Operational Research Literature as a Use Case for the Open Research Knowledge Graph
dc.bibliographicCitation.bookTitle | Mathematical Software – ICMS 2020 | eng |
dc.bibliographicCitation.firstPage | 327 | eng |
dc.bibliographicCitation.journalTitle | Lecture Notes in Computer Science | eng |
dc.bibliographicCitation.lastPage | 334 | eng |
dc.contributor.author | Runnwerth, Mila | |
dc.contributor.author | Stocker, Markus | |
dc.contributor.author | Auer, Sören | |
dc.contributor.editor | Bigatti, Anna Maria | |
dc.contributor.editor | Carette, Jacques | |
dc.contributor.editor | Davenport, James H. | |
dc.contributor.editor | Joswig, Michael | |
dc.contributor.editor | de Wolff, Timo | |
dc.date.accessioned | 2021-06-04T10:23:01Z | |
dc.date.available | 2021-06-04T10:23:01Z | |
dc.date.issued | 2020 | |
dc.description.abstract | The Open Research Knowledge Graph (ORKG) provides machine-actionable access to scholarly literature that habitually is written in prose. Following the FAIR principles, the ORKG makes traditional, human-coded knowledge findable, accessible, interoperable, and reusable in a structured manner in accordance with the Linked Open Data paradigm. At the moment, in ORKG papers are described manually, but in the long run the semantic depth of the literature at scale needs automation. Operational Research is a suitable test case for this vision because the mathematical field and, hence, its publication habits are highly structured: A mundane problem is formulated as a mathematical model, solved or approximated numerically, and evaluated systematically. We study the existing literature with respect to the Assembly Line Balancing Problem and derive a semantic description in accordance with the ORKG. Eventually, selected papers are ingested to test the semantic description and refine it further. | eng |
dc.description.version | submittedVersion | eng |
dc.identifier.uri | https://oa.tib.eu/renate/handle/123456789/6183 | |
dc.identifier.uri | https://doi.org/10.34657/5230 | |
dc.language.iso | eng | eng |
dc.publisher | Cham : Springer | eng |
dc.relation.doi | https://doi.org/10.1007/978-3-030-52200-1_32 | |
dc.relation.essn | 1611-3349 | |
dc.relation.isbn | 978-3-030-52199-8 | |
dc.relation.isbn | 978-3-030-52200-1 | |
dc.relation.issn | 0302-9743 | |
dc.rights.license | Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. | eng |
dc.subject.ddc | 020 | eng |
dc.subject.gnd | Konferenzschrift | ger |
dc.subject.other | Knowledge graph | eng |
dc.subject.other | Mathematical knowledge management | eng |
dc.subject.other | Operational research literature | eng |
dc.subject.other | Operations research literature | eng |
dc.title | Operational Research Literature as a Use Case for the Open Research Knowledge Graph | eng |
dc.type | BookPart | eng |
dc.type | Text | eng |
dcterms.event | International Congress on Mathematical Software, 7th International Conference, Braunschweig, Germany, July 13–16, 2020 | |
tib.accessRights | openAccess | eng |
wgl.contributor | TIB | eng |
wgl.subject | Informatik | eng |
wgl.type | Buchkapitel / Sammelwerksbeitrag | eng |
wgl.type | Konferenzbeitrag | eng |
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