code refactor, created and moved scala code on the correct maven folder under src/main/scala and src/test/scala

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

@@ -4,20 +4,19 @@ import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf._
 import eu.dnetlib.dhp.schema.oaf.utils.{IdentifierFactory, OafMapperUtils}
 import eu.dnetlib.dhp.utils.DHPUtils
-import eu.dnetlib.doiboost.DoiBoostMappingUtil.{decideAccessRight, _}
+import eu.dnetlib.doiboost.DoiBoostMappingUtil
+import eu.dnetlib.doiboost.DoiBoostMappingUtil._
 import org.apache.commons.lang.StringUtils
 import org.json4s
 import org.json4s.DefaultFormats
-import org.json4s.JsonAST.{JValue, _}
+import org.json4s.JsonAST._
 import org.json4s.jackson.JsonMethods._
 import org.slf4j.{Logger, LoggerFactory}
 
+import java.util
 import scala.collection.JavaConverters._
 import scala.collection.mutable
 import scala.util.matching.Regex
-import java.util
-
-import eu.dnetlib.doiboost.DoiBoostMappingUtil
 
 case class CrossrefDT(doi: String, json:String, timestamp: Long) {}
 

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

@@ -6,7 +6,7 @@ import org.apache.commons.io.IOUtils
 import org.apache.hadoop.io.{IntWritable, Text}
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.expressions.Aggregator
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql.{Dataset, Encoder, SaveMode, SparkSession}
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
@@ -17,12 +17,12 @@ object CrossrefDataset {
   val logger: Logger = LoggerFactory.getLogger(SparkMapDumpIntoOAF.getClass)
 
 
-  def to_item(input:String):CrossrefDT = {
+  def to_item(input: String): CrossrefDT = {
 
     implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
     lazy val json: json4s.JValue = parse(input)
-    val ts:Long = (json \ "indexed" \ "timestamp").extract[Long]
-    val doi:String  = DoiBoostMappingUtil.normalizeDoi((json \ "DOI").extract[String])
+    val ts: Long = (json \ "indexed" \ "timestamp").extract[Long]
+    val doi: String = DoiBoostMappingUtil.normalizeDoi((json \ "DOI").extract[String])
     CrossrefDT(doi, input, ts)
 
   }
@@ -30,7 +30,6 @@ object CrossrefDataset {
   def main(args: Array[String]): Unit = {
 
 
-
     val conf: SparkConf = new SparkConf()
     val parser = new ArgumentApplicationParser(IOUtils.toString(CrossrefDataset.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/crossref_to_dataset_params.json")))
     parser.parseArgument(args)
@@ -54,7 +53,7 @@ object CrossrefDataset {
           return b
 
 
-        if(a.timestamp >b.timestamp) {
+        if (a.timestamp > b.timestamp) {
           return a
         }
         b
@@ -66,7 +65,7 @@ object CrossrefDataset {
         if (a == null)
           return b
 
-        if(a.timestamp >b.timestamp) {
+        if (a.timestamp > b.timestamp) {
           return a
         }
         b
@@ -79,20 +78,20 @@ object CrossrefDataset {
       override def finish(reduction: CrossrefDT): CrossrefDT = reduction
     }
 
-    val workingPath:String = parser.get("workingPath")
+    val workingPath: String = parser.get("workingPath")
 
 
-    val main_ds:Dataset[CrossrefDT] = spark.read.load(s"$workingPath/crossref_ds").as[CrossrefDT]
+    val main_ds: Dataset[CrossrefDT] = spark.read.load(s"$workingPath/crossref_ds").as[CrossrefDT]
 
 
     val update =
-      spark.createDataset(spark.sparkContext.sequenceFile(s"$workingPath/index_update",  classOf[IntWritable], classOf[Text])
-        .map(i =>CrossrefImporter.decompressBlob(i._2.toString))
-        .map(i =>to_item(i)))
+      spark.createDataset(spark.sparkContext.sequenceFile(s"$workingPath/index_update", classOf[IntWritable], classOf[Text])
+        .map(i => CrossrefImporter.decompressBlob(i._2.toString))
+        .map(i => to_item(i)))
 
     main_ds.union(update).groupByKey(_.doi)
       .agg(crossrefAggregator.toColumn)
-      .map(s=>s._2)
+      .map(s => s._2)
       .write.mode(SaveMode.Overwrite).save(s"$workingPath/crossref_ds_updated")
 
   }

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

@@ -2,17 +2,12 @@ package eu.dnetlib.doiboost.crossref
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
-import eu.dnetlib.doiboost.crossref.CrossrefDataset.to_item
-import eu.dnetlib.doiboost.crossref.UnpackCrtossrefEntries.getClass
-import org.apache.hadoop.io.{IntWritable, Text}
-import org.apache.hadoop.io.compress.GzipCodec
 import org.apache.spark.rdd.RDD
-import org.apache.spark.{SparkConf, SparkContext}
 import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.{SparkConf, SparkContext}
 import org.json4s
 import org.json4s.DefaultFormats
-import org.json4s.JsonAST.JArray
-import org.json4s.jackson.JsonMethods.{compact, parse, render}
+import org.json4s.jackson.JsonMethods.parse
 import org.slf4j.{Logger, LoggerFactory}
 
 import scala.io.Source
@@ -24,11 +19,10 @@ object GenerateCrossrefDataset {
   implicit val mrEncoder: Encoder[CrossrefDT] = Encoders.kryo[CrossrefDT]
 
 
-
   def crossrefElement(meta: String): CrossrefDT = {
     implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
     lazy val json: json4s.JValue = parse(meta)
-    val doi:String = DoiBoostMappingUtil.normalizeDoi((json \ "DOI").extract[String])
+    val doi: String = DoiBoostMappingUtil.normalizeDoi((json \ "DOI").extract[String])
     val timestamp: Long = (json \ "indexed" \ "timestamp").extract[Long]
     CrossrefDT(doi, meta, timestamp)
 
@@ -51,14 +45,14 @@ object GenerateCrossrefDataset {
     import spark.implicits._
 
 
-    val tmp : RDD[String] = sc.textFile(sourcePath,6000)
+    val tmp: RDD[String] = sc.textFile(sourcePath, 6000)
 
     spark.createDataset(tmp)
       .map(entry => crossrefElement(entry))
       .write.mode(SaveMode.Overwrite).save(targetPath)
-//               .map(meta => crossrefElement(meta))
-//               .toDS.as[CrossrefDT]
-//              .write.mode(SaveMode.Overwrite).save(targetPath)
+    //               .map(meta => crossrefElement(meta))
+    //               .toDS.as[CrossrefDT]
+    //              .write.mode(SaveMode.Overwrite).save(targetPath)
 
   }
 

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

@@ -4,10 +4,8 @@ import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.schema.oaf
 import eu.dnetlib.dhp.schema.oaf.{Oaf, Publication, Relation, Dataset => OafDataset}
 import org.apache.commons.io.IOUtils
-
 import org.apache.spark.SparkConf
-
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
 import org.slf4j.{Logger, LoggerFactory}
 
 

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

@@ -2,8 +2,8 @@ package eu.dnetlib.doiboost.crossref
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import org.apache.hadoop.io.compress.GzipCodec
+import org.apache.spark.sql.SparkSession
 import org.apache.spark.{SparkConf, SparkContext}
-import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.JsonAST.JArray
@@ -17,9 +17,7 @@ object UnpackCrtossrefEntries {
   val log: Logger = LoggerFactory.getLogger(UnpackCrtossrefEntries.getClass)
 
 
-
-
-  def extractDump(input:String):List[String] = {
+  def extractDump(input: String): List[String] = {
     implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
     lazy val json: json4s.JValue = parse(input)
 
@@ -30,7 +28,6 @@ object UnpackCrtossrefEntries {
   }
 
 
-
   def main(args: Array[String]): Unit = {
     val conf = new SparkConf
     val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/crossref_dump_reader/generate_dataset_params.json")).mkString)
@@ -45,7 +42,7 @@ object UnpackCrtossrefEntries {
       .getOrCreate()
     val sc: SparkContext = spark.sparkContext
 
-    sc.wholeTextFiles(sourcePath,6000).flatMap(d =>extractDump(d._2))
+    sc.wholeTextFiles(sourcePath, 6000).flatMap(d => extractDump(d._2))
       .saveAsTextFile(targetPath, classOf[GzipCodec])
 
 

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

@@ -5,10 +5,10 @@ import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory
 import eu.dnetlib.dhp.schema.oaf.{Instance, Journal, Publication, StructuredProperty}
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
+import eu.dnetlib.doiboost.DoiBoostMappingUtil._
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
-import eu.dnetlib.doiboost.DoiBoostMappingUtil._
 
 import scala.collection.JavaConverters._
 import scala.collection.mutable

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

@@ -3,8 +3,8 @@ package eu.dnetlib.doiboost.mag
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
-import org.apache.spark.sql.{SaveMode, SparkSession}
 import org.apache.spark.sql.types._
+import org.apache.spark.sql.{SaveMode, SparkSession}
 import org.slf4j.{Logger, LoggerFactory}
 
 object SparkImportMagIntoDataset {
@@ -24,13 +24,13 @@ object SparkImportMagIntoDataset {
     "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")),
+    "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")),
+    "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")),
@@ -75,7 +75,6 @@ object SparkImportMagIntoDataset {
         .master(parser.get("master")).getOrCreate()
 
 
-
     stream.foreach { case (k, v) =>
       val s: StructType = getSchema(k)
       val df = spark.read

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

@@ -5,19 +5,16 @@ import eu.dnetlib.dhp.schema.oaf.Publication
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
-import org.apache.spark.rdd.RDD
-import org.apache.spark.sql.functions._
+import org.apache.spark.sql.functions.{col, collect_list, struct}
 import org.apache.spark.sql._
 import org.slf4j.{Logger, LoggerFactory}
-
 import scala.collection.JavaConverters._
-
 object SparkProcessMAG {
 
-  def getDistinctResults (d:Dataset[MagPapers]):Dataset[MagPapers]={
+  def getDistinctResults(d: Dataset[MagPapers]): Dataset[MagPapers] = {
     d.where(col("Doi").isNotNull)
       .groupByKey(mp => DoiBoostMappingUtil.normalizeDoi(mp.Doi))(Encoders.STRING)
-      .reduceGroups((p1:MagPapers,p2:MagPapers) => ConversionUtil.choiceLatestMagArtitcle(p1,p2))
+      .reduceGroups((p1: MagPapers, p2: MagPapers) => ConversionUtil.choiceLatestMagArtitcle(p1, p2))
       .map(_._2)(Encoders.product[MagPapers])
       .map(mp => {
         new MagPapers(mp.PaperId, mp.Rank, DoiBoostMappingUtil.normalizeDoi(mp.Doi),
@@ -98,13 +95,13 @@ object SparkProcessMAG {
 
     var magPubs: Dataset[(String, Publication)] =
       spark.read.load(s"$workingPath/merge_step_2").as[Publication]
-      .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
+        .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
 
 
     val conference = spark.read.load(s"$sourcePath/ConferenceInstances")
-      .select($"ConferenceInstanceId".as("ci"), $"DisplayName", $"Location", $"StartDate",$"EndDate" )
+      .select($"ConferenceInstanceId".as("ci"), $"DisplayName", $"Location", $"StartDate", $"EndDate")
     val conferenceInstance = conference.joinWith(papers, papers("ConferenceInstanceId").equalTo(conference("ci")))
-      .select($"_1.ci", $"_1.DisplayName", $"_1.Location", $"_1.StartDate",$"_1.EndDate", $"_2.PaperId").as[MagConferenceInstance]
+      .select($"_1.ci", $"_1.DisplayName", $"_1.Location", $"_1.StartDate", $"_1.EndDate", $"_2.PaperId").as[MagConferenceInstance]
 
 
     magPubs.joinWith(conferenceInstance, col("_1").equalTo(conferenceInstance("PaperId")), "left")
@@ -122,7 +119,7 @@ object SparkProcessMAG {
 
     magPubs.joinWith(paperAbstract, col("_1").equalTo(paperAbstract("PaperId")), "left")
       .map(item => ConversionUtil.updatePubsWithDescription(item)
-    ).write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_4")
+      ).write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_4")
 
 
     logger.info("Phase 7) Enrich Publication with FieldOfStudy")
@@ -148,11 +145,10 @@ object SparkProcessMAG {
     spark.read.load(s"$workingPath/mag_publication").as[Publication]
       .filter(p => p.getId == null)
       .groupByKey(p => p.getId)
-      .reduceGroups((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
+      .reduceGroups((a: Publication, b: Publication) => ConversionUtil.mergePublication(a, b))
       .map(_._2)
       .write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
 
 
-
   }
 }

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/orcid/ORCIDToOAF.scala

@@ -4,17 +4,16 @@ import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory
 import eu.dnetlib.dhp.schema.oaf.{Author, DataInfo, Publication}
-import eu.dnetlib.dhp.schema.orcid.{AuthorData, OrcidDOI}
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
 import eu.dnetlib.doiboost.DoiBoostMappingUtil.{createSP, generateDataInfo}
 import org.apache.commons.lang.StringUtils
-import org.slf4j.{Logger, LoggerFactory}
-
-import scala.collection.JavaConverters._
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.JsonAST._
 import org.json4s.jackson.JsonMethods._
+import org.slf4j.{Logger, LoggerFactory}
+
+import scala.collection.JavaConverters._
 
 
 case class ORCIDItem(doi:String, authors:List[OrcidAuthor]){}

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/orcid/SparkConvertORCIDToOAF.scala

@@ -11,10 +11,10 @@ object SparkConvertORCIDToOAF {
   val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
 
 
-  def run(spark:SparkSession, workingPath:String, targetPath:String) :Unit = {
+  def run(spark: SparkSession, workingPath: String, targetPath: String): Unit = {
     implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
     import spark.implicits._
-    val dataset: Dataset[ORCIDItem] =spark.read.load(s"$workingPath/orcidworksWithAuthor").as[ORCIDItem]
+    val dataset: Dataset[ORCIDItem] = spark.read.load(s"$workingPath/orcidworksWithAuthor").as[ORCIDItem]
 
     logger.info("Converting ORCID to OAF")
     dataset.map(o => ORCIDToOAF.convertTOOAF(o)).write.mode(SaveMode.Overwrite).save(targetPath)
@@ -35,8 +35,8 @@ object SparkConvertORCIDToOAF {
     val workingPath = parser.get("workingPath")
     val targetPath = parser.get("targetPath")
 
-   run(spark,workingPath, targetPath)
+    run(spark, workingPath, targetPath)
 
   }
 
-}
+}

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/orcid/SparkPreprocessORCID.scala

@@ -1,48 +1,45 @@
 package eu.dnetlib.doiboost.orcid
 
-import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper}
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.oa.merge.AuthorMerger
 import eu.dnetlib.dhp.schema.oaf.Publication
-import eu.dnetlib.dhp.schema.orcid.OrcidDOI
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.rdd.RDD
-import org.apache.spark.sql.functions._
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql.functions.{col, collect_list}
+import org.apache.spark.sql._
 import org.slf4j.{Logger, LoggerFactory}
 
 object SparkPreprocessORCID {
   val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
 
-    def fixORCIDItem(item :ORCIDItem):ORCIDItem = {
-      ORCIDItem(item.doi, item.authors.groupBy(_.oid).map(_._2.head).toList)
+  def fixORCIDItem(item: ORCIDItem): ORCIDItem = {
+    ORCIDItem(item.doi, item.authors.groupBy(_.oid).map(_._2.head).toList)
 
   }
 
 
-  def run(spark:SparkSession,sourcePath:String,workingPath:String):Unit = {
+  def run(spark: SparkSession, sourcePath: String, workingPath: String): Unit = {
     import spark.implicits._
     implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
 
-    val inputRDD:RDD[OrcidAuthor]  = spark.sparkContext.textFile(s"$sourcePath/authors").map(s => ORCIDToOAF.convertORCIDAuthor(s)).filter(s => s!= null).filter(s => ORCIDToOAF.authorValid(s))
+    val inputRDD: RDD[OrcidAuthor] = spark.sparkContext.textFile(s"$sourcePath/authors").map(s => ORCIDToOAF.convertORCIDAuthor(s)).filter(s => s != null).filter(s => ORCIDToOAF.authorValid(s))
 
     spark.createDataset(inputRDD).as[OrcidAuthor].write.mode(SaveMode.Overwrite).save(s"$workingPath/author")
 
-    val res = spark.sparkContext.textFile(s"$sourcePath/works").flatMap(s => ORCIDToOAF.extractDOIWorks(s)).filter(s => s!= null)
+    val res = spark.sparkContext.textFile(s"$sourcePath/works").flatMap(s => ORCIDToOAF.extractDOIWorks(s)).filter(s => s != null)
 
     spark.createDataset(res).as[OrcidWork].write.mode(SaveMode.Overwrite).save(s"$workingPath/works")
 
-    val authors :Dataset[OrcidAuthor] = spark.read.load(s"$workingPath/author").as[OrcidAuthor]
+    val authors: Dataset[OrcidAuthor] = spark.read.load(s"$workingPath/author").as[OrcidAuthor]
 
-    val works :Dataset[OrcidWork] = spark.read.load(s"$workingPath/works").as[OrcidWork]
+    val works: Dataset[OrcidWork] = spark.read.load(s"$workingPath/works").as[OrcidWork]
 
     works.joinWith(authors, authors("oid").equalTo(works("oid")))
-      .map(i =>{
+      .map(i => {
         val doi = i._1.doi
         val author = i._2
-      (doi, author)
-    }).groupBy(col("_1").alias("doi"))
+        (doi, author)
+      }).groupBy(col("_1").alias("doi"))
       .agg(collect_list(col("_2")).alias("authors")).as[ORCIDItem]
       .map(s => fixORCIDItem(s))
       .write.mode(SaveMode.Overwrite).save(s"$workingPath/orcidworksWithAuthor")
@@ -67,4 +64,4 @@ object SparkPreprocessORCID {
 
   }
 
-}
+}

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/uw/SparkMapUnpayWallToOAF.scala

@@ -1,16 +1,14 @@
 package eu.dnetlib.doiboost.uw
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-
 import eu.dnetlib.dhp.schema.oaf.Publication
 import eu.dnetlib.doiboost.crossref.SparkMapDumpIntoOAF
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.rdd.RDD
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
 import org.slf4j.{Logger, LoggerFactory}
 
-
 object SparkMapUnpayWallToOAF {
 
   def main(args: Array[String]): Unit = {
@@ -32,11 +30,11 @@ object SparkMapUnpayWallToOAF {
 
     val sourcePath = parser.get("sourcePath")
     val targetPath = parser.get("targetPath")
-    val inputRDD:RDD[String] = spark.sparkContext.textFile(s"$sourcePath")
+    val inputRDD: RDD[String] = spark.sparkContext.textFile(s"$sourcePath")
 
     logger.info("Converting UnpayWall to OAF")
 
-    val d:Dataset[Publication] = spark.createDataset(inputRDD.map(UnpayWallToOAF.convertToOAF).filter(p=>p!=null)).as[Publication]
+    val d: Dataset[Publication] = spark.createDataset(inputRDD.map(UnpayWallToOAF.convertToOAF).filter(p => p != null)).as[Publication]
     d.write.mode(SaveMode.Overwrite).save(targetPath)
   }
 

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

@@ -4,14 +4,13 @@ import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory
 import eu.dnetlib.dhp.schema.oaf.{AccessRight, Instance, OpenAccessRoute, Publication}
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
+import eu.dnetlib.doiboost.DoiBoostMappingUtil._
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
 import org.slf4j.{Logger, LoggerFactory}
 
 import scala.collection.JavaConverters._
-import eu.dnetlib.doiboost.DoiBoostMappingUtil._
-import eu.dnetlib.doiboost.uw.UnpayWallToOAF.get_unpaywall_color
 
 
 

dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/doiboost/DoiBoostHostedByMapTest.scala

@@ -1,4 +1,4 @@
-package eu.dnetlib.dhp.doiboost
+package eu.dnetlib.doiboost
 
 import eu.dnetlib.dhp.schema.oaf.{Publication, Dataset => OafDataset}
 import eu.dnetlib.doiboost.{DoiBoostMappingUtil, HostedByItemType}

dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/doiboost/NormalizeDoiTest.scala

@@ -1,4 +1,4 @@
-package eu.dnetlib.dhp.doiboost
+package eu.dnetlib.doiboost
 
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
 import org.junit.jupiter.api.Test

dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/doiboost/mag/MAGMappingTest.scala

@@ -3,9 +3,9 @@ package eu.dnetlib.doiboost.mag
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{Dataset, SparkSession}
 import org.codehaus.jackson.map.ObjectMapper
+import org.json4s.DefaultFormats
 import org.junit.jupiter.api.Assertions._
 import org.junit.jupiter.api.Test
-import org.json4s.DefaultFormats
 import org.slf4j.{Logger, LoggerFactory}
 
 import java.sql.Timestamp

dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/doiboost/orcid/MappingORCIDToOAFTest.scala

@@ -10,9 +10,8 @@ import org.junit.jupiter.api.io.TempDir
 import org.slf4j.{Logger, LoggerFactory}
 
 import java.nio.file.Path
-import scala.io.Source
-
 import scala.collection.JavaConversions._
+import scala.io.Source
 
 class MappingORCIDToOAFTest {
   val logger: Logger = LoggerFactory.getLogger(ORCIDToOAF.getClass)

dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/doiboost/uw/UnpayWallMappingTest.scala

@@ -3,11 +3,11 @@ package eu.dnetlib.doiboost.uw
 
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.schema.oaf.OpenAccessRoute
+import org.junit.jupiter.api.Assertions._
 import org.junit.jupiter.api.Test
+import org.slf4j.{Logger, LoggerFactory}
 
 import scala.io.Source
-import org.junit.jupiter.api.Assertions._
-import org.slf4j.{Logger, LoggerFactory}
 
 class UnpayWallMappingTest {