Show simple item record

dc.identifier.uri Auer, Sören ger Kovtun, Viktor ger Prinz, Manuel ger Kasprzik, Anna ger Stocker, Markus ger 2018-05-24T10:31:34Z 2018-05-24T10:31:34Z 2018
dc.identifier.citation Auer, S.; Kovtun, V.; Prinz, M.; Kasprzik, A.; Stocker, M.: Towards a Knowledge Graph for Science. In: Proceedings of the 8th International Conference on Web Intelligence, Mining and Semantics (WIMS 2018), 6 S. ger
dc.description.abstract The document-centric workflows in science have reached (or already exceeded) the limits of adequacy. This is emphasized by recent discussions on the increasing proliferation of scientific literature and the reproducibility crisis. This presents an opportunity to rethink the dominant paradigm of document-centric scholarly information communication and transform it into knowledge-based information flows by representing and expressing information through semantically rich, interlinked knowledge graphs. At the core of knowledge-based information flows is the creation and evolution of information models that establish a common understanding of information communicated between stakeholders as well as the integration of these technologies into the infrastructure and processes of search and information exchange in the research library of the future. By integrating these models into existing and new research infrastructure services, the information structures that are currently still implicit and deeply hidden in documents can be made explicit and directly usable. This has the potential to revolutionize scientific work as information and research results can be seamlessly interlinked with each other and better matched to complex information needs. Furthermore, research results become directly comparable and easier to reuse. As our main contribution, we propose the vision of a knowledge graph for science, present a possible infrastructure for such a knowledge graph as well as our early attempts towards an implementation of the infrastructure. ger
dc.language.iso eng ger
dc.publisher New York : ACM
dc.relation.ispartof WIMS 2018: 8th International Conference on Web Intelligence, Mining and Semantics ger
dc.rights Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. ger
dc.subject Knowledge Graph eng
dc.subject Science and Technology eng
dc.subject Research Infrastructure eng
dc.subject Libraries eng
dc.subject Information Science eng
dc.subject Wissensgraphen ger
dc.subject.ddc 004 | Informatik ger
dc.subject.ddc 020 | Bibliotheks- und Informationswissenschaft ger
dc.title Towards a Knowledge Graph for Science ger
dc.type conferenceObject ger
dc.type Text ger
dc.relation.doi 10.1145/3227609.3227689
dc.description.version acceptedVersion ger
tib.accessRights frei zug�nglich ger

Files in this item

This item appears in the following Collection(s):

Show simple item record


Search the repository


My Account

Usage Statistics