Improving Research Data findability with FAIR Signposting: implementation insights from KonsortSWD Data Centers
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| Title: | Improving Research Data findability with FAIR Signposting: implementation insights from KonsortSWD Data Centers |
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| Authors: | Saldanha Bach, Janete, Mathiak, Brigitte, Zhang, Yudong, Mutschke, Peter |
| Publisher Information: | Zenodo, 2025. |
| Publication Year: | 2025 |
| Subject Terms: | FAIR data, FAIR Principles, Metadata standards, Research Data findability, Data FAIRness, FAIR Signposting, FAIR Automated assessment |
| Description: | The FAIR Principles are open to interpretation, which results in varying assessments of compliance by different FAIR assessment instruments, such as F-UJI, Each of these tools uses slightly different approaches to measure FAIRness. FAIR Signposting plays a critical role in standardizing assessments of FAIRness, reducing inconsistencies, and ensuring a more consistent interpretation of the FAIR Principles across various assessment platforms. This is particularly relevant in the context of a pilot project of the KonsortSWD consortium of the German National Research Data Infrastructure (NFDI), which addresses challenges in evaluating and improving the FAIRness, particularly the findability, of research data. This project implements the FAIR Signposting standard, a set of machine-readable, HTTP-based link relations, designed to standardize metadata exposure and improve automated FAIR assessments. It embeds standard relation types (such as cite-as, describedby, license, author, item, and collection) into HTML headers, HTTP responses, or standalone linkset documents, guiding automated agents—such as search engines, data harvesters, and FAIR assessment tools - to the metadata, persistent identifiers (PIDs), and related resources associated with digital objects. A two-part strategy was employed: first, the deployment of a prototype at GESIS - Leibniz Institute for the Social Sciences and with partner data centers (e.g., the Leibniz Institute for Educational Trajectories (LIfBi), the Leibniz-Institute for Research and Information in Education (DIPF), the German Institute for Economic Research (DIW/SOEP), and the German Centre for Higher Education Research and Science Studies (DZHW); second, the development of a best practices document based on implementation experiences. The application of FAIR Signposting significantly increased FAIRness scores—GESIS saw an increase from 43% to 88%, and LIfBi from 41% to 100%. The project demonstrates that embedding standard link relations in metadata (via HTTP headers or standalone linksets) enhances metadata interoperability, discoverability, and machine-readability. Tools like F-UJI were used to measure these improvements. The contribution offers practical guidance, implementation examples, and FAIR Signposting validation tools to support broader adoption across research data centers. KonsortSWD is funded by the German Research Foundation (DFG) as part of the NFDI – Project number: 42494171 Results have been generated with F-UJI based on FsF Metrics v0.8, Domain agnostic |
| Document Type: | Conference object |
| Language: | English |
| DOI: | 10.5281/zenodo.17151838 |
| DOI: | 10.5281/zenodo.17151837 |
| Rights: | CC BY |
| Accession Number: | edsair.doi.dedup.....25d8135a11e5235c43ee3765f30a5ab8 |
| Database: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstract: | The FAIR Principles are open to interpretation, which results in varying assessments of compliance by different FAIR assessment instruments, such as F-UJI, Each of these tools uses slightly different approaches to measure FAIRness. FAIR Signposting plays a critical role in standardizing assessments of FAIRness, reducing inconsistencies, and ensuring a more consistent interpretation of the FAIR Principles across various assessment platforms. This is particularly relevant in the context of a pilot project of the KonsortSWD consortium of the German National Research Data Infrastructure (NFDI), which addresses challenges in evaluating and improving the FAIRness, particularly the findability, of research data. This project implements the FAIR Signposting standard, a set of machine-readable, HTTP-based link relations, designed to standardize metadata exposure and improve automated FAIR assessments. It embeds standard relation types (such as cite-as, describedby, license, author, item, and collection) into HTML headers, HTTP responses, or standalone linkset documents, guiding automated agents—such as search engines, data harvesters, and FAIR assessment tools - to the metadata, persistent identifiers (PIDs), and related resources associated with digital objects. A two-part strategy was employed: first, the deployment of a prototype at GESIS - Leibniz Institute for the Social Sciences and with partner data centers (e.g., the Leibniz Institute for Educational Trajectories (LIfBi), the Leibniz-Institute for Research and Information in Education (DIPF), the German Institute for Economic Research (DIW/SOEP), and the German Centre for Higher Education Research and Science Studies (DZHW); second, the development of a best practices document based on implementation experiences. The application of FAIR Signposting significantly increased FAIRness scores—GESIS saw an increase from 43% to 88%, and LIfBi from 41% to 100%. The project demonstrates that embedding standard link relations in metadata (via HTTP headers or standalone linksets) enhances metadata interoperability, discoverability, and machine-readability. Tools like F-UJI were used to measure these improvements. The contribution offers practical guidance, implementation examples, and FAIR Signposting validation tools to support broader adoption across research data centers.<br />KonsortSWD is funded by the German Research Foundation (DFG) as part of the NFDI – Project number: 42494171<br />Results have been generated with F-UJI based on FsF Metrics v0.8, Domain agnostic |
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| DOI: | 10.5281/zenodo.17151838 |