Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD |
| Herausgeber/-innen | David Aveiro, Jan Dietz, Joaquim Filipe |
| Seiten | 64-75 |
| Seitenumfang | 12 |
| ISBN (elektronisch) | 9789897584749 |
| Publikationsstatus | Veröffentlicht - 2020 |
| Veranstaltung | 12th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2020 - Part of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2020 - Virtual, Online Dauer: 2 Nov. 2020 → 4 Nov. 2020 |
Publikationsreihe
| Name | IC3K 2020 - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management |
|---|---|
| Band | 2 |
Abstract
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.
ASJC Scopus Sachgebiete
- Betriebswirtschaft, Management und Rechnungswesen (insg.)
- Technologie- und Innovationsmanagement
- Betriebswirtschaft, Management und Rechnungswesen (insg.)
- Strategie und Management
- Informatik (insg.)
- Software
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- BibTex
- RIS
Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD. Hrsg. / David Aveiro; Jan Dietz; Joaquim Filipe. 2020. S. 64-75 (IC3K 2020 - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management; Band 2).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Semantic Representation of Physics Research Data
AU - Say, Aysegul
AU - Fathalla, Said
AU - Vahdati, Sahar
AU - Lehmann, Jens
AU - Auer, Sören
N1 - Funding Information: This work has been supported by ERC project Sci-enceGRAPH (grant no. 819536).
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Domain ontology
KW - Ontology engineering
KW - Physics
KW - Scholarly communication
KW - Semantic publishing
KW - Semantic web
UR - http://www.scopus.com/inward/record.url?scp=85101861653&partnerID=8YFLogxK
U2 - 10.5220/0010111000640075
DO - 10.5220/0010111000640075
M3 - Conference contribution
AN - SCOPUS:85101861653
T3 - IC3K 2020 - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
SP - 64
EP - 75
BT - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD
A2 - Aveiro, David
A2 - Dietz, Jan
A2 - Filipe, Joaquim
T2 - 12th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2020 - Part of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2020
Y2 - 2 November 2020 through 4 November 2020
ER -