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Semantic Representation of Physics Research Data

: Say, Aysegul; Fathalla, Said; Vahdati, Sahar; Lehmann, Jens; Auer, Sören


Aveiro, D. ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Proceedings. Vol.2: KEOD : November 2-4, 2020, web-based event
SciTePress, 2020
ISBN: 978-989-758-474-9
International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K) <12, 2020, Online>
International Conference on Knowledge Engineering and Ontology Development (KEOD) <12, 2020, Online>
Conference Paper
Fraunhofer IAIS ()
Semantic Web; domain ontology; Ontology Engineering; Semantic Publishing; Scholarly Communication; physics

Improvements in web technologies and artificial intelligence enable novel, more data-driven research practices for scientists. However, scientific knowledge generated from data-intensive research practices is disseminated with unstructured formats, thus hindering the scholarly communication in various respects. The traditional document-based representation of scholarly information hampers the reusability of research contributions. To address this concern, we developed the Physics Ontology (PhySci) to represent physics-related scholarly data in a machine-interpretable format. PhySci facilitates knowledge exploration, comparison, and organization of such data by representing it as knowledge graphs. It establishes a unique conceptualization to increase the visibility and accessibility to the digital content of physics publications. We present the iterative design principles by outlining a methodology for its development and applying three different evaluation approaches: data-driven and criteria-based evaluation, as well as ontology testing.