Implementation & Adoption Stories

The FAIR-IMPACT Implementation stories illustrate good practices in research communities and organisations to support the implementation of the FAIR principles.

Implementation Story

Improving FAIRness for GeoSphere Austria

A team from GeoSphere Austria used F-UJI to assess and improve the FAIRness of their data repository.

FAIRness Assessment Challenge. During the 3-month challenge participants took part in three virtual workshops to self-assess and incrementally improve the FAIRness of their selected outputs. During the support action, participants benefited from interacting with a group of mentors representing the various FAIRness assessment tools and methods.

Authors:

Matthias Schwarz, GeoSphere Austria

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Implementation Story

Assessing the FAIRness of the Erasmus University Rotterdam Data Repository

A research data steward from Erasmus University Rotterdam used two different tools, F-UJI and FDMM, to assess and improve the FAIRness of their institutional data repository.

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Implementation Story

Approaching FAIRness Assessment as a Vocabulary Curator

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Implementation Story

Coming full circle: A diversity of approaches to improve the FAIRness of a biodiversity ontology repository

A senior knowledge architect from the Institute for Applied Informatics at Leipzig University experimented with a range of assessment approaches, including automated tools like O’FAIRe and non-automated assessment methods, in order to improve the FAIRness of the NFDI4Biodiversity project ontologies prior to the transition to a new portal.

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Implementation Story

Translating FAIR assessment results into improved metadata and workflow procedures in a social sciences data repository in Bosnia and Herzegovina

A coordinator of the Data Archive for Social Sciences in Bosnia andHerzegovina (DASS-BiH) used F-UJI and FDMM to assess the FAIRness of datasets in the catalogue, with the aim of translating the assessment results into practical actions and workflow procedures in the repository.

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Implementation Story

First impressions on FAIRness from technology consultancy firm Datrix

A team from the technology consultancy firm Datrix starts their FAIRness journey by testing the F-UJI tool for FAIRness assessment on some of their project datasets.

Authors:

Matteo Bregonzio, Datrix S.p.A
Alsu Shakirzyanova, Datrix S.p.A
Clara Linés, Digital Curation Centre (DCC)

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Implementation Story

Applying the FAIR Data Maturity Model at the German Medical Data Integration Centers

FAIRness Assessment Challenge

Participants from the Medical Informatics Laboratory at the University Medicine Greifswald and the Berlin Institute of Health in Germany sought guidance for using FAIR tools to undertake a FAIR assessment and improve the FAIRness of their Core Dataset, used within the German Medical Informatics Initiative.

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Implementation Story

FAIRness assessment of vocabularies: Insights from the British Oceanographic Data Centre team

FAIRness Assessment Challenge

A team from the British Oceanographic Data Centre tested different methods and tools (10 simple rules, recommendations for FAIR semantics, O’FAIRe, FOOPS!, and F-UJI) in the task of assessing the FAIRness of their controlled vocabulary.

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Implementation Story

FAIRness assessment in the Life Cycle Assessment domain

FAIRness Assessment Challenge

A researcher from the Life Cycle Assessment (LCA) domain assessed the FAIRness of one of their datasets using F-UJI and an ontology using FOOPS! and FAIRsFAIR Semantic Recommendations, as part of broader ongoing efforts to understand the level of FAIRness in the LCA domain and gain insights to define good practice workflows for data sharing.

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Implementation Story

FAIRness assessment as a catalyst of chemistry research repository transformation in Germany

FAIRness Asssement Challenge

A team from FIZ Karlsruhe - Leibniz Institute for Information Infrastructure used F-UJI to assess the FAIRness of representative datasets from the RADAR4Chem repository, which helped them identify some improvements and inspired them to include a FAIRness check functionality in their repository.

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Implementation Story

Making the metadata machine-readable to increase FAIRness of medical data in Poland

FAIRness Asssement Challenge

A team from the Medical University of Gdansk (MUG) Main Library increased the FAIRness and machine readability of their repository datasets with the help of the F-UJI tool.

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Implementation Story

FAIRness assessment of datasets and ontologies at Eurac Research

FAIRness Asssement Challenge

A team from Eurac Research assessed the FAIRness of a dataset hosted in their Environmental Data Platform using F-UJI and an ontology using O’FAIRe. After an initial low score in F-UJI, they implemented signposting to improve the machine interoperability of their metadata catalogue.

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