DOIBoost Mapping: change the creation of the instance in the DOIBoost result #155

Merged
claudio.atzori merged 12 commits from doiboost_url into beta 2021-11-11 10:40:33 +01:00
4 changed files with 653 additions and 27 deletions

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

Clean up commented out code lines

Clean up commented out code lines
// if (links.nonEmpty) {
// instance.setUrl(links.asJava)
// }
if(s.nonEmpty)
{
instance.setUrl(s.asJava)
}
result.setInstance(List(instance).asJava)
//IMPORTANT

View File

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

View File

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

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@ -0,0 +1,614 @@
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[
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]
],
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"timestamp": 1635695281393
},
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"publisher": "Elsevier BV",
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{
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[
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]
],
"date-time": "2019-12-01T00:00:00Z",
"timestamp": 1575158400000
},
"content-version": "tdm",
"delay-in-days": 0,
"URL": "https://www.elsevier.com/tdm/userlicense/1.0/"
},
{
"start": {
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[
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]
],
"date-time": "2019-09-13T00:00:00Z",
"timestamp": 1568332800000
},
"content-version": "vor",
"delay-in-days": 0,
"URL": "http://creativecommons.org/licenses/by/4.0/"
}
],
"funder": [
{
"DOI": "10.13039/100001182",
"name": "INSTAP",
"doi-asserted-by": "publisher"
},
{
"DOI": "10.13039/100014440",
"name": "Ministry of Science, Innovation and Universities",
"doi-asserted-by": "publisher",
"award": [
"RYC-2016-19637"
]
},
{
"DOI": "10.13039/100010661",
"name": "European Unions Horizon 2020",
"doi-asserted-by": "publisher",
"award": [
"746446"
]
}
],
"content-domain": {
"domain": [
"elsevier.com",
"sciencedirect.com"
],
"crossmark-restriction": true
},
"short-container-title": [
"Journal of Archaeological Science"
],
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[
2019,
12
]
]
},
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"type": "journal-article",
"created": {
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],
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},
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"A brave new world for archaeological survey: Automated machine learning-based potsherd detection using high-resolution drone imagery"
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{
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"Archaeology"
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