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FAIR DO Applications: Achievements and Challenges

Blumenröhr, Nicolas ORCID iD icon 1
1 Scientific Computing Center (SCC), Karlsruher Institut für Technologie (KIT)

Abstract:

Recent application cases of FAIR DOs in the context of Machine Learning show their usability to facilitate automated data processing and linking distributed data. However, the implementation and use of the FAIR DOs have highlighted the issues that need to be addressed in the future; i.e. the granularity of the data being represented by FAIR DOs (data sets vs data elements), the granularity of the attributes in the FAIR DO’s information record (general vs specific information), and the specifications for operations.


Volltext §
DOI: 10.5445/IR/1000158155
Veröffentlicht am 25.04.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Scientific Computing Center (SCC)
Publikationstyp Vortrag
Publikationsdatum 22.03.2023
Sprache Englisch
Identifikator KITopen-ID: 1000158155
HGF-Programm 46.21.05 (POF IV, LK 01) HMC
Veranstaltung 20th RDA Plenary Meeting (2023), Göteborg, Schweden, 21.03.2023 – 23.03.2023
Schlagwörter FAIR DOs, Machine Learning
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