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Full Record Details
Persistent URL
http://purl.org/net/epubs/work/53762066
Record Status
Checked
Record Id
53762066
Title
Data FAIRness Practice
Contributors
Dr N Vizcaino (STFC Rutherford Appleton Lab.)
Abstract
FAIR synopsis. F.A.I.R breakdown in Findable, Accessible, Interoperable and Reusable and what do they mean in practice. GoFAIR and F-UJI interpretation of FAIR. DCAT along with other standards in this context (DOME code examples in JSON-LD). Cascade of concerns. Low scores in seemingly FAIR data. Tool software implementation and scoring issues. Link rot in metadata, destroyer of graph structure, and how to mitigate it (in practice) with FAIR PID strategies. Ontology standards. Avoiding hardcoding solutions.
Organisation
STFC
,
SCI-COMP
,
SCI-COMP-DST
Keywords
semantic,
,
FAIR,
,
Knowledge representation
,
AI
,
software engineering
,
metadata,
Funding Information
H2020
, The Digital Open Marketplace Ecosystem (DOME) 4.0 (953163)
Related Research Object(s):
Licence Information:
Creative Commons Attribution 4.0 International (CC BY 4.0)
Language
English (EN)
Type
Details
URI(s)
Local file(s)
Year
Presentation
Presented at DOME 4.0 Industrial Engagement Open Day and Hackathon, Bologna, Italy, 17-19 Jan 2023.
presentation2-FAIRness.zip
2023
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