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Full Record Details
Persistent URL
http://purl.org/net/epubs/work/58030046
Record Status
Checked
Record Id
58030046
Title
Adapting FAIR evaluation to photon and neutron facilities
Contributors
Simon Lambert (STFC Rutherford Appleton Lab.)
,
Abigail McBirnie (STFC Rutherford Appleton Lab.)
,
Brian Matthews (STFC Rutherford Appleton Lab.)
Abstract
The FAIR principles (Wilkinson 2015) have become an essential principle in establishing transparent research practices, and initiatives such as the European Open Science Cloud (EOSC) aims that all supported data and services to be FAIR1. Thus data providers need to be able to validate the FAIR-ness of their data; however the FAIR principles are guidelines indicating the features expected for data to be FAIR, and do not stipulate evaluation criteria. Consequently, there has been a proliferation of approaches to FAIR evaluation, to substantiate claims for FAIRness, establish baselines, and measure improvement. Some approaches are focussed on FAIRness of individual datasets, others of repositories; some require extensive human evaluation, others use automation. However we contend that within some scientific domains, something is missing. In these domains, data generation and management follow well-defined processes that result in datasets annotated with metadata and archived in repositories. Existing FAIR evaluation methods focus on metrics for these datasets and repositories, but the crucial contribution of the processes used in collecting and analysing data to ensuring FAIR research outputs has been considered in less detail. In this paper we consider evaluating the FAIR-ness of data derived from experiments undertaken at facilities operated by Photon and Neutron Research Infrastructures (PaN RIs), which have in general well-defined experimental processes with systematic human and IT support. PaN RIs also need to ensure that the use of their facilities leads to transparent and reusable results. Consequently, an appropriate FAIR evaluation method would consider how those processes deliver FAIR data. Further, we would contend that our approach forms an exemplar of the FAIR evaluation of research processes and is generalisable to other domains beyond that of PaN RIs.
Organisation
STFC
,
SCI-COMP
,
SCI-COMP-DST
Keywords
Funding Information
EU
, Horizon 2020 (857641)
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 18th International Digital Curation Conference (IDCC24), Edinburgh, Scotland, 19-21 Feb 2024.
IDCC24-FAIREvaluation-Abstract.pdf
2024
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