Applications of Plasma-KG, a knowledge graph for low-temperature plasma physics
Markus M. Becker, Markus Stocker, Thomas Koprucki, Holger Israel, Ihda Chaerony Siffa, Hidir Aras, Burkhard Schmidt
Zenodo (CERN European Organization for Nuclear Research)
Problems Identified (5)
Structured data linking: Research data management needs structured representation and linking of data, information, and knowledge.
Persistent entity representation: Low-temperature plasma physics needs reusable entities represented with persistent identifiers.
Heterogeneous data source connection: Various data sources need to be connected through formally described entities.
Semantic content enrichment: Patents, scientific articles, and mathematical models are target application areas for content enrichment from knowledge graphs.
Structured data linking: Research data management needs structured representation and linking of data, information, and knowledge.
Proposed Solutions (5)
Plasma-KG knowledge graph: Plasma-KG is developed as a knowledge graph for low-temperature plasma physics based on Plasma-MDS and Plasma-O.
Formally described semantic entities: The approach uses formally described reusable entities with persistent identifiers to connect data sources.
Semantic data platform: Plasma-KG is presented as a semantic data platform for the future physics information service FID Physik.
Plasma-KG knowledge graph: Plasma-KG is developed as a knowledge graph for low-temperature plasma physics based on Plasma-MDS and Plasma-O.
Formally described semantic entities: The approach uses formally described reusable entities with persistent identifiers to connect data sources.
Results (3)
Plasma-KG concepts introduced:
Data sources connected:
KG content enrichment applications:
Research Domain
Low-temperature plasma physics research data management