diff --git a/dhp-workflows/dhp-doiboost/src/main/java/eu/dnetlib/doiboost/orcidnodoi/oaf/PublicationToOaf.java b/dhp-workflows/dhp-doiboost/src/main/java/eu/dnetlib/doiboost/orcidnodoi/oaf/PublicationToOaf.java index f92040c24..ba7c7dd01 100644 --- a/dhp-workflows/dhp-doiboost/src/main/java/eu/dnetlib/doiboost/orcidnodoi/oaf/PublicationToOaf.java +++ b/dhp-workflows/dhp-doiboost/src/main/java/eu/dnetlib/doiboost/orcidnodoi/oaf/PublicationToOaf.java @@ -554,7 +554,7 @@ public class PublicationToOaf implements Serializable { private KeyValue createCollectedFrom() { KeyValue cf = new KeyValue(); cf.setValue(ModelConstants.ORCID.toUpperCase()); - cf.setKey("10|" + OPENAIRE_PREFIX + SEPARATOR + "806360c771262b4d6770e7cdf04b5c5a"); + cf.setKey("10|" + OPENAIRE_PREFIX + SEPARATOR + "cd0f74b5955dc87fd0605745c4b49ee8"); return cf; } diff --git a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/community/QueryInformationSystem.java b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/community/QueryInformationSystem.java index f06c0d47a..ec89edc63 100644 --- a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/community/QueryInformationSystem.java +++ b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/community/QueryInformationSystem.java @@ -26,6 +26,9 @@ public class QueryInformationSystem { + " return " + " " + " { $x//CONFIGURATION/context/@id} " + + " " + + "{$x//CONFIGURATION/context/param[./@name='advancedConstraints']/text() }" + + "" + " " + " {for $y in tokenize($subj,',') " + " return " diff --git a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/community/ResultTagger.java b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/community/ResultTagger.java index 0452a6ebf..d6498e942 100644 --- a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/community/ResultTagger.java +++ b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/community/ResultTagger.java @@ -9,16 +9,16 @@ import java.util.*; import java.util.stream.Collectors; import java.util.stream.Stream; +import eu.dnetlib.dhp.schema.common.ModelConstants; +import eu.dnetlib.dhp.schema.common.ModelSupport; +import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils; import org.apache.commons.lang3.StringUtils; import com.google.gson.Gson; import com.jayway.jsonpath.DocumentContext; import com.jayway.jsonpath.JsonPath; -import eu.dnetlib.dhp.schema.common.ModelConstants; -import eu.dnetlib.dhp.schema.common.ModelSupport; import eu.dnetlib.dhp.schema.oaf.*; -import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils; /** Created by miriam on 02/08/2018. */ public class ResultTagger implements Serializable { diff --git a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/ContainsVerbIgnoreCase.java b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/ContainsVerbIgnoreCase.java index a4a6f5663..501eb51b9 100644 --- a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/ContainsVerbIgnoreCase.java +++ b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/ContainsVerbIgnoreCase.java @@ -3,7 +3,7 @@ package eu.dnetlib.dhp.bulktag.criteria; import java.io.Serializable; -@VerbClass("contains_ignorecase") +@VerbClass("contains_caseinsensitive") public class ContainsVerbIgnoreCase implements Selection, Serializable { private String param; diff --git a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/EqualVerbIgnoreCase.java b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/EqualVerbIgnoreCase.java index c5f0ce070..1cd07755c 100644 --- a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/EqualVerbIgnoreCase.java +++ b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/EqualVerbIgnoreCase.java @@ -3,7 +3,7 @@ package eu.dnetlib.dhp.bulktag.criteria; import java.io.Serializable; -@VerbClass("equals_ignorecase") +@VerbClass("equals_caseinsensitive") public class EqualVerbIgnoreCase implements Selection, Serializable { private String param; diff --git a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/NotContainsVerbIgnoreCase.java b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/NotContainsVerbIgnoreCase.java index b21be83f0..e12b65a27 100644 --- a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/NotContainsVerbIgnoreCase.java +++ b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/NotContainsVerbIgnoreCase.java @@ -3,7 +3,7 @@ package eu.dnetlib.dhp.bulktag.criteria; import java.io.Serializable; -@VerbClass("not_contains_ignorecase") +@VerbClass("not_contains_caseinsensitive") public class NotContainsVerbIgnoreCase implements Selection, Serializable { private String param; diff --git a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/NotEqualVerbIgnoreCase.java b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/NotEqualVerbIgnoreCase.java index c6958a641..c1749621e 100644 --- a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/NotEqualVerbIgnoreCase.java +++ b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/NotEqualVerbIgnoreCase.java @@ -3,7 +3,7 @@ package eu.dnetlib.dhp.bulktag.criteria; import java.io.Serializable; -@VerbClass("not_equals_ignorecase") +@VerbClass("not_equals_caseinsensitive") public class NotEqualVerbIgnoreCase implements Selection, Serializable { private String param; diff --git a/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/StartsWithVerb.java b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/StartsWithVerb.java new file mode 100644 index 000000000..f22e1a864 --- /dev/null +++ b/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/bulktag/criteria/StartsWithVerb.java @@ -0,0 +1,30 @@ + +package eu.dnetlib.dhp.bulktag.criteria; + +import java.io.Serializable; + +@VerbClass("starts_with") +public class StartsWithVerb implements Selection, Serializable { + + private String param; + + public StartsWithVerb() { + } + + public StartsWithVerb(final String param) { + this.param = param; + } + + @Override + public boolean apply(String value) { + return value.startsWith(param); + } + + public String getParam() { + return param; + } + + public void setParam(String param) { + this.param = param; + } +} diff --git a/dhp-workflows/dhp-enrichment/src/test/java/eu/dnetlib/dhp/bulktag/BulkTagJobTest.java b/dhp-workflows/dhp-enrichment/src/test/java/eu/dnetlib/dhp/bulktag/BulkTagJobTest.java index def524156..364e53376 100644 --- a/dhp-workflows/dhp-enrichment/src/test/java/eu/dnetlib/dhp/bulktag/BulkTagJobTest.java +++ b/dhp-workflows/dhp-enrichment/src/test/java/eu/dnetlib/dhp/bulktag/BulkTagJobTest.java @@ -16,6 +16,7 @@ import org.apache.commons.io.IOUtils; import org.apache.spark.SparkConf; import org.apache.spark.api.java.JavaRDD; import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.ForeachFunction; import org.apache.spark.sql.Encoders; import org.apache.spark.sql.Row; import org.apache.spark.sql.SparkSession; @@ -45,7 +46,9 @@ public class BulkTagJobTest { + " \"orcid\" : \"$['author'][*]['pid'][*][?(@['key']=='ORCID')]['value']\"," + " \"contributor\" : \"$['contributor'][*]['value']\"," + " \"description\" : \"$['description'][*]['value']\", " - + " \"subject\" :\"$['subject'][*]['value']\" }"; + + " \"subject\" :\"$['subject'][*]['value']\" , " + + + "\"fos\" : \"$['subject'][?(@['qualifier']['classid']=='subject:fos')].value\"} "; private static SparkSession spark; @@ -769,28 +772,14 @@ public class BulkTagJobTest { org.apache.spark.sql.Dataset idExplodeCommunity = spark.sql(query); idExplodeCommunity.show(false); - Assertions.assertEquals(4, idExplodeCommunity.count()); + Assertions.assertEquals(5, idExplodeCommunity.count()); Assertions .assertEquals( 3, idExplodeCommunity.filter("provenance = 'community:datasource'").count()); Assertions .assertEquals( - 1, idExplodeCommunity.filter("provenance = 'community:advconstraint'").count()); + 2, idExplodeCommunity.filter("provenance = 'community:advconstraint'").count()); } -// @Test -// void test1(){ -// ProtoMap params = new Gson().fromJson(pathMap, ProtoMap.class); -// HashMap param = new HashMap<>(); -// for (String key : params.keySet()) { -// try { -// param.put(key, jsonContext.read(params.get(key))); -// } catch (com.jayway.jsonpath.PathNotFoundException e) { -// param.put(key, new ArrayList<>()); -// } -// } -// return param; -// } -// } } diff --git a/dhp-workflows/dhp-enrichment/src/test/resources/eu/dnetlib/dhp/bulktag/communityconfiguration/tagging_conf.xml b/dhp-workflows/dhp-enrichment/src/test/resources/eu/dnetlib/dhp/bulktag/communityconfiguration/tagging_conf.xml index 06c57511d..b2e33df12 100644 --- a/dhp-workflows/dhp-enrichment/src/test/resources/eu/dnetlib/dhp/bulktag/communityconfiguration/tagging_conf.xml +++ b/dhp-workflows/dhp-enrichment/src/test/resources/eu/dnetlib/dhp/bulktag/communityconfiguration/tagging_conf.xml @@ -844,6 +844,89 @@ + + { + "criteria": [ + { + "constraint": [ + { + "verb": "equals_caseinsensitive", + "field": "subject", + "value": "North America" + }, + { + "verb": "contains", + "field": "fos", + "value": "05" + } + ] + }, + { + "constraint": [ + { + "verb": "equals_caseinsensitive", + "field": "subject", + "value": "North America" + }, + { + "verb": "contains", + "field": "fos", + "value": "06" + } + ] + }, + { + "constraint": [ + { + "verb": "equals_caseinsensitive", + "field": "subject", + "value": "Mexico" + }, + { + "verb": "equals_caseinsensitive", + "field": "subject", + "value": "United States" + }, + { + "verb": "equals_caseinsensitive", + "field": "subject", + "value": "Canada" + }, + { + "verb": "contains", + "field": "fos", + "value": "05" + } + ] + }, + { + "constraint": [ + { + "verb": "equals_caseinsensitive", + "field": "subject", + "value": "Mexico" + }, + { + "verb": "equals_caseinsensitive", + "field": "subject", + "value": "United States" + }, + { + "verb": "equals_caseinsensitive", + "field": "subject", + "value": "Canada" + }, + { + "verb": "contains", + "field": "fos", + "value": "06" + } + ] + } + ] + } + + @@ -1174,7 +1257,9 @@ + + @@ -1193,7 +1278,7 @@ - {"criteria":[{"constraint":[{"verb":"equals_ignorecase","field":"subject","value":"ciencias de la comunicación"}, + {"criteria":[{"constraint":[{"verb":"equals_caseinsensitive","field":"subject","value":"ciencias de la comunicación"}, {"verb":"equals","field":"subject","value":"Miriam"}]}, {"constraint":[{"verb":"equals","field":"subject","value":"miriam"}]}]} @@ -1317,81 +1402,81 @@ opendoar____::358aee4cc897452c00244351e4d91f69 - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCoV"}}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCoV"}}]} re3data_____::7b0ad08687b2c960d5aeef06f811d5e6 - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCoV"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCoV"}]}]} driver______::bee53aa31dc2cbb538c10c2b65fa5824 - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCoV"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCoV"}]}]} openaire____::437f4b072b1aa198adcbc35910ff3b98 - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCoV"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCoV"}]}]} openaire____::081b82f96300b6a6e3d282bad31cb6e2 - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCoV"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCoV"}]}]} openaire____::9e3be59865b2c1c335d32dae2fe7b254 - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCoV"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCoV"}]}]} opendoar____::8b6dd7db9af49e67306feb59a8bdc52c - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCoV"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCoV"}]}]} share_______::4719356ec8d7d55d3feb384ce879ad6c - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCoV"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCoV"}]}]} share_______::bbd802baad85d1fd440f32a7a3a2c2b1 - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCoV"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCoV"}]}]} opendoar____::6f4922f45568161a8cdf4ad2299f6d23 - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]}, - {"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCoV"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]}, + {"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCoV"}]}]} re3data_____::7980778c78fb4cf0fab13ce2159030dc - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]},{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]},{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCov"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]},{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]},{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCov"}]}]} re3data_____::978378def740bbf2bfb420de868c460b - {"criteria":[{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"SARS-CoV-2"}]},{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"COVID-19"}]},{"constraint":[{"verb":"contains_ignorecase","field":"title","value":"2019-nCov"}]}]} + {"criteria":[{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"SARS-CoV-2"}]},{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"COVID-19"}]},{"constraint":[{"verb":"contains_caseinsensitive","field":"title","value":"2019-nCov"}]}]} diff --git a/dhp-workflows/dhp-enrichment/src/test/resources/eu/dnetlib/dhp/bulktag/sample/dataset/update_datasourcewithconstraints/dataset_10.json b/dhp-workflows/dhp-enrichment/src/test/resources/eu/dnetlib/dhp/bulktag/sample/dataset/update_datasourcewithconstraints/dataset_10.json index 168343401..17553eb83 100644 --- a/dhp-workflows/dhp-enrichment/src/test/resources/eu/dnetlib/dhp/bulktag/sample/dataset/update_datasourcewithconstraints/dataset_10.json +++ b/dhp-workflows/dhp-enrichment/src/test/resources/eu/dnetlib/dhp/bulktag/sample/dataset/update_datasourcewithconstraints/dataset_10.json @@ -6,5 +6,5 @@ {"dataInfo":{"invisible":false,"inferred":false,"deletedbyinference":false,"trust":"0.9","inferenceprovenance":"","provenanceaction":{"classid":"sysimport:crosswalk:repository","classname":"sysimport:crosswalk:repository","schemeid":"dnet:provenanceActions","schemename":"dnet:provenanceActions"}},"lastupdatetimestamp":1585055869498,"id":"50|od______3989::2f4f3c820c450bd08dac08d07cc82dcf","originalId":["od______3989::2f4f3c820c450bd08dac08d07cc82dcf"],"collectedfrom":[{"key":"opendoar____::3989","value":"Depósito Digital e-UCJC","dataInfo":null}],"pid":[],"dateofcollection":"2020-03-03T13:05:34.806Z","dateoftransformation":"2020-03-03T13:06:54.229Z","extraInfo":[],"oaiprovenance":{"originDescription":{"harvestDate":"2020-03-03T13:05:34.806Z","altered":true,"baseURL":"http%3A%2F%2Frepositorio.ucjc.edu%2Foai%2Frequest","identifier":"oai:repositorio.ucjc.edu:20.500.12020/797","datestamp":"2018-11-14T12:12:23Z","metadataNamespace":"http://www.openarchives.org/OAI/2.0/oai_dc/"}},"author":[{"fullname":"Cuesta Cano, Laura","name":"Laura","surname":"Cuesta Cano","rank":1,"pid":null,"affiliation":null}],"resulttype":{"classid":"dataset","classname":"dataset","schemeid":"dnet:result_typologies","schemename":"dnet:result_typologies"},"language":{"classid":"esl/spa","classname":"Spanish","schemeid":"dnet:languages","schemename":"dnet:languages"},"country":[],"subject":[{"value":"Ciencias de la Comunicación","qualifier":{"classid":"","classname":"","schemeid":"","schemename":""},"dataInfo":{"invisible":false,"inferred":false,"deletedbyinference":false,"trust":"0.9","inferenceprovenance":"","provenanceaction":{"classid":"sysimport:crosswalk:repository","classname":"sysimport:crosswalk:repository","schemeid":"dnet:provenanceActions","schemename":"dnet:provenanceActions"}}},{"value":"Marketing digital","qualifier":{"classid":"","classname":"","schemeid":"","schemename":""},"dataInfo":{"invisible":false,"inferred":false,"deletedbyinference":false,"trust":"0.9","inferenceprovenance":"","provenanceaction":{"classid":"sysimport:crosswalk:repository","classname":"sysimport:crosswalk:repository","schemeid":"dnet:provenanceActions","schemename":"dnet:provenanceActions"}}},{"value":"Medios 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se están desarrollando en la Universidad Camilo José Cela (UCJC) sobre la cafeína y sus efectos cuando se realiza deporte. https://www.ucjc.edu/2016/08/la-bbc-s...\n\nJuan Del Coso, director del Laboratorio de Fisiología del Ejercicio de la Universidad Camilo José Cela, nos describe cómo está siendo la investigación que desarrolla con deportistas de alto rendimiento y el consumo de cafeína.\n\n\"Nuestra investigación se enmarca dentro del campo de la fisiología del ejercicio y el objetivo que tenemos es investigar los efectos que tiene la cafeína en los deportistas, principalmente saber si es una ayuda ergogénica en la mayor parte de los deportes, pero también conocer qué perjuicios existen para aquellos deportistas que la utilizan para incrementar el rendimiento deportivo\", explica Del Coso.\n\nY es que los datos son muy llamativos: tres de cada cuatro deportistas de alto rendimiento utilizan la cafeína antes de la competición y muchas veces se utiliza sin saber los perjuicios que 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El formato es al estilo inglés, similar al de la Oxford Union, donde algunos jóvenes se reunían a debatir sobre temas de la más candente actualidad y polemizaban con la intención de formarse en tan valoradas habilidades.\n\nLa Liga de Debate CICAE-UCJC es una ocasión única para los alumnos de ponerse en contacto con herramientas tan útiles como la oratoria y la comunicación efectiva. Pero, sobre todo, una oportunidad de fomentar el pensamiento crítico y la socialización entre alumnos con espíritu emprendedor. La Liga de Debate CICAE - Universidad Camilo José Cela se diferencia del resto de torneos en que potenciamos que sea eminentemente formativa. 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+ fsh_____4119::68126da991bd76d8be494bddfbf7a1bb + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be + + + + + + 2022-11-15T12:29:19Z + 2022-11-15T12:29:19Z + fsh_____4119 + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be + 2022-11-15T12:29:19Z + rohub_data + ro-crate_data +
+ + + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be + + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be + + + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be/resources/b1b617b2-6b79-4bae-9fa6-b76945645626 + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be/resources/78103994-30be-4875-bf89-5acd752b5c3d + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be/resources/18fd1c70-249b-4c67-80ee-539f801a0da7 + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be/resources/32faa2eb-4cc8-401f-ac5c-bec2849b70e1 + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be/resources/4c253f5a-d427-40c2-9e9f-6063ae087239 + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be/resources/371b1957-078c-472b-a195-af7bce152c10 + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be/resources/82f9e4b8-01b4-4e50-9e27-ec9d337c8d74 + + RO-crate + + Creative Commons Attribution 4.0 International + open access + + + Mapping the photic zone of the Mediterranean Sea + + + Estimating the penetration of light along the water column from satellite data to map the photic zone in the Mediterranean Sea + + CNR-ISMAR + + + Giorgio Castellan + + + Lorenzo Angeletti + + + Paolo Montagna + + + Marco Taviani + + + + 2022-11-14T16:32:45Z + + + Estimating the penetration of light along the water column from satellite data to map the photic zone in the Mediterranean Sea + + 2022 + + open access + + + 813.478 KB + + + Earth sciences + Ecology + Optics + + + https://w3id.org/ro-id/28499bdf-a0c6-46aa-a96f-50bd9490b8be + 0048 + 2022-11-14 + OPEN + https://creativecommons.org/licenses/by/4.0/legalcode + + + + + + + +
\ No newline at end of file diff --git a/dhp-workflows/dhp-graph-provision/src/test/java/eu/dnetlib/dhp/oa/provision/EOSCFuture_Test.java b/dhp-workflows/dhp-graph-provision/src/test/java/eu/dnetlib/dhp/oa/provision/EOSCFuture_Test.java new file mode 100644 index 000000000..08bf19fe4 --- /dev/null +++ b/dhp-workflows/dhp-graph-provision/src/test/java/eu/dnetlib/dhp/oa/provision/EOSCFuture_Test.java @@ -0,0 +1,88 @@ +package eu.dnetlib.dhp.oa.provision; + +import com.fasterxml.jackson.databind.DeserializationFeature; +import com.fasterxml.jackson.databind.ObjectMapper; +import eu.dnetlib.dhp.oa.provision.model.JoinedEntity; +import eu.dnetlib.dhp.oa.provision.utils.ContextMapper; +import eu.dnetlib.dhp.oa.provision.utils.StreamingInputDocumentFactory; +import eu.dnetlib.dhp.oa.provision.utils.XmlRecordFactory; +import eu.dnetlib.dhp.schema.oaf.OtherResearchProduct; +import eu.dnetlib.dhp.utils.saxon.SaxonTransformerFactory; +import org.apache.commons.io.IOUtils; +import org.apache.solr.client.solrj.util.ClientUtils; +import org.apache.solr.common.SolrInputDocument; +import org.dom4j.Document; +import org.dom4j.DocumentException; +import org.dom4j.io.SAXReader; +import org.junit.jupiter.api.Assertions; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.Test; + +import javax.xml.transform.Transformer; +import javax.xml.transform.TransformerException; +import java.io.IOException; +import java.io.StringReader; + +import static org.junit.jupiter.api.Assertions.assertNotNull; + +public class EOSCFuture_Test { + + public static ObjectMapper OBJECT_MAPPER = new ObjectMapper() + .configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false); + + public static final String VERSION = "2021-04-15T10:05:53Z"; + public static final String DSID = "b9ee796a-c49f-4473-a708-e7d67b84c16d_SW5kZXhEU1Jlc291cmNlcy9JbmRleERTUmVzb3VyY2VUeXBl"; + + private ContextMapper contextMapper; + + @BeforeEach + public void setUp() { + contextMapper = new ContextMapper(); + } + + + @Test + public void testEOSC_ROHub() throws IOException, DocumentException, TransformerException { + + final ContextMapper contextMapper = new ContextMapper(); + + final XmlRecordFactory xmlRecordFactory = new XmlRecordFactory(contextMapper, false, + XmlConverterJob.schemaLocation); + + final OtherResearchProduct p = OBJECT_MAPPER + .readValue(IOUtils.toString(getClass().getResourceAsStream("eosc-future/photic-zone.json")), OtherResearchProduct.class); + + final String xml = xmlRecordFactory.build(new JoinedEntity<>(p)); + + assertNotNull(xml); + + final Document doc = new SAXReader().read(new StringReader(xml)); + + assertNotNull(doc); + System.out.println(doc.asXML()); + + + testRecordTransformation(xml); + } + + + private void testRecordTransformation(final String record) throws IOException, TransformerException { + final String fields = IOUtils.toString(getClass().getResourceAsStream("fields.xml")); + final String xslt = IOUtils.toString(getClass().getResourceAsStream("layoutToRecordTransformer.xsl")); + + final String transformer = XmlIndexingJob.getLayoutTransformer("DMF", fields, xslt); + + final Transformer tr = SaxonTransformerFactory.newInstance(transformer); + + final String indexRecordXML = XmlIndexingJob.toIndexRecord(tr, record); + + final SolrInputDocument solrDoc = new StreamingInputDocumentFactory(VERSION, DSID) + .parseDocument(indexRecordXML); + + final String xmlDoc = ClientUtils.toXML(solrDoc); + + Assertions.assertNotNull(xmlDoc); + System.out.println(xmlDoc); + } + +} diff --git a/dhp-workflows/dhp-graph-provision/src/test/java/eu/dnetlib/dhp/oa/provision/IndexRecordTransformerTest.java b/dhp-workflows/dhp-graph-provision/src/test/java/eu/dnetlib/dhp/oa/provision/IndexRecordTransformerTest.java index e0fbb2a2f..d9dc609d8 100644 --- a/dhp-workflows/dhp-graph-provision/src/test/java/eu/dnetlib/dhp/oa/provision/IndexRecordTransformerTest.java +++ b/dhp-workflows/dhp-graph-provision/src/test/java/eu/dnetlib/dhp/oa/provision/IndexRecordTransformerTest.java @@ -128,6 +128,40 @@ public class IndexRecordTransformerTest { testRecordTransformation(record); } + @Test + public void testForEOSCFutureSoftwareNotebook() throws IOException, TransformerException { + final String record = IOUtils + .toString(getClass().getResourceAsStream("eosc-future/software-justthink.xml")); + testRecordTransformation(record); + } + + @Test + public void testForEOSCFutureSoftwareNotebookClaim() throws IOException, TransformerException { + final String record = IOUtils + .toString(getClass().getResourceAsStream("eosc-future/software-justthink-claim.xml")); + testRecordTransformation(record); + } + + @Test + public void testForEOSCFutureZenodo7353841() throws IOException, TransformerException { + final String record = IOUtils + .toString(getClass().getResourceAsStream("eosc-future/zenodo7353841.xml")); + testRecordTransformation(record); + } + + @Test + public void testForEOSCFutureZenodo7351393() throws IOException, TransformerException { + final String record = IOUtils + .toString(getClass().getResourceAsStream("eosc-future/zenodo7351393.xml")); + testRecordTransformation(record); + } + + @Test + public void testForEOSCFutureZenodo7351221() throws IOException, TransformerException { + final String record = IOUtils + .toString(getClass().getResourceAsStream("eosc-future/zenodo7351221.xml")); + testRecordTransformation(record); + } @Test void testDoiUrlNormalization() throws MalformedURLException { diff --git a/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/photic-zone.json b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/photic-zone.json new file mode 100644 index 000000000..9729c6051 --- /dev/null +++ b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/photic-zone.json @@ -0,0 +1 @@ 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Notebook","label":"EOSC::Jupyter Notebook","url":"","semanticRelation":"compliesWith"},{"code":"EOSC::Data Cube","label":"EOSC::Data Cube","url":"","semanticRelation":"compliesWith"},{"code":"EOSC::RO-crate","label":"EOSC::RO-crate","url":"","semanticRelation":"compliesWith"}],"contactperson":[],"contactgroup":[],"tool":[]} \ No newline at end of file diff --git a/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/software-justthink-claim.xml b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/software-justthink-claim.xml new file mode 100644 index 000000000..02089bb30 --- /dev/null +++ b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/software-justthink-claim.xml @@ -0,0 +1,305 @@ + + +
+ od______2659::3801993ea8f970cfc991277160edf277 + 2022-08-08T03:06:13Z + under curation + +
+ + + + JUSThink + Alignment Analysis + Norman, Utku + Dinkar, Tanvi + Bruno, Barbara + Clavel, Chloé + + + + +

+ 1. Description +

+

This repository contains tools to automatically analyse how + participants align their use of task-specific referents in their + dialogue and actions for a collaborative learning activity, and how + it relates to the task success (i.e. their learning + outcomes and task performance).

+

As a use case, it processes data from a collaborative problem solving + activity named JUSThink [1, 2], i.e. + JUSThink Dialogue and Actions Corpus data set that is available from the + Zenodo Repository, DOI: 10.5281/zenodo.4627104, and reproduces the results and figures + in [3].

+

In brief:

+
    +
  1. JUSThink Dialogue and Actions Corpus contains + transcripts, event logs, and test responses of children aged 9 + through 12, as they participate in the JUSThink activity [1, 2] + in pairs of two, to solve a problem on graphs together.
  2. +
  3. The JUSThink activity and its study is first + described in [1], and elaborated with findings concerning the link + between children's learning, performance in the activity, and + perception of self, the other and the robot in [2].
  4. +
  5. Alignment analysis in our work [3] studies the participants' use of + expressions that are related to the task at hand, their follow up + actions of these expressions, and how it links to task success.
  6. +
+

+ 2. Publications +

+

If you use this work in an academic context, please cite the following + publications:

+
    +
  • +

    Norman*, U., Dinkar*, T., Bruno, B., & Clavel, C. (2022). + Studying Alignment in a Collaborative Learning Activity via + Automatic Methods: The Link Between What We Say and Do. Dialogue + & Discourse, 13(2), 1 - ;48. *Contributed equally to this + work. https://doi.org/10.5210/dad.2022.201

    +
  • +
  • +

    Norman, U., Dinkar, T., Bruno, B., & Clavel, C. (2021). + JUSThink Alignment Analysis. In Dialogue & Discourse + (v1.0.0, Vol. 13, Number 2, pp. 1 - ;48). Zenodo. https://doi.org/10.5281/zenodo.4675070

    +
  • +
+

+ 3. Content +

+

The tools provided in this repository consists of 7 Jupyter Notebooks + written in Python 3, and two additional external tools utilised by the + notebooks.

+

+ 3.1. Jupyter Notebooks +

+

We highlight that the notebooks up until the last (i.e. to test the + hypotheses (tools/7_test_the_hypotheses.ipynb)) present a general + pipeline to process event logs, test responses and transcripts to + extract measures of task performance, learning outcomes, and measures of + alignment.

+
    +
  1. Extract task performance (and other features) from the logs + (tools/1_extract_performance_and_other_features_from_logs.ipynb): + Extracts various measures of task behaviour from the logs, at + varying granularities of the activity (i.e. the whole corpus, task, + attempt, and turn levels). In later notebooks, we focus on one of + the features to estimate the task performance of a team: (minimum) + error.
  2. +
  3. Extract learning outcomes from the test responses + (tools/2_extract_learning_gain_from_test_responses.ipynb): Extracts + measures of learning outcomes from the responses to the pre-test and + the post-test. In later notebooks, we focus on one of the features + to estimate the learning outcome of a team: relative learning gain + [4]
  4. +
  5. Select and visualise a subset of teams for + transcription + (tools/3_visualise_transcribed_teams.ipynb): Visualises the + transcribed teams among the other teams in the feature space spanned + by task performance and learning outcome, as well as the + distribution of their number of attempts and turns.
  6. +
  7. Extract routines from transcripts + (tools/4_extract_routines_from_transcripts.ipynb) (uses dialign to + extract routines): Extracts routines of referring expressions that + are "fixed", i.e. become shared or established amongst + interlocutors.
  8. +
  9. Combine transcripts with logs + (tools/5_construct_the_corpus_by_combining_transcripts_with_logs.ipynb): + Merges transcripts with event logs to have a combined dialogue and + actions corpus, to be processed e.g. to detect follow-up + actions.
  10. +
  11. Recognise instructions and detect follow-up actions + (tools/6_recognise_instructions_detect_follow-up_actions.ipynb): + Extracts verbalised instruction such as "connect Mount Basel to + Montreux", and pairs them with the follow-up action that may + match (e.g. if the other connects Basel to Montreux) or + mismatch (e.g. if the other connects Basel to + Neuchatel) with the instruction.
  12. +
  13. Test the hypotheses in [3] (tools/7_test_the_hypotheses.ipynb) (uses + effsize to estimate effect size, specifically + Cliff's Delta): Considers each research questions and hypotheses + studied in [3] and generates the results in [3].
  14. +
+

+ 3.2. External Tools +

+
    +
  1. dialign + tool to extract routines, specifically Release 1.0 from dialign-1.0.zip:\n It extracts routine expressions that are + "shared" among the participants from transcripts. \n It is + used as an external module (in accordance with its CeCILL-B License, + see License).
  2. +
  3. effsize tool to compute estimators of effect + size.\n We specifically use it to compute Cliff's Delta, which + quantifies the amount difference between two groups of observations, + by computing the Cliff's Delta statistic.\n It is taken from + project DABEST (see License).
  4. +
+

+ 4. Research Questions and Hypotheses in [3] +

+
    +
  • RQ1 Lexical alignment: How do the interlocutors + use expressions related to the task? Is this associated + with task success?
      +
    • H1.1: Task-specific referents become + routine early for more successful teams.
    • +
    • H1.2: Hesitation phenomena are more likely + to occur in the vicinity of priming and establishment of + task-specific referents for more successful teams.
    • +
    +
  • +
  • RQ2 Behavioural alignment: How do the interlocutors + follow up these expressions with actions? Is this + associated with task success?
      +
    • H2.1: Instructions are more likely to be + followed by a corresponding action early in the dialogue for + more successful teams.
    • +
    • H2.2: When instructions are followed by a + corresponding or a different action, the action is more + likely to be in the vicinity of information management + phenomena for more successful teams.
    • +
    +
  • +
+

The RQs and Hs are addressed in the notebook for testing the hypotheses + (i.e. tools/7_test_the_hypotheses.ipynb).

+

+ Acknowledgements +

+

This project has received funding from the European Union's Horizon + 2020 research and innovation programme under grant agreement No 765955. + Namely, the ANIMATAS Project.

+

+ License +

+

The whole package is under MIT License, see the LICENSE + file.

+

Classes under the tools/effsize package were taken from + project DABEST, Copyright 2016-2020 Joses W. Ho. + These classes are licensed under the BSD 3-Clause Clear License. See + tools/effsize/LICENSE file for additional + details.

+

Classes under the tools/dialign-1.0 package were taken + from project dialign. These classes are licensed under the + CeCILL-B License. This package is used as an "external + module", see tools/dialign-1.0/LICENSE.txt for + additional details.

+
+ + + + Zenodo + + + + + + + + + + + + + + + + + + + oai:zenodo.org:4675070 + + oai:zenodo.org:4675070 + 10.5281/zenodo.4675070 + + + + false + false + 0.9 + + + + + + corda__h2020::c4515ebef538a734cf11f795347f5dac + 765955 + ANIMATAS + Advancing intuitive human-machine interaction with human-like + social capabilities for education in schools + + + + ec__________::EC::H2020 + + + + + + + + + + + + + https://zenodo.org/record/4675070 + + + +
+
+
+
+
diff --git a/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/software-justthink.xml b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/software-justthink.xml new file mode 100644 index 000000000..9c0f4ea7d --- /dev/null +++ b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/software-justthink.xml @@ -0,0 +1,429 @@ + + +
+ doi_dedup___::c054151b6a8c4f41c7acf160651a6503 + 2022-10-13T00:15:44+0000 + 2022-10-13T07:44:29.152Z +
+ + + + + + oai:zenodo.org:4675070 + 50|od______2659::3801993ea8f970cfc991277160edf277 + oai:zenodo.org:6974562 + 50|od______2659::9c87ff4a5e7710052b873088e7265072 + 10.5281/zenodo.4675069 + 10.5281/zenodo.4675070 + 10.5281/zenodo.6974562 + 10.5281/zenodo.4675069 + + + + + + JUSThink Alignment + Analysis + + Norman, Utku + Dinkar, Tanvi + Bruno, Barbara + Clavel, Chloé + 2022-08-08 + &lt;strong>1. Description&lt;/strong> This repository + contains&lt;strong> tools to automatically analyse how participants align + their use of task-specific referents in their dialogue and actions for a + collaborative learning activity, and how it relates to the task + success&lt;/strong> (i.e. their learning outcomes and task performance). As + a use case, it processes data from a collaborative problem solving activity + named JUSThink [1, 2], i.e. JUSThink Dialogue and Actions Corpus data set that + is available from the Zenodo Repository, DOI: 10.5281/zenodo.4627104, and + reproduces the results and figures in [3]. In brief: &lt;strong>JUSThink + Dialogue and Actions Corpus&lt;/strong> contains transcripts, event logs, + and test responses of children aged 9 through 12, as they participate in the + JUSThink activity [1, 2] in pairs of two, to solve a problem on graphs together. + &lt;strong>The JUSThink activity and its study&lt;/strong> is first + described in [1], and elaborated with findings concerning the link between + children's learning, performance in the activity, and perception of self, the + other and the robot in [2]. &lt;strong>Alignment analysis in our work + [3]&lt;/strong> studies the participants' use of expressions that are + related to the task at hand, their follow up actions of these expressions, and + how it links to task success. &lt;strong>Changes in Release + v1.1.0:&lt;/strong> updated with the publication information, finalized + paper structure, research questions and hypotheses as in the published article: + U. Norman*&lt;em>, &lt;/em>T. Dinkar*, B. Bruno, and C. Clavel, + "Studying Alignment in a Collaborative Learning Activity via Automatic Methods: + The Link Between What We Say and Do," Dialogue &amp;amp; Discourse, 13(2), + 1–48. *Contributed equally to this work. 10.5210/dad.2022.201. + &lt;strong>Full Changelog:&lt;/strong> + https://github.com/chili-epfl/justhink-alignment-analysis/compare/v1.0.0...v1.1.0 + &lt;strong>2. Publications&lt;/strong> If you use this work in an + academic context, please cite the following publications: Norman*, U., Dinkar*, + T., Bruno, B., &amp;amp; Clavel, C. (2022). Studying Alignment in a + Collaborative Learning Activity via Automatic Methods: The Link Between What We + Say and Do. Dialogue &amp;amp; Discourse, 13(2), 1–48. *Contributed equally + to this work. https://doi.org/10.5210/dad.2022.201 Norman, U., Dinkar, T., + Bruno, B., &amp;amp; Clavel, C. (2021). JUSThink Alignment Analysis. In + Dialogue &amp;amp; Discourse (v1.1.0, Vol. 13, Number 2, pp. 1–48). Zenodo. + https://doi.org/10.5281/zenodo.6974562 &lt;strong>3. Content&lt;/strong> + The tools provided in this repository consists of 7 Jupyter Notebooks written in + Python 3, and two additional external tools utilised by the notebooks. + &lt;strong>3.1. Jupyter Notebooks&lt;/strong> We highlight that the + notebooks up until the last (i.e. to test the hypotheses + (tools/7_test_the_hypotheses.ipynb)) present a general pipeline to process event + logs, test responses and transcripts to extract measures of task performance, + learning outcomes, and measures of alignment. &lt;strong>Extract task + performance (and other features) from the logs + &lt;/strong>(tools/1_extract_performance_and_other_features_from_logs.ipynb): + Extracts various measures of task behaviour from the logs, at varying + granularities of the activity (i.e. the whole corpus, task, attempt, and turn + levels). In later notebooks, we focus on one of the features to estimate the + task performance of a team: (minimum) error. &lt;strong>Extract learning + outcomes from the test responses&lt;/strong> + (tools/2_extract_learning_gain_from_test_responses.ipynb): Extracts measures of + learning outcomes from the responses to the pre-test and the post-test. In later + notebooks, we focus on one of the features to estimate the learning outcome of a + team: relative learning gain [4] &lt;strong>Select and visualise a subset of + teams for transcription&lt;/strong> + (tools/3_visualise_transcribed_teams.ipynb): Visualises the transcribed teams + among the other teams in the feature space spanned by task performance and + learning outcome, as well as the distribution of their number of attempts and + turns. &lt;strong>Extract routines from transcripts&lt;/strong> + (tools/4_extract_routines_from_transcripts.ipynb) (uses dialign to extract + routines): Extracts routines of referring expressions that are "fixed", i.e. + become shared or established amongst interlocutors. &lt;strong>Combine + transcripts with logs&lt;/strong> + (tools/5_construct_the_corpus_by_combining_transcripts_with_logs.ipynb): Merges + transcripts with event logs to have a combined dialogue and actions corpus, to + be processed e.g. to detect follow-up actions. &lt;strong>Recognise + instructions and detect follow-up actions&lt;/strong> + (tools/6_recognise_instructions_detect_follow-up_actions.ipynb): Extracts + verbalised instruction such as "connect Mount Basel to Montreux", and pairs them + with the follow-up action that may &lt;em>match&lt;/em> (e.g. if the + other connects Basel to Montreux) or &lt;em>mismatch&lt;/em> (e.g. if + the other connects Basel to Neuchatel) with the instruction. &lt;strong>Test + the hypotheses &lt;/strong>in [3] (tools/7_test_the_hypotheses.ipynb) (uses + &lt;strong>effsize&lt;/strong> to estimate effect size, specifically + Cliff's Delta): Considers each research questions and hypotheses studied in [3] + and generates the results in [3]. &lt;strong>3.2. External + Tools&lt;/strong> &lt;strong>dialign tool&lt;/strong> to extract + routines, specifically Release 1.0 from dialign-1.0.zip:&lt;br> It extracts + routine expressions that are "shared" among the participants from transcripts. + &lt;br> It is used as an external module (in accordance with its CeCILL-B + License, see &lt;strong>License&lt;/strong>). &lt;strong>effsize + tool&lt;/strong> to compute estimators of effect size.&lt;br> We + specifically use it to compute Cliff's Delta, which quantifies the amount + difference between two groups of observations, by computing the Cliff's Delta + statistic.&lt;br> It is taken from project DABEST (see + &lt;strong>License&lt;/strong>). &lt;strong>4. Research Questions + and Hypotheses in [3]&lt;/strong> &lt;strong>RQ1 Lexical + alignment&lt;/strong>: How do the interlocutors &lt;em>use&lt;/em> + expressions related to the task? Is this associated with task success? + &lt;strong>H1.1&lt;/strong>: Task-specific referents become routine + early for more successful teams. &lt;strong>H1.2&lt;/strong>: Hesitation + phenomena are more likely to occur in the vicinity of priming and establishment + of task-specific referents for more successful teams. &lt;strong>RQ2 + Behavioural alignment&lt;/strong>: How do the interlocutors + &lt;em>follow up&lt;/em> these expressions with actions? Is this + associated with task success? &lt;strong>H2.1&lt;/strong>: Instructions + are more likely to be followed by a corresponding action early in the dialogue + for more successful teams. &lt;strong>H2.2&lt;/strong>: When + instructions are followed by a corresponding or a different action, the action + is more likely to be in the vicinity of information management phenomena for + more successful teams. The RQs and Hs are addressed in the notebook for testing + the hypotheses (i.e. tools/7_test_the_hypotheses.ipynb). + &lt;strong>Acknowledgements&lt;/strong> This project has received + funding from the European Union's Horizon 2020 research and innovation programme + under grant agreement No 765955. Namely, the ANIMATAS Project. + &lt;strong>License&lt;/strong> The whole package is under MIT License, + see the &lt;strong>LICENSE&lt;/strong> file. Classes under the + &lt;strong>tools/effsize&lt;/strong> package were taken from project + &lt;strong>DABEST&lt;/strong>, Copyright 2016-2020 Joses W. Ho. These + classes are licensed under the BSD 3-Clause Clear License. See + &lt;strong>tools/effsize/LICENSE&lt;/strong> file for additional + details. Classes under the &lt;strong>tools/dialign-1.0&lt;/strong> + package were taken from project &lt;strong>dialign&lt;/strong>. These + classes are licensed under the CeCILL-B License. This package is used as an + "external module", see&lt;strong> + tools/dialign-1.0/LICENSE.txt&lt;/strong> for additional + details. + {"references": ["[1] J. Nasir, U. Norman, B. Bruno, and P. Dillenbourg, + \"You Tell, I Do, and We Swap until we Connect All the Gold Mines!,\" ERCIM + News, vol. 2020, no. 120, 2020, [Online]. Available: + https://ercim-news.ercim.eu/en120/special/you-tell-i-do-and-we-swap-until-we-connect-all-the-gold-mines", + "[2] J. Nasir*, U. Norman*, B. Bruno, and P. Dillenbourg, \"When Positive + Perception of the Robot Has No Effect on Learning,\" in 2020 29th IEEE + International Conference on Robot and Human Interactive Communication (RO-MAN), + Aug. 2020, pp. 313\u2013320, doi: 10.1109/RO-MAN47096.2020.9223343", "[3] U. + Norman*, T. Dinkar*, B. Bruno, and C. Clavel, \"Studying Alignment in a + Collaborative Learning Activity via Automatic Methods: The Link Between What We + Say and Do,\" Dialogue &amp;amp; Discourse, vol. 13, no. 2, pp. 1\u201348, + Aug. 2022, doi: 10.5210/dad.2022.201.", "[4] M. Sangin, G. Molinari, M.-A. + N\u00fcssli, and P. Dillenbourg, \"Facilitating peer knowledge modeling: Effects + of a knowledge awareness tool on collaborative learning outcomes and + processes,\"\" Computers in Human Behavior, vol. 27, no. 3, pp. 1059\u20131067, + May 2011, doi: 10.1016/j.chb.2010.05.032."]} + alignment + situated + dialogue + collaborative + learning + spontaneous + speech + disfluency + mutual + understanding + + 2021-04-09 + 2022-08-08 + Zenodo + + + + + + + + + + + true + false + 0.8 + dedup-result-decisiontree-v3 + + + + + doi_dedup___::ae235765bbc422195a6c9f632b2d77eb + + 2104.04429 + + arXiv + + 2022-08-05 + Studying + Alignment in a Collaborative Learning Activity via Automatic Methods: + The Link Between What We Say and Do + + + 10.48550/arxiv.2104.04429 + 10.5210/dad.2022.201 + + + corda__h2020::c4515ebef538a734cf11f795347f5dac + Advancing intuitive human-machine interaction with human-like social + capabilities for education in schools + 765955 + + + ec__________::EC::H2020 + ec__________::EC::H2020::MSCA-ITN-ETN + + ANIMATAS + + + doi_dedup___::0a6314b0ed275d915f5b57a259375691 + 2021-03-22 + Zenodo + 10.5281/zenodo.4627104 + JUSThink Dialogue and Actions Corpus + 10.5281/zenodo.4627103 + + + + + + + Zenodo + 10.5281/zenodo.4675070 + JUSThink Alignment Analysis + 2021-04-09 + + + + 2022-08-08 + Zenodo + 10.5281/zenodo.6974562 + + JUSThink Alignment Analysis (v1.1.0) + + + JUSThink + Alignment Analysis (v1.1.0) + 2022-08-08 + Zenodo + 10.5281/zenodo.4675069 + + + + + + + 2022-08-08 + + 10.5281/zenodo.4675069 + + https://opensource.org/licenses/MIT + + https://doi.org/10.5281/zenodo.4675069 + + + + + + + 2022-08-08 + + 10.5281/zenodo.6974562 + + https://opensource.org/licenses/MIT + + https://doi.org/10.5281/zenodo.6974562 + + + + + + + 2021-04-09 + + 10.5281/zenodo.4675070 + + https://opensource.org/licenses/MIT + + https://doi.org/10.5281/zenodo.4675070 + + + + + + +
+
diff --git a/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/zenodo7351221.xml b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/zenodo7351221.xml new file mode 100644 index 000000000..7f1e66dac --- /dev/null +++ b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/zenodo7351221.xml @@ -0,0 +1,99 @@ + + +
+ doi_________::9cb0664d4c891c4baaf73f007c0c9de0 + 2022-11-25T12:55:13Z + under curation + +
+ + + + + COVID-19 Knowledge Graph: A semantic resource embedding biological and chemical entities + Karki, Reagon + + + +

A Knowledge graph representation of compounds and associated biological entities in the BY-COVID and EOSC Future project.

Current status

  • Number of Nodes: 35952
  • Number of Edges: 279462
  • Human Proteins: 1347
  • Assay: 15835
  • Chemical/Compound: 4096
  • Mechanism of Action: 739
  • Pathway: 1513
  • Disease: 1585
  • SideEffect: 7420
  • Biological Process: 2085
  • Molecular Function: 1332

Please check the BY_COVID_update_August.ipynb for understanding step wise process of KG generation and KG statistics. The KG has been exported to formats such as graphml, sif and so on for visualizations in other platforms. For example, the graphml file can be imported to Cytoscape directly. These files are located in 'data\export' folder.

+ + + + Zenodo + + + + + + + + + + + + + + + + + + + oai:zenodo.org:7351221 + + oai:zenodo.org:7351221 + 10.5281/zenodo.7351221 + + + + false + false + 0.9 + + + + + + corda__h2020::256485716fdb9f5ca69007b7ca5a072b + 101017536 + EOSC Future + EOSC Future + + + + ec__________::EC::H2020 + + + + + corda__h2020::4a3254eac2997eee0a9dcb7a7daedb81 + 101046203 + BY-COVID + Beyond COVID + + + + ec__________::EC::Horizon Europe Framework Programme - HORIZON-RIA\HORIZON Action Grant Budget-Based + + + + + + + + + + + + + https://zenodo.org/record/7351221 + + + +
+
+
+
+
\ No newline at end of file diff --git a/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/zenodo7351393.xml b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/zenodo7351393.xml new file mode 100644 index 000000000..21b656d2c --- /dev/null +++ b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/zenodo7351393.xml @@ -0,0 +1,100 @@ + + +
+ doi_________::07fdccabd77830e3caccf0b33c083f1b + 2022-11-25T01:08:31Z + under curation + +
+ + + + Monkeypox Knowledge Graph: A semantic resource embedding biological and chemical entities + Karki, Reagon + Andrea, Zaliani + Gadiya, Yojana + Gribbon, Philip + + + +

The Monkeypox KG is built using viral and human proteins reported in different resources. Additionally, the KG represents chemicals tested against Monkeypox and their targets, associated biological processes, molecular functions, diseases and side effects.

KG status

Version 1 stats:

  • Number of Nodes: 8235
  • Number of Edges: 40422

Version 2 stats (2nd September) :

  • Number of Nodes: 9129
  • Number of Edges: 44568

Please check the graph.ipynb for understanding step wise process of KG generation and KG statistics. The KG has been exported to formats such as graphml, sif and so on for visualizations in other platforms. For example, the graphml file can be imported to Cytoscape directly. These files are located in 'data\export' folder.

+ + + + Zenodo + + + + + + + + + + + + + + + + + + + oai:zenodo.org:7351393 + + oai:zenodo.org:7351393 + 10.5281/zenodo.7351393 + + + false + false + 0.9 + + + + + + corda__h2020::256485716fdb9f5ca69007b7ca5a072b + 101017536 + EOSC Future + EOSC Future + + + + ec__________::EC::H2020 + + + + + corda__h2020::4a3254eac2997eee0a9dcb7a7daedb81 + 101046203 + BY-COVID + Beyond COVID + + + + ec__________::EC::Horizon Europe Framework Programme - HORIZON-RIA\HORIZON Action Grant Budget-Based + + + + + + + + + + + + + https://zenodo.org/record/7351393 + + + +
+
+
+
+
\ No newline at end of file diff --git a/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/zenodo7353841.xml b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/zenodo7353841.xml new file mode 100644 index 000000000..4bd287e50 --- /dev/null +++ b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/eosc-future/zenodo7353841.xml @@ -0,0 +1,85 @@ + + +
+ doi_________::93d39dd7edef016928788c3500e149f1 + 2022-11-24T08:41:37Z + under curation + +
+ + + + ENVRI SP - Dashboard State of the Environment - Ocean Indicators + Tjerk Krijger + + + +

The attached .yaml file is used as input to the Dashboard State of the Environment, which is a science project of the ENVRI-FAIR science cluster within EOSC-FUTURE. The contents of the file enable the visualization of Ocean indicators on the dashboard. It is possible to download the attached file and change the contents to include indicators from different domains such as atmosphere or biodiversity.

+ + + + Zenodo + + + + + + + + + + + + + + + + + + + oai:zenodo.org:7353841 + + oai:zenodo.org:7353841 + 10.5281/zenodo.7353841 + + + false + false + 0.9 + + + + + + corda__h2020::256485716fdb9f5ca69007b7ca5a072b + 101017536 + EOSC Future + EOSC Future + + + + ec__________::EC::H2020 + + + + + + + + + + + + + https://zenodo.org/record/7353841 + + + +
+
+
+
+
diff --git a/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/fields.xml b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/fields.xml index 910a366f6..be2ee7b98 100644 --- a/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/fields.xml +++ b/dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/fields.xml @@ -2,11 +2,11 @@ - - - - - + + + + + @@ -14,17 +14,16 @@ - - - - + + + - - - - - - + + + + + + @@ -34,18 +33,17 @@ - - - + + - - - + + + - + - + @@ -54,35 +52,36 @@ - + - + - + - - + + - + - - + + + - - - + + + @@ -94,26 +93,29 @@ - + - - + + + + + - - + + - + - + - - + + - + @@ -132,13 +134,15 @@ + - + + - + @@ -156,20 +160,6 @@ - - - - - - - - - - - - - - - + \ No newline at end of file