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Applications of Plasma-KG, a knowledge graph for low-temperature plasma physics

2026application demonstrationapplicationsystem

Markus M. Becker, Markus Stocker, Ihda Chaerony Siffa, Hidir Aras, Burkhard Schmidt, Thomas Koprucki, Holger Israel

Zenodo (CERN European Organization for Nuclear Research)

https://doi.org/10.5281/zenodo.19217656OpenAlex: W7140326374
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Abstract Quality
GPT-5.5 Abstract Analysis

Problems Identified (5)

Structured Knowledge Representation: Research data management requires structured representation and linking of data, information, and knowledge.

Persistent Entity Representation: Low-temperature plasma physics needs reusable entities represented with persistent identifiers.

Semantic Data Source Integration: Various data sources need to be connected through formally described entities.

Structured Knowledge Representation: Research data management requires structured representation and linking of data, information, and knowledge.

Persistent Entity Representation: Low-temperature plasma physics needs reusable entities represented with persistent identifiers.

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.

Semantic Data Platform: Plasma-KG is positioned as a semantic data platform for the future physics information service FID Physik.

KG-Based Content Enrichment: The work applies content enrichment from knowledge graphs to patents, scientific articles, and mathematical models.

Plasma-KG Knowledge Graph: Plasma-KG is developed as a knowledge graph for low-temperature plasma physics based on Plasma-MDS and Plasma-O.

Semantic Data Platform: Plasma-KG is positioned as a semantic data platform for the future physics information service FID Physik.

Results (3)

Concept Introduction:

Data Source Connection Demonstration:

Application Coverage:

Research Domain

Research data management for low-temperature plasma physics

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