>
<action name="generateTable">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Generate MAG Table</name>
<class>eu.dnetlib.dhp.collection.mag.SparkCreateMagDenormalizedTable</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.executor.memoryOverhead=2g
--conf spark.sql.shuffle.partitions=3000
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--magBasePath</arg><arg>${magBasePath}</arg>
<arg>--master</arg><arg>yarn</arg>
</spark>
<ok to="StartTransaction"/>
<error to="Kill"/>
</action>
<action name="StartTransaction">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>NEW_VERSION</arg>
<arg>--mdStoreID</arg><arg>${mdStoreOutputId}</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
<capture-output/>
</java>
<ok to="generateOAF"/>
<error to="EndReadRollBack"/>
</action>
<action name="generateOAF">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>MAG TO OAF</name>
<class>eu.dnetlib.dhp.collection.mag.SparkMAGtoOAF</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.executor.memoryOverhead=2g
--conf spark.sql.shuffle.partitions=3000
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--mdstoreOutputVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
<arg>--magBasePath</arg><arg>${magBasePath}</arg>
<arg>--master</arg><arg>yarn</arg>
</spark>
<ok to="CommitVersion"/>
<error to="RollBack"/>
</action>
<action name="CommitVersion">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>COMMIT</arg>
<arg>--namenode</arg><arg>${nameNode}</arg>
<arg>--mdStoreVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
</java>
<ok to="End"/>
<error to="Kill"/>
</action>
<action name="EndReadRollBack">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>READ_UNLOCK</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
<arg>--readMDStoreId</arg><arg>${wf:actionData('BeginRead')['mdStoreReadLockVersion']}</arg>
<capture-output/>
</java>
<ok to="RollBack"/>
<error to="Kill"/>
</action>
<action name="RollBack">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>ROLLBACK</arg>
<arg>--mdStoreVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
</java>
<ok to="Kill"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

1099
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/collection/crossref/Crossref2Oaf.scala Normal file
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dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/collection/crossref/SparkMapDumpIntoOAF.scala Normal file
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package eu.dnetlib.dhp.collection.crossref
import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.application.AbstractScalaApplication
import eu.dnetlib.dhp.collection.crossref.Crossref2Oaf.{TransformationType, mergeUnpayWall}
import eu.dnetlib.dhp.common.Constants.MDSTORE_DATA_PATH
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
import eu.dnetlib.dhp.schema.mdstore.MDStoreVersion
import eu.dnetlib.dhp.schema.oaf.{Oaf, Result}
import eu.dnetlib.dhp.utils.ISLookupClientFactory
import org.apache.spark.sql._
import org.apache.spark.sql.functions.{col, explode, lower}
import org.apache.spark.sql.types._
import org.slf4j.{Logger, LoggerFactory}
class SparkMapDumpIntoOAF(propertyPath: String, args: Array[String], log: Logger)
extends AbstractScalaApplication(propertyPath, args, log: Logger) {
/** Here all the spark applications runs this method
* where the whole logic of the spark node is defined
*/
override def run(): Unit = {
val sourcePath = parser.get("sourcePath")
log.info("sourcePath: {}", sourcePath)
val unpaywallPath = parser.get("unpaywallPath")
log.info("unpaywallPath: {}", unpaywallPath)
val isLookupUrl: String = parser.get("isLookupUrl")
log.info("isLookupUrl: {}", isLookupUrl)
val isLookupService = ISLookupClientFactory.getLookUpService(isLookupUrl)
val vocabularies = VocabularyGroup.loadVocsFromIS(isLookupService)
require(vocabularies != null)
val mdstoreOutputVersion = parser.get("mdstoreOutputVersion")
log.info(s"mdstoreOutputVersion is '$mdstoreOutputVersion'")
val mapper = new ObjectMapper()
val cleanedMdStoreVersion = mapper.readValue(mdstoreOutputVersion, classOf[MDStoreVersion])
val outputBasePath = cleanedMdStoreVersion.getHdfsPath
log.info(s"outputBasePath is '$outputBasePath'")
val targetPath = s"$outputBasePath$MDSTORE_DATA_PATH"
log.info(s"targetPath is '$targetPath'")
transformCrossref(spark, sourcePath, targetPath, unpaywallPath, vocabularies)
reportTotalSize(targetPath, outputBasePath)
}
def transformUnpayWall(spark: SparkSession, unpaywallPath: String, crossrefPath: String): Dataset[UnpayWall] = {
val schema = new StructType()
.add(StructField("doi", StringType))
.add(StructField("is_oa", BooleanType))
.add(
StructField(
"best_oa_location",
new StructType()
.add("host_type", StringType)
.add("license", StringType)
.add("url", StringType)
)
)
.add("oa_status", StringType)
import spark.implicits._
val cId = spark.read
.schema(new StructType().add("DOI", StringType))
.json(crossrefPath)
.withColumn("doi", lower(col("DOI")))
val uw = spark.read
.schema(schema)
.json(unpaywallPath)
.withColumn("doi", lower(col("doi")))
.where("is_oa = true and best_oa_location.url is not null")
uw.join(cId, uw("doi") === cId("doi"), "leftsemi").as[UnpayWall].cache()
}
def transformCrossref(
spark: SparkSession,
sourcePath: String,
targetPath: String,
unpaywallPath: String,
vocabularies: VocabularyGroup
): Unit = {
import spark.implicits._
val mapper = new ObjectMapper()
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf])
implicit val resultEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
val dump: Dataset[String] = spark.read.text(sourcePath).as[String]
dump
.flatMap(s => Crossref2Oaf.convert(s, vocabularies, TransformationType.OnlyRelation))
.as[Oaf]
.map(r => mapper.writeValueAsString(r))
.write
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.text(targetPath)
val uw = transformUnpayWall(spark, unpaywallPath, sourcePath)
val resultCrossref: Dataset[(String, Result)] = dump
.flatMap(s => Crossref2Oaf.convert(s, vocabularies, TransformationType.OnlyResult))
.as[Oaf]
.map(r => r.asInstanceOf[Result])
.map(r => (r.getPid.get(0).getValue, r))(Encoders.tuple(Encoders.STRING, resultEncoder))
resultCrossref
.joinWith(uw, resultCrossref("_1").equalTo(uw("doi")), "left")
.map(k => {
mergeUnpayWall(k._1._2, k._2)
})
.map(r => mapper.writeValueAsString(r))
.as[Result]
.write
.mode(SaveMode.Append)
.option("compression", "gzip")
.text(s"$targetPath")
// Generate affiliation relations:
spark.read
.json(sourcePath)
.select(col("DOI"), explode(col("author.affiliation")).alias("affiliations"))
.select(col("DOI"), explode(col("affiliations.id")).alias("aids"))
.where("aids is not null")
.select(col("DOI"), explode(col("aids")).alias("aff"))
.select(col("DOI"), col("aff.id").alias("id"), col("aff.id-type").alias("idType"))
.where(col("idType").like("ROR"))
.flatMap(r => Crossref2Oaf.generateAffliation(r))
.write
.mode(SaveMode.Append)
.option("compression", "gzip")
.text(s"$targetPath")
}
}
object SparkMapDumpIntoOAF {
def main(args: Array[String]): Unit = {
val logger: Logger = LoggerFactory.getLogger(SparkMapDumpIntoOAF.getClass)
new SparkMapDumpIntoOAF(
log = logger,
args = args,
propertyPath = "/eu/dnetlib/dhp/collection/crossref/convert_crossref_dump_to_oaf_params.json"
).initialize().run()
}
}

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dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/collection/mag/MagUtility.scala Normal file
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package eu.dnetlib.dhp.collection.mag
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.utils.OafMapperUtils._
import eu.dnetlib.dhp.schema.oaf.utils.{OafMapperUtils, PidType}
import eu.dnetlib.dhp.schema.oaf.{Author, DataInfo, Instance, Journal, Organization, Publication, Relation, Result, Dataset => OafDataset}
import eu.dnetlib.dhp.utils.DHPUtils
import org.apache.spark.sql.types._
import org.apache.spark.sql.{Dataset, Row, SparkSession}
import org.json4s
import org.json4s.DefaultFormats
import org.json4s.jackson.JsonMethods.parse
import scala.collection.JavaConverters._
case class MAGPaper(
paperId: Option[Long],
doi: Option[String],
docType: Option[String],
paperTitle: Option[String],
originalTitle: Option[String],
bookTitle: Option[String],
year: Option[Int],
date: Option[String],
onlineDate: Option[String],
publisher: Option[String],
journalId: Option[Long],
journalName: Option[String],
journalIssn: Option[String],
journalPublisher: Option[String],
conferenceSeriesId: Option[Long],
conferenceInstanceId: Option[Long],
conferenceName: Option[String],
conferenceLocation: Option[String],
conferenceStartDate: Option[String],
conferenceEndDate: Option[String],
volume: Option[String],
issue: Option[String],
firstPage: Option[String],
lastPage: Option[String],
referenceCount: Option[Long],
citationCount: Option[Long],
estimatedCitation: Option[Long],
originalVenue: Option[String],
familyId: Option[Long],
familyRank: Option[Int],
docSubTypes: Option[String],
createdDate: Option[String],
abstractText: Option[String],
authors: Option[List[MAGAuthor]],
urls: Option[List[String]]
)
case class MAGAuthor(
AffiliationId: Option[Long],
AuthorSequenceNumber: Option[Int],
AffiliationName: Option[String],
AuthorName: Option[String],
AuthorId: Option[Long],
GridId: Option[String]
)
object MagUtility extends Serializable {
val mapper = new ObjectMapper()
private val MAGCollectedFrom = keyValue(ModelConstants.MAG_ID, ModelConstants.MAG_NAME)
private val MAGDataInfo: DataInfo = {
val di = new DataInfo
di.setDeletedbyinference(false)
di.setInferred(false)
di.setInvisible(false)
di.setTrust("0.9")
di.setProvenanceaction(
OafMapperUtils.qualifier(
ModelConstants.SYSIMPORT_ACTIONSET,
ModelConstants.SYSIMPORT_ACTIONSET,
ModelConstants.DNET_PROVENANCE_ACTIONS,
ModelConstants.DNET_PROVENANCE_ACTIONS
)
)
di
}
private val MAGDataInfoInvisible: DataInfo = {
val di = new DataInfo
di.setDeletedbyinference(false)
di.setInferred(false)
di.setInvisible(true)
di.setTrust("0.9")
di.setProvenanceaction(
OafMapperUtils.qualifier(
ModelConstants.SYSIMPORT_ACTIONSET,
ModelConstants.SYSIMPORT_ACTIONSET,
ModelConstants.DNET_PROVENANCE_ACTIONS,
ModelConstants.DNET_PROVENANCE_ACTIONS
)
)
di
}
val datatypedict = Map(
"bool" -> BooleanType,
"int" -> IntegerType,
"uint" -> IntegerType,
"long" -> LongType,
"ulong" -> LongType,
"float" -> FloatType,
"string" -> StringType,
"DateTime" -> DateType
)
val stream: Map[String, (String, Seq[String])] = Map(
"Affiliations" -> Tuple2(
"mag/Affiliations.txt",
Seq(
"AffiliationId:long",
"Rank:uint",
"NormalizedName:string",
"DisplayName:string",
"GridId:string",
"OfficialPage:string",
"WikiPage:string",
"PaperCount:long",
"PaperFamilyCount:long",
"CitationCount:long",
"Iso3166Code:string",
"Latitude:float?",
"Longitude:float?",
"CreatedDate:DateTime"
)
),
"AuthorExtendedAttributes" -> Tuple2(
"mag/AuthorExtendedAttributes.txt",
Seq("AuthorId:long", "AttributeType:int", "AttributeValue:string")
),
"Authors" -> Tuple2(
"mag/Authors.txt",
Seq(
"AuthorId:long",
"Rank:uint",
"NormalizedName:string",
"DisplayName:string",
"LastKnownAffiliationId:long?",
"PaperCount:long",
"PaperFamilyCount:long",
"CitationCount:long",
"CreatedDate:DateTime"
)
),
"ConferenceInstances" -> Tuple2(
"mag/ConferenceInstances.txt",
Seq(
"ConferenceInstanceId:long",
"NormalizedName:string",
"DisplayName:string",
"ConferenceSeriesId:long",
"Location:string",
"OfficialUrl:string",
"StartDate:DateTime?",
"EndDate:DateTime?",
"AbstractRegistrationDate:DateTime?",
"SubmissionDeadlineDate:DateTime?",
"NotificationDueDate:DateTime?",
"FinalVersionDueDate:DateTime?",
"PaperCount:long",
"PaperFamilyCount:long",
"CitationCount:long",
"Latitude:float?",
"Longitude:float?",
"CreatedDate:DateTime"
)
),
"ConferenceSeries" -> Tuple2(
"mag/ConferenceSeries.txt",
Seq(
"ConferenceSeriesId:long",
"Rank:uint",
"NormalizedName:string",
"DisplayName:string",
"PaperCount:long",
"PaperFamilyCount:long",
"CitationCount:long",
"CreatedDate:DateTime"
)
),
"EntityRelatedEntities" -> Tuple2(
"advanced/EntityRelatedEntities.txt",
Seq(
"EntityId:long",
"EntityType:string",
"RelatedEntityId:long",
"RelatedEntityType:string",
"RelatedType:int",
"Score:float"
)
),
"FieldOfStudyChildren" -> Tuple2(
"advanced/FieldOfStudyChildren.txt",
Seq("FieldOfStudyId:long", "ChildFieldOfStudyId:long")
),
"FieldOfStudyExtendedAttributes" -> Tuple2(
"advanced/FieldOfStudyExtendedAttributes.txt",
Seq("FieldOfStudyId:long", "AttributeType:int", "AttributeValue:string")
),
"FieldsOfStudy" -> Tuple2(
"advanced/FieldsOfStudy.txt",
Seq(
"FieldOfStudyId:long",
"Rank:uint",
"NormalizedName:string",
"DisplayName:string",
"MainType:string",
"Level:int",
"PaperCount:long",
"PaperFamilyCount:long",
"CitationCount:long",
"CreatedDate:DateTime"
)
),
"Journals" -> Tuple2(
"mag/Journals.txt",
Seq(
"JournalId:long",
"Rank:uint",
"NormalizedName:string",
"DisplayName:string",
"Issn:string",
"Publisher:string",
"Webpage:string",
"PaperCount:long",
"PaperFamilyCount:long",
"CitationCount:long",
"CreatedDate:DateTime"
)
),
"PaperAbstractsInvertedIndex" -> Tuple2(
"nlp/PaperAbstractsInvertedIndex.txt.*",
Seq("PaperId:long", "IndexedAbstract:string")
),
"PaperAuthorAffiliations" -> Tuple2(
"mag/PaperAuthorAffiliations.txt",
Seq(
"PaperId:long",
"AuthorId:long",
"AffiliationId:long?",
"AuthorSequenceNumber:uint",
"OriginalAuthor:string",
"OriginalAffiliation:string"
)
),
"PaperCitationContexts" -> Tuple2(
"nlp/PaperCitationContexts.txt",
Seq("PaperId:long", "PaperReferenceId:long", "CitationContext:string")
),
"PaperExtendedAttributes" -> Tuple2(
"mag/PaperExtendedAttributes.txt",
Seq("PaperId:long", "AttributeType:int", "AttributeValue:string")
),
"PaperFieldsOfStudy" -> Tuple2(
"advanced/PaperFieldsOfStudy.txt",
Seq("PaperId:long", "FieldOfStudyId:long", "Score:float")
),
"PaperMeSH" -> Tuple2(
"advanced/PaperMeSH.txt",
Seq(
"PaperId:long",
"DescriptorUI:string",
"DescriptorName:string",
"QualifierUI:string",
"QualifierName:string",
"IsMajorTopic:bool"
)
),
"PaperRecommendations" -> Tuple2(
"advanced/PaperRecommendations.txt",
Seq("PaperId:long", "RecommendedPaperId:long", "Score:float")
),
"PaperReferences" -> Tuple2(
"mag/PaperReferences.txt",
Seq("PaperId:long", "PaperReferenceId:long")
),
"PaperResources" -> Tuple2(
"mag/PaperResources.txt",
Seq(
"PaperId:long",
"ResourceType:int",
"ResourceUrl:string",
"SourceUrl:string",
"RelationshipType:int"
)
),
"PaperUrls" -> Tuple2(
"mag/PaperUrls.txt",
Seq("PaperId:long", "SourceType:int?", "SourceUrl:string", "LanguageCode:string")
),
"Papers" -> Tuple2(
"mag/Papers.txt",
Seq(
"PaperId:long",
"Rank:uint",
"Doi:string",
"DocType:string",
"PaperTitle:string",
"OriginalTitle:string",
"BookTitle:string",
"Year:int?",
"Date:DateTime?",
"OnlineDate:DateTime?",
"Publisher:string",
"JournalId:long?",
"ConferenceSeriesId:long?",
"ConferenceInstanceId:long?",
"Volume:string",
"Issue:string",
"FirstPage:string",
"LastPage:string",
"ReferenceCount:long",
"CitationCount:long",
"EstimatedCitation:long",
"OriginalVenue:string",
"FamilyId:long?",
"FamilyRank:uint?",
"DocSubTypes:string",
"CreatedDate:DateTime"
)
),
"RelatedFieldOfStudy" -> Tuple2(
"advanced/RelatedFieldOfStudy.txt",
Seq(
"FieldOfStudyId1:long",
"Type1:string",
"FieldOfStudyId2:long",
"Type2:string",
"Rank:float"
)
)
)
def getSchema(streamName: String): StructType = {
var schema = new StructType()
val d: Seq[String] = stream(streamName)._2
d.foreach { t =>
val currentType = t.split(":")
val fieldName: String = currentType.head
var fieldType: String = currentType.last
val nullable: Boolean = fieldType.endsWith("?")
if (nullable)
fieldType = fieldType.replace("?", "")
schema = schema.add(StructField(fieldName, datatypedict(fieldType), nullable))
}
schema
}
def loadMagEntity(spark: SparkSession, entity: String, basePath: String): Dataset[Row] = {
if (stream.contains(entity)) {
val s = getSchema(entity)
val pt = stream(entity)._1
spark.read
.option("header", "false")
.option("charset", "UTF8")
.option("delimiter", "\t")
.schema(s)
.csv(s"$basePath/$pt")
} else
null
}
def createResultFromType(magType: Option[String], source: Option[String]): Result = {
var result: Result = null
if (magType == null || magType.orNull == null) {
result = new Publication
result.setDataInfo(MAGDataInfo)
val i = new Instance
i.setInstancetype(
qualifier(
"0038",
"Other literature type",
ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE
)
)
result.setInstance(List(i).asJava)
return result
}
val currentType: String = magType.get
val tp = currentType.toLowerCase match {
case "book" =>
result = new Publication
qualifier("0002", "Book", ModelConstants.DNET_PUBLICATION_RESOURCE, ModelConstants.DNET_PUBLICATION_RESOURCE)
case "bookchapter" =>
result = new Publication
qualifier(
"00013",
"Part of book or chapter of book",
ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE
)
case "journal" =>
result = new Publication
qualifier("0043", "Journal", ModelConstants.DNET_PUBLICATION_RESOURCE, ModelConstants.DNET_PUBLICATION_RESOURCE)
case "patent" =>
if (source != null && source.orNull != null) {
val s = source.get.toLowerCase
if (s.contains("patent") || s.contains("brevet")) {
result = new Publication
qualifier(
"0019",
"Patent",
ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE
)
} else if (s.contains("journal of")) {
result = new Publication
qualifier(
"0043",
"Journal",
ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE
)
} else if (
s.contains("proceedings") || s.contains("conference") || s.contains("workshop") || s.contains(
"symposium"
)
) {
result = new Publication
qualifier(
"0001",
"Article",
ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE
)
} else null
} else null
case "repository" =>
result = new Publication()
result.setDataInfo(MAGDataInfoInvisible)
qualifier(
"0038",
"Other literature type",
ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE
)
case "thesis" =>
result = new Publication
qualifier(
"0044",
"Thesis",
ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE
)
case "dataset" =>
result = new OafDataset
qualifier(
"0021",
"Dataset",
ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE
)
case "conference" =>
result = new Publication
qualifier(
"0001",
"Article",
ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE
)
}
if (result != null) {
if (result.getDataInfo == null)
result.setDataInfo(MAGDataInfo)
val i = new Instance
i.setInstancetype(tp)
i.setInstanceTypeMapping(
List(instanceTypeMapping(currentType, ModelConstants.OPENAIRE_COAR_RESOURCE_TYPES_3_1)).asJava
)
result.setInstance(List(i).asJava)
}
result
}
def convertMAGtoOAF(paper: MAGPaper): String = {
// FILTER all the MAG paper with no URL
if (paper.urls.orNull == null)
return null
val result = createResultFromType(paper.docType, paper.originalVenue)
if (result == null)
return null
result.setCollectedfrom(List(MAGCollectedFrom).asJava)
val pidList = List(
structuredProperty(
paper.paperId.get.toString,
qualifier(
PidType.mag_id.toString,
PidType.mag_id.toString,
ModelConstants.DNET_PID_TYPES,
ModelConstants.DNET_PID_TYPES
),
null
)
)
result.setPid(pidList.asJava)
result.setOriginalId(pidList.map(s => s.getValue).asJava)
result.setId(s"50|mag_________::${DHPUtils.md5(paper.paperId.get.toString)}")
val originalTitles = structuredProperty(paper.paperTitle.get, ModelConstants.MAIN_TITLE_QUALIFIER, null)
result.setTitle(List(originalTitles).asJava)
if (paper.date.orNull != null) {
result.setDateofacceptance(field(paper.date.get, null))
} else {
if (paper.year.isDefined && paper.year.get > 1700) {
result.setDateofacceptance(field(s"${paper.year.get}-01-01", null))
}
}
if (paper.onlineDate.orNull != null) {
result.setRelevantdate(
List(
structuredProperty(
paper.onlineDate.get,
qualifier(
"published-online",
"published-online",
ModelConstants.DNET_DATACITE_DATE,
ModelConstants.DNET_DATACITE_DATE
),
null
)
).asJava
)
}
if (paper.publisher.orNull != null) {
result.setPublisher(field(paper.publisher.get, null))
}
if (paper.date.isDefined)
result.setDateofacceptance(field(paper.date.get, null))
if (paper.onlineDate.orNull != null)
result.setRelevantdate(
List(
structuredProperty(
paper.onlineDate.get,
qualifier(
"published-online",
"published-online",
ModelConstants.DNET_DATACITE_DATE,
ModelConstants.DNET_DATACITE_DATE
),
null
)
).asJava
)
if (paper.publisher.isDefined)
result.setPublisher(field(paper.publisher.get, null))
if (paper.journalId.isDefined && paper.journalName.isDefined) {
val j = new Journal
j.setName(paper.journalName.get)
j.setSp(paper.firstPage.orNull)
j.setEp(paper.lastPage.orNull)
if (paper.publisher.isDefined)
result.setPublisher(field(paper.publisher.get, null))
j.setIssnPrinted(paper.journalIssn.orNull)
j.setVol(paper.volume.orNull)
j.setIss(paper.issue.orNull)
j.setConferenceplace(paper.conferenceLocation.orNull)
result match {
case publication: Publication => publication.setJournal(j)
}
}
if (paper.abstractText.isDefined)
result.setDescription(List(field(paper.abstractText.get, null)).asJava)
if (paper.authors.isDefined && paper.authors.get.nonEmpty) {
result.setAuthor(
paper.authors.get
.filter(a => a.AuthorName.isDefined)
.map(a => {
val author = new Author
author.setFullname(a.AuthorName.get)
author
})
.asJava
)
}
val instance = result.getInstance().get(0)
instance.setPid(pidList.asJava)
if (paper.doi.orNull != null)
instance.setAlternateIdentifier(
List(
structuredProperty(
paper.doi.get,
qualifier(
PidType.doi.toString,
PidType.doi.toString,
ModelConstants.DNET_PID_TYPES,
ModelConstants.DNET_PID_TYPES
),
null
)
).asJava
)
instance.setUrl(paper.urls.get.asJava)
instance.setHostedby(ModelConstants.UNKNOWN_REPOSITORY)
instance.setCollectedfrom(MAGCollectedFrom)
instance.setAccessright(
accessRight(
ModelConstants.UNKNOWN,
ModelConstants.NOT_AVAILABLE,
ModelConstants.DNET_ACCESS_MODES,
ModelConstants.DNET_ACCESS_MODES
)
)
if (paper.authors.orNull != null && paper.authors.get.nonEmpty)
result.setAuthor(
paper.authors.get
.filter(a => a.AuthorName.orNull != null)
.map { a =>
val author = new Author
author.setFullname(a.AuthorName.get)
var authorPid = List(
structuredProperty(
a.AuthorId.get.toString,
qualifier(
PidType.mag_id.toString,
PidType.mag_id.toString,
ModelConstants.DNET_PID_TYPES,
ModelConstants.DNET_PID_TYPES
),
null
)
)
if (a.GridId.orNull != null) {
authorPid = authorPid ::: List(
structuredProperty(
a.AuthorId.get.toString,
qualifier(
PidType.mag_id.toString,
PidType.mag_id.toString,
ModelConstants.DNET_PID_TYPES,
ModelConstants.DNET_PID_TYPES
),
null
)
)
}
author.setPid(authorPid.asJava)
author
}
.asJava
)
mapper.writeValueAsString(result)
}
def generateOrganization(r: Row): String = {
val o = new Organization
val affId = s"20|mag_________::${DHPUtils.md5(r.getAs[Long]("AffiliationId").toString)}"
o.setId(affId)
o.setDataInfo(MAGDataInfo)
o.setCollectedfrom(List(MAGCollectedFrom).asJava)
o.setLegalname(field(r.getAs[String]("DisplayName"), null))
val gid = r.getAs[String]("GridId")
if (gid != null) {
o.setPid(List(
structuredProperty(gid, qualifier(
PidType.GRID.toString,
PidType.GRID.toString,
ModelConstants.DNET_PID_TYPES,
ModelConstants.DNET_PID_TYPES
),
null),
structuredProperty(r.getAs[Long]("AffiliationId").toString, qualifier(
PidType.mag_id.toString,
PidType.mag_id.toString,
ModelConstants.DNET_PID_TYPES,
ModelConstants.DNET_PID_TYPES
),
null)
).asJava)
} else {
o.setPid(List(
structuredProperty(r.getAs[Long]("AffiliationId").toString, qualifier(
PidType.mag_id.toString,
PidType.mag_id.toString,
ModelConstants.DNET_PID_TYPES,
ModelConstants.DNET_PID_TYPES
),
null)
).asJava)
}
val c = r.getAs[String]("Iso3166Code")
if (c != null)
o.setCountry(qualifier(c, c, "dnet:countries", "dnet:countries"))
else
o.setCountry(ModelConstants.UNKNOWN_COUNTRY)
val ws = r.getAs[String]("OfficialPage")
if (ws != null)
o.setWebsiteurl(field(ws, null))
val a = new AtomicAction[Organization]()
a.setClazz(classOf[Organization])
a.setPayload(o)
mapper.writeValueAsString(a)
}
def generateAffiliationRelations(paperAffiliation: Row): List[Relation] = {
val affId = s"20|mag_________::${DHPUtils.md5(paperAffiliation.getAs[Long]("AffiliationId").toString)}"
val oafId = s"50|mag_________::${DHPUtils.md5(paperAffiliation.getAs[Long]("PaperId").toString)}"
val r: Relation = new Relation
r.setSource(oafId)
r.setTarget(affId)
r.setRelType(ModelConstants.RESULT_ORGANIZATION)
r.setRelClass(ModelConstants.HAS_AUTHOR_INSTITUTION)
r.setSubRelType(ModelConstants.AFFILIATION)
r.setDataInfo(MAGDataInfo)
r.setCollectedfrom(List(MAGCollectedFrom).asJava)
val r1: Relation = new Relation
r1.setTarget(oafId)
r1.setSource(affId)
r1.setRelType(ModelConstants.RESULT_ORGANIZATION)
r1.setRelClass(ModelConstants.IS_AUTHOR_INSTITUTION_OF)
r1.setSubRelType(ModelConstants.AFFILIATION)
r1.setDataInfo(MAGDataInfo)
r1.setCollectedfrom(List(MAGCollectedFrom).asJava)
List(r, r1)
}
def convertInvertedIndexString(json_input: String): String = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
lazy val json: json4s.JValue = parse(json_input)
val idl = (json \ "IndexLength").extract[Int]
if (idl > 0) {
val res = Array.ofDim[String](idl)
val iid = (json \ "InvertedIndex").extract[Map[String, List[Int]]]
for { (k: String, v: List[Int]) <- iid } {
v.foreach(item => res(item) = k)
}
(0 until idl).foreach(i => {
if (res(i) == null)
res(i) = ""
})
return res.mkString(" ")
}
""
}
}

199
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/collection/mag/SparkCreateMagDenormalizedTable.scala Normal file
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@ -0,0 +1,199 @@
package eu.dnetlib.dhp.collection.mag
import eu.dnetlib.dhp.application.AbstractScalaApplication
import org.apache.spark.sql.functions._
import org.apache.spark.sql.types.{StringType, StructField, StructType}
import org.apache.spark.sql.{Dataset, Row, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
class SparkCreateMagDenormalizedTable(propertyPath: String, args: Array[String], log: Logger)
extends AbstractScalaApplication(propertyPath, args, log: Logger) {
/** Here all the spark applications runs this method
* where the whole logic of the spark node is defined
*/
override def run(): Unit = {
val magBasePath: String = parser.get("magBasePath")
log.info("found parameters magBasePath: {}", magBasePath)
generatedDenormalizedMAGTable(spark, magBasePath)
}
private def generatedDenormalizedMAGTable(
spark: SparkSession,
magBasePath: String
): Unit = {
import spark.implicits._
val schema: StructType = StructType(StructField("DOI", StringType) :: Nil)
//Filter all the MAG Papers that intersect with a Crossref DOI
val magPapers = MagUtility
.loadMagEntity(spark, "Papers", magBasePath)
.withColumn("Doi", lower(col("Doi")))
magPapers.cache()
magPapers.count()
//log.info("Create current abstract")
//Abstract is an inverted list, we define a function that convert in string the abstract and recreate
// a table(PaperId, Abstract)
val paperAbstract = MagUtility
.loadMagEntity(spark, "PaperAbstractsInvertedIndex", magBasePath)
.map(s => (s.getLong(0), MagUtility.convertInvertedIndexString(s.getString(1))))
.withColumnRenamed("_1", "PaperId")
.withColumnRenamed("_2", "Abstract")
//We define Step0 as the result of the Join between PaperIntersection and the PaperAbstract
val step0 = magPapers
.join(paperAbstract, magPapers("PaperId") === paperAbstract("PaperId"), "left")
.select(magPapers("*"), paperAbstract("Abstract"))
.cache()
step0.count()
magPapers.unpersist()
// We have three table Author, Affiliation, and PaperAuthorAffiliation, in the
//next step we create a table containing
val authors = MagUtility.loadMagEntity(spark, "Authors", magBasePath)
val affiliations = MagUtility.loadMagEntity(spark, "Affiliations", magBasePath)
val paperAuthorAffiliations = MagUtility.loadMagEntity(spark, "PaperAuthorAffiliations", magBasePath)
val j1 = paperAuthorAffiliations
.join(authors, paperAuthorAffiliations("AuthorId") === authors("AuthorId"), "inner")
.select(
col("PaperId"),
col("AffiliationId"),
col("AuthorSequenceNumber"),
authors("DisplayName").alias("AuthorName"),
authors("AuthorId")
)
val paperAuthorAffiliationNormalized = j1
.join(affiliations, j1("AffiliationId") === affiliations("AffiliationId"), "left")
.select(j1("*"), affiliations("DisplayName").alias("AffiliationName"), affiliations("GridId"))
.groupBy("PaperId")
.agg(
collect_list(
struct("AffiliationId", "AuthorSequenceNumber", "AffiliationName", "AuthorName", "AuthorId", "GridId")
).alias("authors")
)
val step1 = step0
.join(paperAuthorAffiliationNormalized, step0("PaperId") === paperAuthorAffiliationNormalized("PaperId"), "left")
.select(step0("*"), paperAuthorAffiliationNormalized("authors"))
.cache()
step1.count()
step0.unpersist()
val conference = MagUtility
.loadMagEntity(spark, "ConferenceInstances", magBasePath)
.select(
$"ConferenceInstanceId",
$"DisplayName".as("conferenceName"),
$"Location".as("conferenceLocation"),
$"StartDate".as("conferenceStartDate"),
$"EndDate".as("conferenceEndDate")
)
val step2 = step1
.join(conference, step1("ConferenceInstanceId") === conference("ConferenceInstanceId"), "left")
.select(
step1("*"),
conference("conferenceName"),
conference("conferenceLocation"),
conference("conferenceStartDate"),
conference("conferenceEndDate")
)
.cache()
step2.count()
step1.unpersist()
val journals = MagUtility
.loadMagEntity(spark, "Journals", magBasePath)
.select(
$"JournalId",
$"DisplayName".as("journalName"),
$"Issn".as("journalIssn"),
$"Publisher".as("journalPublisher")
)
val step3 = step2
.join(journals, step2("JournalId") === journals("JournalId"), "left")
.select(
step2("*"),
journals("journalName"),
journals("journalIssn"),
journals("journalPublisher")
)
.cache
step3.count()
val paper_urls = MagUtility
.loadMagEntity(spark, "PaperUrls", magBasePath)
.groupBy("PaperId")
.agg(slice(collect_set("SourceUrl"), 1, 6).alias("urls"))
.cache
paper_urls.count
step3
.join(paper_urls, step3("PaperId") === paper_urls("PaperId"))
.select(step3("*"), paper_urls("urls"))
.select(
$"PaperId".as("paperId"),
$"Doi".as("doi"),
$"DocType".as("docType"),
$"PaperTitle".as("paperTitle"),
$"OriginalTitle".as("originalTitle"),
$"BookTitle".as("bookTitle"),
$"Year".as("year"),
$"Date".as("date"),
$"OnlineDate".as("onlineDate"),
$"Publisher".as("publisher"),
$"JournalId".as("journalId"),
$"ConferenceSeriesId".as("conferenceSeriesId"),
$"ConferenceInstanceId".as("conferenceInstanceId"),
$"Volume".as("volume"),
$"Issue".as("issue"),
$"FirstPage".as("firstPage"),
$"LastPage".as("lastPage"),
$"ReferenceCount".as("referenceCount"),
$"CitationCount".as("citationCount"),
$"EstimatedCitation".as("estimatedCitation"),
$"OriginalVenue".as("originalVenue"),
$"FamilyId".as("familyId"),
$"FamilyRank".as("familyRank"),
$"DocSubTypes".as("docSubTypes"),
$"CreatedDate".as("createdDate"),
$"Abstract".as("abstractText"),
$"authors".as("authors"),
$"conferenceName".as("conferenceName"),
$"conferenceLocation".as("conferenceLocation"),
$"conferenceStartDate".as("conferenceStartDate"),
$"conferenceEndDate".as("conferenceEndDate"),
$"journalName".as("journalName"),
$"journalIssn".as("journalIssn"),
$"journalPublisher".as("journalPublisher"),
$"urls"
)
.write
.mode("OverWrite")
.save(s"$magBasePath/mag_denormalized")
step3.unpersist()
}
}
object SparkCreateMagDenormalizedTable {
val log: Logger = LoggerFactory.getLogger(SparkCreateMagDenormalizedTable.getClass)
def main(args: Array[String]): Unit = {
new SparkCreateMagDenormalizedTable(
"/eu/dnetlib/dhp/collection/mag/create_MAG_denormalized_table_properties.json",
args,
log
).initialize().run()
}
}

83
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/collection/mag/SparkMAGtoOAF.scala Normal file
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package eu.dnetlib.dhp.collection.mag
import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.application.AbstractScalaApplication
import eu.dnetlib.dhp.common.Constants.MDSTORE_DATA_PATH
import eu.dnetlib.dhp.schema.mdstore.MDStoreVersion
import eu.dnetlib.dhp.schema.oaf.Relation
import org.apache.spark.sql.functions.col
import org.apache.spark.sql.types.{ArrayType, StringType, StructField, StructType}
import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
class SparkMAGtoOAF(propertyPath: String, args: Array[String], log: Logger)
extends AbstractScalaApplication(propertyPath, args, log: Logger) {
/** Here all the spark applications runs this method
* where the whole logic of the spark node is defined
*/
override def run(): Unit = {
val mdstoreOutputVersion = parser.get("mdstoreOutputVersion")
log.info(s"mdstoreOutputVersion is '$mdstoreOutputVersion'")
val mapper = new ObjectMapper()
val cleanedMdStoreVersion = mapper.readValue(mdstoreOutputVersion, classOf[MDStoreVersion])
val outputBasePath = cleanedMdStoreVersion.getHdfsPath
log.info(s"outputBasePath is '$outputBasePath'")
val mdstorePath = s"$outputBasePath$MDSTORE_DATA_PATH"
val magBasePath: String = parser.get("magBasePath")
log.info("found parameters magBasePath: {}", magBasePath)
convertMAG(spark, magBasePath, mdstorePath)
generateAffiliations(spark, magBasePath, mdstorePath)
reportTotalSize(mdstorePath, outputBasePath)
}
def convertMAG(spark: SparkSession, magBasePath: String, mdStorePath: String): Unit = {
import spark.implicits._
spark.read
.load(s"$magBasePath/mag_denormalized")
.as[MAGPaper]
.map(s => MagUtility.convertMAGtoOAF(s))
.filter(s => s != null)
.write
.option("compression", "gzip")
.mode(SaveMode.Overwrite)
.text(mdStorePath)
}
def generateAffiliations(spark: SparkSession, magBasePath: String, mdStorePath: String): Unit = {
implicit val relEncoder: Encoder[Relation] = Encoders.bean(classOf[Relation])
val schema = new StructType()
.add(StructField("id", StringType))
.add(StructField("originalId", ArrayType(StringType)))
val generatedMag =
spark.read.schema(schema).json(mdStorePath).selectExpr("explode(originalId) as PaperId").distinct()
val paperAuthorAffiliations = MagUtility
.loadMagEntity(spark, "PaperAuthorAffiliations", magBasePath)
.where(col("AffiliationId").isNotNull)
.select("PaperId", "AffiliationId")
.distinct
paperAuthorAffiliations
.join(generatedMag, paperAuthorAffiliations("PaperId") === generatedMag("PaperId"), "leftsemi")
.flatMap(r => MagUtility.generateAffiliationRelations(r))
.write
.option("compression", "gzip")
.mode(SaveMode.Append)
.json(mdStorePath)
}
}
object SparkMAGtoOAF {
val log: Logger = LoggerFactory.getLogger(SparkMAGtoOAF.getClass)
def main(args: Array[String]): Unit = {
new SparkMAGtoOAF("/eu/dnetlib/dhp/collection/mag/convert_MAG_to_OAF_properties.json", args, log)
.initialize()
.run()
}
}

42
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/collection/mag/SparkMagOrganizationAS.scala Normal file
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package eu.dnetlib.dhp.collection.mag
import eu.dnetlib.dhp.application.AbstractScalaApplication
import eu.dnetlib.dhp.schema.action.AtomicAction
import eu.dnetlib.dhp.schema.oaf.Organization
import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
class SparkMagOrganizationAS (propertyPath: String, args: Array[String], log: Logger)
extends AbstractScalaApplication(propertyPath, args, log: Logger) {
/** Here all the spark applications runs this method
* where the whole logic of the spark node is defined
*/
override def run(): Unit = {
val magBasePath:String = parser.get("magBasePath")
log.info(s"magBasePath is $magBasePath")
val outputPath:String = parser.get("outputPath")
log.info(s"outputPath is $outputPath")
generateAS(spark,magBasePath, outputPath)
}
def generateAS(spark:SparkSession, magBasePath:String,outputPath:String ):Unit = {
import spark.implicits._
val organizations = MagUtility.loadMagEntity(spark,"Affiliations", magBasePath)
organizations.map(r => MagUtility.generateOrganization(r)).write.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.text(outputPath)
}
}
object SparkMagOrganizationAS{
val log: Logger = LoggerFactory.getLogger(SparkMagOrganizationAS.getClass)
def main(args: Array[String]): Unit = {
new SparkMagOrganizationAS("/eu/dnetlib/dhp/collection/mag/create_organization_AS.json", args, log)
.initialize()
.run()
}
}

14
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/datacite/GenerateDataciteDatasetSpark.scala
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@ -46,20 +46,6 @@ class GenerateDataciteDatasetSpark(propertyPath: String, args: Array[String], lo
reportTotalSize(targetPath, outputBasePath) reportTotalSize(targetPath, outputBasePath)
} }
/** For working with MDStore we need to store in a file on hdfs the size of
* the current dataset
* @param targetPath
* @param outputBasePath
*/
def reportTotalSize(targetPath: String, outputBasePath: String): Unit = {
val total_items = spark.read.text(targetPath).count()
writeHdfsFile(
spark.sparkContext.hadoopConfiguration,
s"$total_items",
outputBasePath + MDSTORE_SIZE_PATH
)
}
/** Generate the transformed and cleaned OAF Dataset from the native one /** Generate the transformed and cleaned OAF Dataset from the native one
* *
* @param sourcePath sourcePath of the native Dataset in format JSON/Datacite * @param sourcePath sourcePath of the native Dataset in format JSON/Datacite

849
dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/collection/crossref/issn_pub.json Normal file
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@ -0,0 +1,849 @@
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"article-title": "Enzyme-linked immunosorbent assay (ELISAs) for metalloproteinase derived type II collagen neoepitope, CIIM-Increased serum CIIM in subjects with severe radiographic osteoarthritis",
"year": "2011",
"volume": "44",
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{
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"article-title": "Cartilage turnover reflected by metabolic processing of type II collagen: a novel marker of anabolic function in chondrocytes",
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{
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"DOI": "10.1016/j.clinbiochem.2010.03.012",
"article-title": "A novel assay for extracellular matrix remodeling associated with liver fibrosis: an enzyme-linked immunosorbent assay (ELISA) for a MMP-9 proteolytically revealed neo-epitope of type III collagen",
"year": "2010",
"volume": "43",
"journal-title": "Clin Biochem"
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{
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"DOI": "10.1016/0003-2697(87)90658-0",
"article-title": "Microdetermination of proteoglycans and glycosaminoglycans in the presence of guanidine hydrochloride",
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"volume": "161",
"journal-title": "Anal Biochem"
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"article-title": "Amino acid addition to Vibrio cholerae LPS establishes a link between surface remodeling in Gram-positive and Gram-negative bacteria",
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{
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},
{
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"DOI": "10.1016/j.joca.2013.03.018",
"article-title": "The epidemiology and impact of pain in osteoarthritis",
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"journal-title": "Osteoarthr Cartil"
},
{
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"DOI": "10.1016/j.rdc.2008.05.004",
"article-title": "The symptoms of osteoarthritis and the genesis of pain",
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"journal-title": "Rheum Dis Clin N Am"
},
{
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"DOI": "10.1038/nm.3978",
"article-title": "Inhibition of mechanical allodynia in neuropathic pain by TLR5-mediated A-fiber blockade",
"year": "2015",
"volume": "21",
"journal-title": "Nat Med"
},
{
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"issue": "October 2017",
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"key": "10.1016/j.joca.2019.11.002_bib30",
"DOI": "10.1016/j.pharmthera.2017.10.006",
"article-title": "Toll-like receptors and their role in persistent pain",
"year": "2018",
"volume": "184",
"journal-title": "Pharmacol Ther"
},
{
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"first-page": "2016",
"article-title": "Blockade of toll-like receptors (TLR2, TLR4) attenuates pain and potentiates buprenorphine analgesia in a rat neuropathic pain model",
"author": "Jurga",
"year": "2016",
"journal-title": "Neural Plast"
},
{
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"issue": "5",
"author": "Huang",
"key": "10.1016/j.joca.2019.11.002_bib32",
"DOI": "10.1007/s11926-009-0051-z",
"article-title": "The role of toll-like receptors in rheumatoid arthritis",
"year": "2009",
"volume": "11",
"journal-title": "Curr Rheumatol Rep"
},
{
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"first-page": "1",
"article-title": "TLR4 signalling in osteoarthritis-finding targets for candidate DMOADs",
"volume": "11",
"author": "Gómez",
"year": "2014",
"journal-title": "Nat Rev Rheumatol"
},
{
"issue": "5 Pt 1",
"key": "10.1016/j.joca.2019.11.002_bib34",
"first-page": "1432",
"article-title": "Procollagen types I and III aminoterminal propeptide levels during acute respiratory distress syndrome and in response to methylprednisolone treatment.[Erratum appears in Am J Respir Crit Care Med. 2013 Dec 15;188(12):1477]",
"volume": "158",
"author": "Meduri",
"year": "1998",
"journal-title": "Am J Respir Crit Care Med"
},
{
"doi-asserted-by": "crossref",
"first-page": "5",
"issue": "1",
"author": "Scheja",
"key": "10.1016/j.joca.2019.11.002_bib35",
"DOI": "10.3109/03009749209095054",
"article-title": "Serum levels of aminoterminal type III procollagen peptide and hyaluronan predict mortality in systemic sclerosis",
"year": "1992",
"volume": "21",
"journal-title": "Scand J Rheumatol"
},
{
"doi-asserted-by": "crossref",
"first-page": "547",
"issue": "8",
"author": "Kjelgaard-Petersen",
"key": "10.1016/j.joca.2019.11.002_bib36",
"DOI": "10.3109/1354750X.2015.1105497",
"article-title": "Synovitis biomarkers: ex vivo characterization of three biomarkers for identification of inflammatory osteoarthritis",
"year": "2015",
"volume": "20",
"journal-title": "Biomarkers"
},
{
"key": "10.1016/j.joca.2019.11.002_bib37",
"article-title": "Sensitization and serological biomarkers in knee osteoarthritis patients with different degrees of synovitis",
"author": "Petersen",
"year": "2015",
"journal-title": "Clin J Pain"
},
{
"doi-asserted-by": "crossref",
"first-page": "309",
"author": "He",
"key": "10.1016/j.joca.2019.11.002_bib38",
"DOI": "10.1186/1471-2474-15-309",
"article-title": "Type X collagen levels are elevated in serum from human osteoarthritis patients and associated with biomarkers of cartilage degradation and inflammation",
"year": "2014",
"volume": "15",
"journal-title": "BMC Muscoskelet Disord"
},
{
"doi-asserted-by": "crossref",
"first-page": "1",
"issue": "1",
"author": "Bay-Jensen",
"key": "10.1016/j.joca.2019.11.002_bib39",
"DOI": "10.1371/journal.pone.0054504",
"article-title": "Circulating protein fragments of cartilage and connective tissue degradation are diagnostic and prognostic markers of rheumatoid arthritis and ankylosing spondylitis",
"year": "2013",
"volume": "8",
"journal-title": "PLoS One"
},
{
"doi-asserted-by": "crossref",
"first-page": "44",
"issue": "1",
"author": "Siebuhr",
"key": "10.1016/j.joca.2019.11.002_bib40",
"DOI": "10.1016/j.joca.2013.10.020",
"article-title": "Identification and characterisation of osteoarthritis patients with inflammation derived tissue turnover",
"year": "2014",
"volume": "22",
"journal-title": "Osteoarthr Cartil"
},
{
"doi-asserted-by": "crossref",
"first-page": "221",
"issue": "3",
"author": "Yuji Yoshida",
"key": "10.1016/j.joca.2019.11.002_bib41",
"DOI": "10.1016/0306-9877(88)90147-8",
"article-title": "Interleukin 6 and rheumatoid arthritis",
"year": "1988",
"volume": "27",
"journal-title": "Med Hypotheses"
},
{
"doi-asserted-by": "crossref",
"first-page": "5173",
"issue": "22",
"author": "Suthaus",
"key": "10.1016/j.joca.2019.11.002_bib42",
"DOI": "10.1182/blood-2011-09-377705",
"article-title": "HHV8 encoded viral IL-6 collaborates with mouse IL-6 in MCD-like development in mice",
"year": "2012",
"volume": "119",
"journal-title": "Blood"
},
{
"doi-asserted-by": "crossref",
"first-page": "1",
"issue": "1",
"author": "Zhou",
"key": "10.1016/j.joca.2019.11.002_bib43",
"DOI": "10.1186/s12974-016-0607-6",
"article-title": "Interleukin-6: an emerging regulator of pathological pain",
"year": "2016",
"volume": "13",
"journal-title": "J Neuroinflammation"
},
{
"key": "10.1016/j.joca.2019.11.002_bib44",
"series-title": "Local Translation and Retrograde Axonal Transport of Creb Regulates Il-6-Induced Nociceptive Plasticity",
"first-page": "1",
"author": "Melemedjian",
"year": "2014"
},
{
"issue": "6",
"key": "10.1016/j.joca.2019.11.002_bib45",
"first-page": "1149",
"article-title": "Aggrecanase and Aggrecan degradation in osteoarthritis: a review",
"volume": "36",
"author": "Huang",
"year": "2008",
"journal-title": "J Int Med Res"
},
{
"doi-asserted-by": "crossref",
"first-page": "133",
"issue": "1",
"author": "Troeberg",
"key": "10.1016/j.joca.2019.11.002_bib46",
"DOI": "10.1016/j.bbapap.2011.06.020",
"article-title": "Proteases involved in cartilage matrix degradation in osteoarthritis",
"year": "2012",
"volume": "1824",
"journal-title": "Biochim Biophys Acta Protein Proteonomics"
},
{
"doi-asserted-by": "crossref",
"first-page": "1633",
"issue": "11",
"author": "Zhang",
"key": "10.1016/j.joca.2019.11.002_bib47",
"DOI": "10.1136/ard.2007.079574",
"article-title": "Differential Toll-like receptor-dependent collagenase expression in chondrocytes",
"year": "2008",
"volume": "67",
"journal-title": "Ann Rheum Dis"
},
{
"doi-asserted-by": "crossref",
"first-page": "2152",
"issue": "7",
"author": "Kim",
"key": "10.1016/j.joca.2019.11.002_bib48",
"DOI": "10.1002/art.21951",
"article-title": "The catabolic pathway mediated by toll-like receptors in human osteoarthritic chondrocytes",
"year": "2006",
"volume": "54",
"journal-title": "Arthritis Rheum"
},
{
"issue": "2018",
"key": "10.1016/j.joca.2019.11.002_bib49",
"article-title": "The anti-ADAMTS-5 nanobody®, M6495, protects against cartilage breakdown in cartilage and synovial joint tissue explant models",
"volume": "26",
"author": "Siebuhr",
"year": "2018",
"journal-title": "Osteoarthr Cartil"
},
{
"doi-asserted-by": "crossref",
"first-page": "2933",
"issue": "11",
"author": "Miller",
"key": "10.1016/j.joca.2019.11.002_bib50",
"DOI": "10.1002/art.39291",
"article-title": "Damage-associated molecular patterns generated in osteoarthritis directly excite murine nociceptive neurons through toll-like receptor 4",
"year": "2015",
"volume": "67",
"journal-title": "Arthritis Rheum"
}
],
"title": [
"Inflammation and joint destruction may be linked to the generation of cartilage metabolites of ADAMTS-5 through activation of toll-like receptors"
],
"link": [
{
"URL": "https://api.elsevier.com/content/article/PII:S106345841931266X?httpAccept=text/xml",
"content-type": "text/xml",
"content-version": "vor",
"intended-application": "text-mining"
},
{
"URL": "https://api.elsevier.com/content/article/PII:S106345841931266X?httpAccept=text/plain",
"content-type": "text/plain",
"content-version": "vor",
"intended-application": "text-mining"
}
],
"source": "Crossref",
"type": "journal-article",
"publisher": "Elsevier BV",
"journal-issue": {
"issue": "5",
"published-print": {
"date-parts": [
[
2020,
5
]
]
}
},
"volume": "28",
"references-count": 50,
"issn-type": [
{
"value": "2227-9717",
"type": "electronic"
},
{
"value": "VALUE",
"type": "PIPPO"
},
{
"value": "1063-4584",
"type": "pu"
}
],
"assertion": [
{
"value": "Elsevier",
"name": "publisher",
"label": "This article is maintained by"
},
{
"value": "Inflammation and joint destruction may be linked to the generation of cartilage metabolites of ADAMTS-5 through activation of toll-like receptors",
"name": "articletitle",
"label": "Article Title"
},
{
"value": "Osteoarthritis and Cartilage",
"name": "journaltitle",
"label": "Journal Title"
},
{
"value": "https://doi.org/10.1016/j.joca.2019.11.002",
"name": "articlelink",
"label": "CrossRef DOI link to publisher maintained version"
},
{
"value": "article",
"name": "content_type",
"label": "Content Type"
},
{
"value": "© 2019 Osteoarthritis Research Society International. Published by Elsevier Ltd.",
"name": "copyright",
"label": "Copyright"
}
],
"deposited": {
"date-parts": [
[
2022,
7,
9
]
],
"date-time": "2022-07-09T14:08:02Z",
"timestamp": 1657375682000
},
"language": "en",
"page": "658-668",
"short-container-title": [
"Osteoarthritis and Cartilage"
]
}

5921
dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/transform/synonyms.txt
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3193
dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/transform/terms.txt
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21
dhp-workflows/dhp-aggregation/src/test/scala/eu/dnetlib/dhp/collection/crossref/CrossrefMappingTest.scala Normal file
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@ -0,0 +1,21 @@
package eu.dnetlib.dhp.collection.crossref
import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.aggregation.AbstractVocabularyTest
import org.junit.jupiter.api.BeforeEach
import org.junit.jupiter.api.extension.ExtendWith
import org.mockito.junit.jupiter.MockitoExtension
import org.slf4j.{Logger, LoggerFactory}
@ExtendWith(Array(classOf[MockitoExtension]))
class CrossrefMappingTest extends AbstractVocabularyTest {
val logger: Logger = LoggerFactory.getLogger(Crossref2Oaf.getClass)
val mapper = new ObjectMapper()
@BeforeEach
def setUp(): Unit = {
super.setUpVocabulary()
}
}

85
dhp-workflows/dhp-aggregation/src/test/scala/eu/dnetlib/dhp/collection/mag/MAGMappingTest.scala Normal file
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@ -0,0 +1,85 @@
package eu.dnetlib.dhp.collection.mag
import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.schema.oaf.{Dataset, Publication, Result}
import org.apache.spark.sql.SparkSession
import org.junit.jupiter.api.Assertions._
import org.junit.jupiter.api.Test
class MAGMappingTest {
val mapper = new ObjectMapper()
def mappingTest(): Unit = {
val spark = SparkSession
.builder()
.appName("Test")
.master("local[*]")
.getOrCreate()
val s = new SparkMagOrganizationAS(null, null, null)
s.generateAS(spark, "/home/sandro/Downloads/mag_test", "/home/sandro/Downloads/mag_AS")
}
@Test
def mappingMagType(): Unit = {
checkResult[Publication](MagUtility.createResultFromType(null, null), invisible = false, "Other literature type")
checkResult[Publication](
MagUtility.createResultFromType(Some("BookChapter"), null),
invisible = false,
"Part of book or chapter of book"
)
checkResult[Publication](MagUtility.createResultFromType(Some("Book"), null), invisible = false, "Book")
checkResult[Publication](
MagUtility.createResultFromType(Some("Repository"), null),
invisible = true,
"Other literature type"
)
checkResult[Publication](MagUtility.createResultFromType(Some("Thesis"), null), invisible = false, "Thesis")
checkResult[Publication](MagUtility.createResultFromType(Some("Conference"), null), invisible = false, "Article")
checkResult[Publication](MagUtility.createResultFromType(Some("Journal"), null), invisible = false, "Journal")
checkResult[Dataset](MagUtility.createResultFromType(Some("Dataset"), null), invisible = false, "Dataset")
checkResult[Publication](
MagUtility.createResultFromType(Some("Patent"), Some("Patent Department of the Navy")),
invisible = false,
"Patent"
)
checkResult[Publication](
MagUtility.createResultFromType(Some("Patent"), Some("Brevet Department of the Navy")),
invisible = false,
"Patent"
)
checkResult[Publication](
MagUtility.createResultFromType(Some("Patent"), Some("Journal of the Navy")),
invisible = false,
"Journal"
)
checkResult[Publication](
MagUtility.createResultFromType(Some("Patent"), Some("Proceedings of the Navy")),
invisible = false,
"Article"
)
checkResult[Dataset](MagUtility.createResultFromType(Some("Dataset"), null), invisible = false, "Dataset")
assertNull(MagUtility.createResultFromType(Some("Patent"), null))
assertNull(MagUtility.createResultFromType(Some("Patent"), Some("Some name ")))
}
def checkResult[T](r: Result, invisible: Boolean, typeName: String): Unit = {
assertNotNull(r)
assertTrue(r.isInstanceOf[T])
assertNotNull(r.getDataInfo)
assertEquals(invisible, r.getDataInfo.getInvisible)
assertNotNull(r.getInstance())
assertTrue(r.getInstance().size() > 0)
assertNotNull(r.getInstance().get(0).getInstancetype)
assertEquals(typeName, r.getInstance().get(0).getInstancetype.getClassname)
}
}

28
dhp-workflows/dhp-doiboost/src/main/resources/eu/dnetlib/dhp/doiboost/convert_crossref_dump_to_oaf_params.json
View File

@ -1,6 +1,26 @@
[ [
{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the path of the OAF Orcid transformed", "paramRequired": true}, {
{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the source path ", "paramRequired": false}, "paramName": "t",
{"paramName":"m", "paramLongName":"master", "paramDescription": "the master name", "paramRequired": true} "paramLongName": "targetPath",
"paramDescription": "the path of the OAF Orcid transformed",
"paramRequired": true
},
{
"paramName": "i",
"paramLongName": "isLookupUrl",
"paramDescription": "the isLookup URL",
"paramRequired": true
},
{
"paramName": "s",
"paramLongName": "sourcePath",
"paramDescription": "the source path ",
"paramRequired": false
},
{
"paramName": "m",
"paramLongName": "master",
"paramDescription": "the master name",
"paramRequired": true
}
] ]

158
dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/crossref/Crossref2Oaf.scala
View File

@ -1,5 +1,6 @@
package eu.dnetlib.doiboost.crossref package eu.dnetlib.doiboost.crossref
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
import eu.dnetlib.dhp.schema.common.ModelConstants import eu.dnetlib.dhp.schema.common.ModelConstants
import eu.dnetlib.dhp.schema.oaf._ import eu.dnetlib.dhp.schema.oaf._
import eu.dnetlib.dhp.schema.oaf.utils.{GraphCleaningFunctions, IdentifierFactory, OafMapperUtils} import eu.dnetlib.dhp.schema.oaf.utils.{GraphCleaningFunctions, IdentifierFactory, OafMapperUtils}
@ -47,59 +48,6 @@ case object Crossref2Oaf {
json.extract[List[funderInfo]] json.extract[List[funderInfo]]
} }
val mappingCrossrefType = Map(
"book-section" -> "publication",
"book" -> "publication",
"book-chapter" -> "publication",
"book-part" -> "publication",
"book-series" -> "publication",
"book-set" -> "publication",
"book-track" -> "publication",
"edited-book" -> "publication",
"reference-book" -> "publication",
"monograph" -> "publication",
"journal-article" -> "publication",
"dissertation" -> "publication",
"other" -> "publication",
"peer-review" -> "publication",
"proceedings" -> "publication",
"proceedings-article" -> "publication",
"reference-entry" -> "publication",
"report" -> "publication",
"report-series" -> "publication",
"standard" -> "publication",
"standard-series" -> "publication",
"posted-content" -> "publication",
"dataset" -> "dataset"
)
val mappingCrossrefSubType = Map(
"book-section" -> "0013 Part of book or chapter of book",
"book" -> "0002 Book",
"book-chapter" -> "0013 Part of book or chapter of book",
"book-part" -> "0013 Part of book or chapter of book",
"book-series" -> "0002 Book",
"book-set" -> "0002 Book",
"book-track" -> "0002 Book",
"edited-book" -> "0002 Book",
"reference-book" -> "0002 Book",
"monograph" -> "0002 Book",
"journal-article" -> "0001 Article",
"dissertation" -> "0044 Thesis",
"other" -> "0038 Other literature type",
"peer-review" -> "0015 Review",
"proceedings" -> "0004 Conference object",
"proceedings-article" -> "0004 Conference object",
"reference-entry" -> "0013 Part of book or chapter of book",
"report" -> "0017 Report",
"report-series" -> "0017 Report",
"standard" -> "0038 Other literature type",
"standard-series" -> "0038 Other literature type",
"dataset" -> "0021 Dataset",
"preprint" -> "0016 Preprint",
"report" -> "0017 Report"
)
def getIrishId(doi: String): Option[String] = { def getIrishId(doi: String): Option[String] = {
val id = doi.split("/").last val id = doi.split("/").last
irishFunder irishFunder
@ -107,7 +55,7 @@ case object Crossref2Oaf {
.map(f => f.id) .map(f => f.id)
} }
def mappingResult(result: Result, json: JValue, cobjCategory: String, originalType: String): Result = { def mappingResult(result: Result, json: JValue, instanceType: Qualifier, originalType: String): Result = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
//MAPPING Crossref DOI into PID //MAPPING Crossref DOI into PID
@ -275,27 +223,20 @@ case object Crossref2Oaf {
instance.setAccessright( instance.setAccessright(
decideAccessRight(instance.getLicense, result.getDateofacceptance.getValue) decideAccessRight(instance.getLicense, result.getDateofacceptance.getValue)
) )
instance.setInstancetype( instance.setInstancetype(instanceType)
OafMapperUtils.qualifier(
cobjCategory.substring(0, 4),
cobjCategory.substring(5),
ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE
)
)
//ADD ORIGINAL TYPE to the mapping //ADD ORIGINAL TYPE to the mapping
val itm = new InstanceTypeMapping val itm = new InstanceTypeMapping
itm.setOriginalType(originalType) itm.setOriginalType(originalType)
itm.setVocabularyName(ModelConstants.OPENAIRE_COAR_RESOURCE_TYPES_3_1) itm.setVocabularyName(ModelConstants.OPENAIRE_COAR_RESOURCE_TYPES_3_1)
instance.setInstanceTypeMapping(List(itm).asJava) instance.setInstanceTypeMapping(List(itm).asJava)
result.setResourcetype( // result.setResourcetype(
OafMapperUtils.qualifier( // OafMapperUtils.qualifier(
cobjCategory.substring(0, 4), // cobjCategory.substring(0, 4),
cobjCategory.substring(5), // cobjCategory.substring(5),
ModelConstants.DNET_PUBLICATION_RESOURCE, // ModelConstants.DNET_PUBLICATION_RESOURCE,
ModelConstants.DNET_PUBLICATION_RESOURCE // ModelConstants.DNET_PUBLICATION_RESOURCE
) // )
) // )
instance.setCollectedfrom(createCrossrefCollectedFrom()) instance.setCollectedfrom(createCrossrefCollectedFrom())
if (StringUtils.isNotBlank(issuedDate)) { if (StringUtils.isNotBlank(issuedDate)) {
@ -354,7 +295,40 @@ case object Crossref2Oaf {
a a
} }
def convert(input: String): List[Oaf] = { /** *
* Use the vocabulary dnet:publication_resource to find a synonym to one of these terms and get the instance.type.
* Using the dnet:result_typologies vocabulary, we look up the instance.type synonym
* to generate one of the following main entities:
* - publication
* - dataset
* - software
* - otherresearchproduct
*
* @param resourceType
* @param vocabularies
* @return
*/
def getTypeQualifier(
resourceType: String,
vocabularies: VocabularyGroup
): (Qualifier, Qualifier, String) = {
if (resourceType != null && resourceType.nonEmpty) {
val typeQualifier =
vocabularies.getSynonymAsQualifier(ModelConstants.DNET_PUBLICATION_RESOURCE, resourceType)
if (typeQualifier != null)
return (
typeQualifier,
vocabularies.getSynonymAsQualifier(
ModelConstants.DNET_RESULT_TYPOLOGIES,
typeQualifier.getClassid
),
resourceType
)
}
null
}
def convert(input: String, vocabularies: VocabularyGroup): List[Oaf] = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
lazy val json: json4s.JValue = parse(input) lazy val json: json4s.JValue = parse(input)
@ -364,17 +338,16 @@ case object Crossref2Oaf {
val objectSubType = (json \ "subtype").extractOrElse[String](null) val objectSubType = (json \ "subtype").extractOrElse[String](null)
if (objectType == null) if (objectType == null)
return resultList return resultList
val typology = getTypeQualifier(objectType, vocabularies)
val result = generateItemFromType(objectType, objectSubType) if (typology == null)
return List()
val result = generateItemFromType(typology._2)
if (result == null) if (result == null)
return List() return List()
val cOBJCategory = mappingCrossrefSubType.getOrElse(
objectType,
mappingCrossrefSubType.getOrElse(objectSubType, "0038 Other literature type")
)
val originalType = if (mappingCrossrefSubType.contains(objectType)) objectType else objectSubType mappingResult(result, json, typology._1, typology._3)
mappingResult(result, json, cOBJCategory, originalType)
if (result == null || result.getId == null) if (result == null || result.getId == null)
return List() return List()
@ -392,7 +365,7 @@ case object Crossref2Oaf {
} }
result match { result match {
case publication: Publication => convertPublication(publication, json, cOBJCategory) case publication: Publication => convertPublication(publication, json, typology._1)
case dataset: Dataset => convertDataset(dataset) case dataset: Dataset => convertDataset(dataset)
} }
@ -622,12 +595,12 @@ case object Crossref2Oaf {
// TODO check if there are other info to map into the Dataset // TODO check if there are other info to map into the Dataset
} }
def convertPublication(publication: Publication, json: JValue, cobjCategory: String): Unit = { def convertPublication(publication: Publication, json: JValue, cobjCategory: Qualifier): Unit = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
val containerTitles = for { JString(ct) <- json \ "container-title" } yield ct val containerTitles = for { JString(ct) <- json \ "container-title" } yield ct
//Mapping book //Mapping book
if (cobjCategory.toLowerCase.contains("book")) { if (cobjCategory.getClassname.toLowerCase.contains("book")) {
val ISBN = for { JString(isbn) <- json \ "ISBN" } yield isbn val ISBN = for { JString(isbn) <- json \ "ISBN" } yield isbn
if (ISBN.nonEmpty && containerTitles.nonEmpty) { if (ISBN.nonEmpty && containerTitles.nonEmpty) {
val source = s"${containerTitles.head} ISBN: ${ISBN.head}" val source = s"${containerTitles.head} ISBN: ${ISBN.head}"
@ -708,12 +681,23 @@ case object Crossref2Oaf {
null null
} }
def generateItemFromType(objectType: String, objectSubType: String): Result = { def generateItemFromType(objectType: Qualifier): Result = {
if (mappingCrossrefType.contains(objectType)) { if (objectType.getClassid.equalsIgnoreCase("publication")) {
if (mappingCrossrefType(objectType).equalsIgnoreCase("publication")) val item = new Publication
return new Publication() item.setResourcetype(objectType)
if (mappingCrossrefType(objectType).equalsIgnoreCase("dataset")) return item
return new Dataset() } else if (objectType.getClassid.equalsIgnoreCase("dataset")) {
val item = new Dataset
item.setResourcetype(objectType)
return item
} else if (objectType.getClassid.equalsIgnoreCase("software")) {
val item = new Software
item.setResourcetype(objectType)
return item
} else if (objectType.getClassid.equalsIgnoreCase("OtherResearchProduct")) {
val item = new OtherResearchProduct
item.setResourcetype(objectType)
return item
} }
null null
} }

9
dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/crossref/SparkMapDumpIntoOAF.scala
View File

@ -1,8 +1,10 @@
package eu.dnetlib.doiboost.crossref package eu.dnetlib.doiboost.crossref
import eu.dnetlib.dhp.application.ArgumentApplicationParser import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
import eu.dnetlib.dhp.schema.oaf import eu.dnetlib.dhp.schema.oaf
import eu.dnetlib.dhp.schema.oaf.{Oaf, Publication, Relation, Dataset => OafDataset} import eu.dnetlib.dhp.schema.oaf.{Oaf, Publication, Relation, Dataset => OafDataset}
import eu.dnetlib.dhp.utils.ISLookupClientFactory
import org.apache.commons.io.IOUtils import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf import org.apache.spark.SparkConf
import org.apache.spark.sql._ import org.apache.spark.sql._
@ -40,11 +42,16 @@ object SparkMapDumpIntoOAF {
implicit val mapEncoderDatasets: Encoder[oaf.Dataset] = Encoders.kryo[OafDataset] implicit val mapEncoderDatasets: Encoder[oaf.Dataset] = Encoders.kryo[OafDataset]
val targetPath = parser.get("targetPath") val targetPath = parser.get("targetPath")
val isLookupUrl: String = parser.get("isLookupUrl")
logger.info("isLookupUrl: {}", isLookupUrl)
val isLookupService = ISLookupClientFactory.getLookUpService(isLookupUrl)
val vocabularies = VocabularyGroup.loadVocsFromIS(isLookupService)
require(vocabularies != null)
spark.read spark.read
.load(parser.get("sourcePath")) .load(parser.get("sourcePath"))
.as[CrossrefDT] .as[CrossrefDT]
.flatMap(k => Crossref2Oaf.convert(k.json)) .flatMap(k => Crossref2Oaf.convert(k.json, vocabularies))
.filter(o => o != null) .filter(o => o != null)
.write .write
.mode(SaveMode.Overwrite) .mode(SaveMode.Overwrite)

1
dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/uw/UnpayWallToOAF.scala
View File

@ -71,6 +71,7 @@ object UnpayWallToOAF {
} }
def convertToOAF(input: String): Publication = { def convertToOAF(input: String): Publication = {
val pub = new Publication val pub = new Publication
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats

50
dhp-workflows/dhp-doiboost/src/test/java/eu/dnetlib/dhp/aggregation/AbstractVocabularyTest.java Normal file
View File

@ -0,0 +1,50 @@
package eu.dnetlib.dhp.aggregation;
import static org.mockito.Mockito.lenient;
import java.io.IOException;
import java.util.Collections;
import java.util.List;
import java.util.Objects;
import org.apache.commons.io.IOUtils;
import org.mockito.Mock;
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup;
import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpException;
import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
public abstract class AbstractVocabularyTest {
@Mock
protected ISLookUpService isLookUpService;
protected VocabularyGroup vocabularies;
public void setUpVocabulary() throws ISLookUpException, IOException {
lenient().when(isLookUpService.quickSearchProfile(VocabularyGroup.VOCABULARIES_XQUERY)).thenReturn(vocs());
lenient()
.when(isLookUpService.quickSearchProfile(VocabularyGroup.VOCABULARY_SYNONYMS_XQUERY))
.thenReturn(synonyms());
vocabularies = VocabularyGroup.loadVocsFromIS(isLookUpService);
}
private static List<String> vocs() throws IOException {
return IOUtils
.readLines(
Objects
.requireNonNull(
AbstractVocabularyTest.class.getResourceAsStream("/eu/dnetlib/dhp/doiboost/terms.txt")));
}
private static List<String> synonyms() throws IOException {
return IOUtils
.readLines(
Objects
.requireNonNull(
AbstractVocabularyTest.class.getResourceAsStream("/eu/dnetlib/dhp/doiboost/synonyms.txt")));
}
}

1500
dhp-workflows/dhp-doiboost/src/test/resources/eu/dnetlib/dhp/doiboost/synonyms.txt Normal file
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1213
dhp-workflows/dhp-doiboost/src/test/resources/eu/dnetlib/dhp/doiboost/terms.txt Normal file
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File diff suppressed because it is too large Load Diff

2
dhp-workflows/dhp-doiboost/src/test/resources/eu/dnetlib/doiboost/crossref/preprint.json
View File

@ -57,7 +57,7 @@
] ]
] ]
}, },
"type": "posted-content", "type": "journal-article",
"URL": "http://dx.doi.org/10.1101/030080", "URL": "http://dx.doi.org/10.1101/030080",
"is-referenced-by-count": 2, "is-referenced-by-count": 2,
"link": [ "link": [

100
dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/dhp/doiboost/crossref/CrossrefMappingTest.scala
View File

@ -1,33 +1,44 @@
package eu.dnetlib.dhp.doiboost.crossref package eu.dnetlib.dhp.doiboost.crossref
import com.fasterxml.jackson.databind.SerializationFeature
import eu.dnetlib.dhp.aggregation.AbstractVocabularyTest
import eu.dnetlib.dhp.schema.common.ModelConstants import eu.dnetlib.dhp.schema.common.ModelConstants
import eu.dnetlib.dhp.schema.oaf._ import eu.dnetlib.dhp.schema.oaf._
import eu.dnetlib.dhp.utils.DHPUtils import eu.dnetlib.dhp.utils.DHPUtils
import eu.dnetlib.doiboost.crossref.Crossref2Oaf import eu.dnetlib.doiboost.crossref.Crossref2Oaf
import org.codehaus.jackson.map.{ObjectMapper, SerializationConfig}
import org.json4s import org.json4s
import com.fasterxml.jackson.databind.ObjectMapper
import org.json4s.JsonAST.{JField, JObject, JString} import org.json4s.JsonAST.{JField, JObject, JString}
import org.json4s.{DefaultFormats, JValue} import org.json4s.{DefaultFormats, JValue}
import org.json4s.jackson.JsonMethods import org.json4s.jackson.JsonMethods
import org.junit.jupiter.api.Assertions._ import org.junit.jupiter.api.Assertions._
import org.junit.jupiter.api.Test import org.junit.jupiter.api.extension.ExtendWith
import org.junit.jupiter.api.{BeforeEach, Test}
import org.mockito.junit.jupiter.MockitoExtension
import org.slf4j.{Logger, LoggerFactory} import org.slf4j.{Logger, LoggerFactory}
import java.nio.file.Files
import scala.collection.JavaConverters._ import scala.collection.JavaConverters._
import scala.io.Source import scala.io.Source
import scala.util.matching.Regex import scala.util.matching.Regex
class CrossrefMappingTest { @ExtendWith(Array(classOf[MockitoExtension]))
class CrossrefMappingTest extends AbstractVocabularyTest {
val logger: Logger = LoggerFactory.getLogger(Crossref2Oaf.getClass) val logger: Logger = LoggerFactory.getLogger(Crossref2Oaf.getClass)
val mapper = new ObjectMapper() val mapper = new ObjectMapper()
@BeforeEach
def setUp(): Unit = {
super.setUpVocabulary()
}
@Test @Test
def testMissingAuthorParser(): Unit = { def testMissingAuthorParser(): Unit = {
val json: String = Source val json: String = Source
.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/s41567-022-01757-y.json")) .fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/s41567-022-01757-y.json"))
.mkString .mkString
val result = Crossref2Oaf.convert(json) val result = Crossref2Oaf.convert(json, vocabularies)
result result
.filter(o => o.isInstanceOf[Publication]) .filter(o => o.isInstanceOf[Publication])
.map(p => p.asInstanceOf[Publication]) .map(p => p.asInstanceOf[Publication])
@ -50,13 +61,13 @@ class CrossrefMappingTest {
for (line <- funder_doi.linesWithSeparators.map(l => l.stripLineEnd)) { for (line <- funder_doi.linesWithSeparators.map(l => l.stripLineEnd)) {
val json = template.replace("%s", line) val json = template.replace("%s", line)
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
checkRelation(resultList) checkRelation(resultList)
} }
for (line <- funder_name.linesWithSeparators.map(l => l.stripLineEnd)) { for (line <- funder_name.linesWithSeparators.map(l => l.stripLineEnd)) {
val json = template.replace("%s", line) val json = template.replace("%s", line)
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
checkRelation(resultList) checkRelation(resultList)
} }
@ -96,7 +107,7 @@ class CrossrefMappingTest {
Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/issue_date.json")).mkString Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/issue_date.json")).mkString
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty) assertFalse(json.isEmpty)
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
val items = resultList.filter(p => p.isInstanceOf[Result]) val items = resultList.filter(p => p.isInstanceOf[Result])
@ -115,14 +126,13 @@ class CrossrefMappingTest {
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty) assertFalse(json.isEmpty)
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
val items = resultList.filter(p => p.isInstanceOf[Result]) val items = resultList.filter(p => p.isInstanceOf[Result])
mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT) items.foreach(p => println(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(p)))
items.foreach(p => println(mapper.writeValueAsString(p)))
} }
@ -142,7 +152,7 @@ class CrossrefMappingTest {
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty) assertFalse(json.isEmpty)
val result: List[Oaf] = Crossref2Oaf.convert(json) val result: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(result.nonEmpty) assertTrue(result.nonEmpty)
@ -163,8 +173,7 @@ class CrossrefMappingTest {
assertEquals(doisReference.size, relationList.size) assertEquals(doisReference.size, relationList.size)
mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT) relationList.foreach(p => println(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(p)))
relationList.foreach(p => println(mapper.writeValueAsString(p)))
} }
@Test @Test
@ -178,14 +187,13 @@ class CrossrefMappingTest {
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
val items = resultList.filter(p => p.isInstanceOf[Result]) val items = resultList.filter(p => p.isInstanceOf[Result])
mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT) items.foreach(p => println(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(p)))
items.foreach(p => println(mapper.writeValueAsString(p)))
} }
@ -194,18 +202,17 @@ class CrossrefMappingTest {
val json = Source val json = Source
.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/prwTest.json")) .fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/prwTest.json"))
.mkString .mkString
mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT)
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
val items = resultList.filter(p => p.isInstanceOf[Result]) val items = resultList.filter(p => p.isInstanceOf[Result])
items.foreach(p => logger.info(mapper.writeValueAsString(p))) items.foreach(p => logger.info(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(p)))
} }
@ -235,7 +242,7 @@ class CrossrefMappingTest {
assertFalse(json.isEmpty) assertFalse(json.isEmpty)
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
val rels: List[Relation] = val rels: List[Relation] =
@ -255,7 +262,7 @@ class CrossrefMappingTest {
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -266,7 +273,7 @@ class CrossrefMappingTest {
val result: Result = items.head.asInstanceOf[Result] val result: Result = items.head.asInstanceOf[Result]
assertNotNull(result) assertNotNull(result)
logger.info(mapper.writeValueAsString(result)); logger.info(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(result));
assertNotNull(result.getDataInfo, "Datainfo test not null Failed"); assertNotNull(result.getDataInfo, "Datainfo test not null Failed");
assertNotNull( assertNotNull(
@ -331,7 +338,7 @@ class CrossrefMappingTest {
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -415,7 +422,7 @@ class CrossrefMappingTest {
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -463,7 +470,7 @@ class CrossrefMappingTest {
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -542,7 +549,7 @@ class CrossrefMappingTest {
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -568,7 +575,7 @@ class CrossrefMappingTest {
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -578,7 +585,8 @@ class CrossrefMappingTest {
assert(items.size == 1) assert(items.size == 1)
val result: Result = items.head.asInstanceOf[Publication] val result: Result = items.head.asInstanceOf[Publication]
assertNotNull(result) assertNotNull(result)
logger.info(mapper.writeValueAsString(result));
logger.info(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(result));
} }
@Test @Test
@ -591,7 +599,7 @@ class CrossrefMappingTest {
val line: String = val line: String =
"\"funder\": [{\"name\": \"Wellcome Trust Masters Fellowship\",\"award\": [\"090633\"]}]," "\"funder\": [{\"name\": \"Wellcome Trust Masters Fellowship\",\"award\": [\"090633\"]}],"
val json = template.replace("%s", line) val json = template.replace("%s", line)
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
val items = resultList.filter(p => p.isInstanceOf[Publication]) val items = resultList.filter(p => p.isInstanceOf[Publication])
val result: Result = items.head.asInstanceOf[Publication] val result: Result = items.head.asInstanceOf[Publication]
@ -610,7 +618,7 @@ class CrossrefMappingTest {
.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/article.json")) .fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/article.json"))
.mkString .mkString
val resultList: List[Oaf] = Crossref2Oaf.convert(template) val resultList: List[Oaf] = Crossref2Oaf.convert(template, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
val items = resultList.filter(p => p.isInstanceOf[Publication]) val items = resultList.filter(p => p.isInstanceOf[Publication])
val result: Result = items.head.asInstanceOf[Publication] val result: Result = items.head.asInstanceOf[Publication]
@ -634,14 +642,13 @@ class CrossrefMappingTest {
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
val item: Result = resultList.filter(p => p.isInstanceOf[Result]).head.asInstanceOf[Result] val item: Result = resultList.filter(p => p.isInstanceOf[Result]).head.asInstanceOf[Result]
mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT) println(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(item))
println(mapper.writeValueAsString(item))
assertTrue( assertTrue(
item.getInstance().asScala exists (i => i.getLicense.getValue.equals("https://www.springer.com/vor")) item.getInstance().asScala exists (i => i.getLicense.getValue.equals("https://www.springer.com/vor"))
@ -664,7 +671,7 @@ class CrossrefMappingTest {
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -681,8 +688,8 @@ class CrossrefMappingTest {
assertTrue( assertTrue(
item.getInstance().asScala exists (i => i.getAccessright.getOpenAccessRoute == OpenAccessRoute.hybrid) item.getInstance().asScala exists (i => i.getAccessright.getOpenAccessRoute == OpenAccessRoute.hybrid)
) )
mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT)
println(mapper.writeValueAsString(item)) println(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(item))
} }
@ -699,7 +706,7 @@ class CrossrefMappingTest {
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -716,8 +723,7 @@ class CrossrefMappingTest {
assertTrue( assertTrue(
item.getInstance().asScala exists (i => i.getAccessright.getOpenAccessRoute == OpenAccessRoute.hybrid) item.getInstance().asScala exists (i => i.getAccessright.getOpenAccessRoute == OpenAccessRoute.hybrid)
) )
mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT) println(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(item))
println(mapper.writeValueAsString(item))
} }
@ -734,7 +740,7 @@ class CrossrefMappingTest {
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -751,8 +757,7 @@ class CrossrefMappingTest {
item.getInstance().asScala exists (i => i.getAccessright.getClassid.equals("EMBARGO")) item.getInstance().asScala exists (i => i.getAccessright.getClassid.equals("EMBARGO"))
) )
assertTrue(item.getInstance().asScala exists (i => i.getAccessright.getOpenAccessRoute == null)) assertTrue(item.getInstance().asScala exists (i => i.getAccessright.getOpenAccessRoute == null))
mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT) println(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(item))
println(mapper.writeValueAsString(item))
} }
@ -769,7 +774,7 @@ class CrossrefMappingTest {
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -786,8 +791,8 @@ class CrossrefMappingTest {
item.getInstance().asScala exists (i => i.getAccessright.getClassid.equals("EMBARGO")) item.getInstance().asScala exists (i => i.getAccessright.getClassid.equals("EMBARGO"))
) )
assertTrue(item.getInstance().asScala exists (i => i.getAccessright.getOpenAccessRoute == null)) assertTrue(item.getInstance().asScala exists (i => i.getAccessright.getOpenAccessRoute == null))
mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT)
println(mapper.writeValueAsString(item)) println(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(item))
} }
@ -802,7 +807,7 @@ class CrossrefMappingTest {
assertNotNull(json) assertNotNull(json)
assertFalse(json.isEmpty); assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json) val resultList: List[Oaf] = Crossref2Oaf.convert(json, vocabularies)
assertTrue(resultList.nonEmpty) assertTrue(resultList.nonEmpty)
@ -812,9 +817,8 @@ class CrossrefMappingTest {
assertEquals(1, item.getInstance().get(0).getUrl().size()) assertEquals(1, item.getInstance().get(0).getUrl().size())
assertEquals( assertEquals(
"https://doi.org/10.1016/j.jas.2019.105013", "https://doi.org/10.1016/j.jas.2019.105013",
item.getInstance().get(0).getUrl().get(0) item.getInstance().get(0).getUrl.get(0)
) )
//println(mapper.writeValueAsString(item))
} }