EVENTSKG: A 5-Star Dataset of Top-Ranked Events in Eight Computer Science Communities

dc.bibliographicCitation.bookTitleThe semantic webeng
dc.bibliographicCitation.firstPage427
dc.bibliographicCitation.journalTitleLecture notes in computer scienceeng
dc.bibliographicCitation.lastPage442
dc.bibliographicCitation.volume11503
dc.contributor.authorFathalla, Said
dc.contributor.authorLange, Christoph
dc.contributor.authorAuer, Sören
dc.contributor.editorHitzler, Pascal
dc.contributor.editorFernández, Miriam
dc.contributor.editorJanowicz, Krzysztof
dc.contributor.editorZaveri, Amrapali
dc.contributor.editorGray, Alasdair J.G.
dc.contributor.editorLopez, Vanessa
dc.contributor.editorHaller, Armin
dc.contributor.editorHammar, Karl
dc.date.accessioned2022-08-17T06:28:46Z
dc.date.available2022-08-17T06:28:46Z
dc.date.issued2019
dc.description.abstractMetadata of scientific events has become increasingly available on the Web, albeit often as raw data in various formats, disregarding its semantics and interlinking relations. This leads to restricting the usability of this data for, e.g., subsequent analyses and reasoning. Therefore, there is a pressing need to represent this data in a semantic representation, i.e., Linked Data. We present the new release of the EVENTSKG dataset, comprising comprehensive semantic descriptions of scientific events of eight computer science communities. Currently, EVENTSKG is a 5-star dataset containing metadata of 73 top-ranked event series (almost 2,000 events) established over the last five decades. The new release is a Linked Open Dataset adhering to an updated version of the Scientific Events Ontology, a reference ontology for event metadata representation, leading to richer and cleaner data. To facilitate the maintenance of EVENTSKG and to ensure its sustainability, EVENTSKG is coupled with a Java API that enables users to add/update events metadata without going into the details of the representation of the dataset. We shed light on events characteristics by analyzing EVENTSKG data, which provides a flexible means for customization in order to better understand the characteristics of renowned CS events.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/10065
dc.identifier.urihttp://dx.doi.org/10.34657/9103
dc.language.isoengeng
dc.publisherBerlin ; Heidelberg : Springer
dc.relation.doihttps://doi.org/10.1007/978-3-030-21348-0_28
dc.relation.essn1611-3349
dc.relation.isbn978-3-030-21348-0
dc.relation.isbn978-3-030-21347-3
dc.rights.licenseCC BY 4.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc004
dc.subject.gndKonferenzschriftger
dc.subject.other5-star dataseteng
dc.subject.otherEVENTSKGeng
dc.subject.otherLinked open dataeng
dc.subject.otherMetadata analysiseng
dc.subject.otherScholarly dataeng
dc.subject.otherScientific events ontologyeng
dc.titleEVENTSKG: A 5-Star Dataset of Top-Ranked Events in Eight Computer Science Communitieseng
dc.typeBookParteng
dc.typeTexteng
dcterms.eventExtended Semantic Web Conference (ESWC), June 2-6, 2019, Portorož, Slovenia
tib.accessRightsopenAccesseng
wgl.contributorTIBger
wgl.subjectInformatikger
wgl.typeBuchkapitel / Sammelwerksbeitragger
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