Agenda Setting on FAIR Guidelines in the European Union and the Role of Expert Committees

Stocker, Misha; Stokmans, M.J.W.; Reisen, Mirjam van

doi:10.1162/dint_a_00168

Cited by 4 publications

(2 citation statements)

References 26 publications

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“…The higher FAIR compliance in databases focused on neuromuscular disorders could be attributed to the relatively specialized nature of these databases and patient advocacy which facilitated more focused and standardized data management practices [30,31]. Additionally, recent initiatives specially designed for data on neuromuscular disorders might have contributed to the higher FAIR adherence in these databases [32,33]. The in uence of EU policies, efforts, and funding assistance that promote data sharing and FAIR implementation may be related to the observed FAIR adherence in databases with a European focus [34,35].…”

Section: Discussionmentioning

confidence: 99%

Landscape analysis of available European data sources amenable for machine learning and recommendations on usability for rare diseases screening

Raycheva,

Kostadinov,

Mitova

et al. 2023

Preprint

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Background Patient registries and databases are essential tools for advancing clinical research in the area of rare diseases, as well as for enhancing patient care and healthcare planning. They are the only means of data pooling that can result in an adequate sample size for epidemiological and/or clinical research. They are crucial to determine the feasibility of clinical trials, and to promote the enrollment of patients. The primary aim of this study is a landscape analysis of available European data sources amenable to ML and their usability for Rare Diseases screening, in terms of FAIR, legal, and business considerations. Second, recommendations will be proposed to provide a better understanding of the health data ecosystem. Results In total, 330 unique replies were processed and analyzed, reflecting the same number of distinct databases (no duplicates included). In terms of geographical scope, we observed 24.2% (n = 80) national, 10.0% (n = 33) regional, 8.8% (n = 29) European, and 5.5% (n = 18) international registries coordinated in Europe. Over 80.0% (n = 269) of the databases were still active, with approximately 60.0% (n = 191) established after the year 2000 and 71.0% last collected new data in 2022. Regarding their geographical scope, European registries were associated with the highest overall FAIR adherence, while registries with regional and “other” geographical scope were ranked at the bottom of the list with the lowest proportion. Responders’ willingness to share data as a contribution to the goals of the Screen4Care project was evaluated at the end of the survey. This question was completed by 108 respondents; however, only 18 of them (16.7%) expressed a direct willingness to contribute to the project by sharing their databases. Among them, an equal split between pro-bono and paid services was observed. Conclusions The most important results of our study demonstrate not enough sufficient FAIR principles adherence and low willingness of the EU health databases to share patient information, combined with some legislation incapacities, resulting in barriers to the secondary use of data. The new EU governing structures, some already in action, are expecting to build trust in data providers and stimulate data sharing to promote accessibility and support ethical and sustainable innovation in healthcare.

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Section: Discussionmentioning

confidence: 99%

Landscape analysis of available European data sources amenable for machine learning and recommendations on usability for rare diseases screening

Raycheva,

Kostadinov,

Mitova

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Additionally, recent initiatives specially designed for data on neuromuscular disorders might have contributed to the higher FAIR adherence in these databases [39,40]. The influence of EU policies, efforts, and funding assistance that promote data sharing and FAIR implementation may be related to the observed FAIR adherence in databases with a European focus [41,42]. European databases might also benefit from standardized data sharing frameworks and infrastructure, enabling smoother data exchange and collaboration across European countries [43].…”

Section: Fairness Recommendationsmentioning

confidence: 99%

Landscape analysis of available European data sources amenable for machine learning and recommendations on usability for rare diseases screening

Raycheva,

Kostadinov,

Mitova

et al. 2024

Orphanet J Rare Dis

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Background Patient registries and databases are essential tools for advancing clinical research in the area of rare diseases, as well as for enhancing patient care and healthcare planning. The primary aim of this study is a landscape analysis of available European data sources amenable to machine learning (ML) and their usability for Rare Diseases screening, in terms of findable, accessible, interoperable, reusable(FAIR), legal, and business considerations. Second, recommendations will be proposed to provide a better understanding of the health data ecosystem. Methods In the period of March 2022 to December 2022, a cross-sectional study using a semi-structured questionnaire was conducted among potential respondents, identified as main contact person of a health-related databases. The design of the self-completed questionnaire survey instrument was based on information drawn from relevant scientific publications, quantitative and qualitative research, and scoping review on challenges in mapping European rare disease (RD) databases. To determine database characteristics associated with the adherence to the FAIR principles, legal and business aspects of database management Bayesian models were fitted. Results In total, 330 unique replies were processed and analyzed, reflecting the same number of distinct databases (no duplicates included). In terms of geographical scope, we observed 24.2% (n = 80) national, 10.0% (n = 33) regional, 8.8% (n = 29) European, and 5.5% (n = 18) international registries coordinated in Europe. Over 80.0% (n = 269) of the databases were still active, with approximately 60.0% (n = 191) established after the year 2000 and 71.0% last collected new data in 2022. Regarding their geographical scope, European registries were associated with the highest overall FAIR adherence, while registries with regional and “other” geographical scope were ranked at the bottom of the list with the lowest proportion. Responders’ willingness to share data as a contribution to the goals of the Screen4Care project was evaluated at the end of the survey. This question was completed by 108 respondents; however, only 18 of them (16.7%) expressed a direct willingness to contribute to the project by sharing their databases. Among them, an equal split between pro-bono and paid services was observed. Conclusions The most important results of our study demonstrate not enough sufficient FAIR principles adherence and low willingness of the EU health databases to share patient information, combined with some legislation incapacities, resulting in barriers to the secondary use of data.

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Incomplete COVID-19 Data: The Curation of Medical Health Data by the Virus Outbreak Data Network-Africa

et al. 2022

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The incompleteness of patient health data is a threat to the management of COVID-19 in Africa and globally. This has become particularly clear with the recent emergence of new variants of concern. The Virus Outbreak Data Network (VODAN)-Africa has studied the curation of patient health data in selected African countries and identified that health information flows often do not involve the use of health data at the point of care, which renders data production largely meaningless to those producing it. This modus operandi leads to disfranchisement over the control of health data, which is extracted to be processed elsewhere. In response to this problem, VODAN-Africa studied whether or not a design that makes local ownership and repositing of data central to the data curation process would 2 have a greater chance of being adopted. The design team based their work on the legal requirements of the European Union's General Data Protection Regulation (GDPR); the FAIR Guidelines on curating data as Findable, Accessible (under well-defined conditions), Interoperable and Reusable (FAIR); and national regulations applying in the context where the data is produced. The study concluded that the visiting of data curated as machine actionable and reposited in the locale where the data is produced and renders services has great potential for access to a wider variety of data. A condition of such innovation is that the innovation team is intradisciplinary, involving stakeholders and experts from all of the places where the innovation is designed, and employs a methodology of co-creation and capacity-building.

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Agenda Setting on FAIR Guidelines in the European Union and the Role of Expert Committees

Cited by 4 publications

References 26 publications

Landscape analysis of available European data sources amenable for machine learning and recommendations on usability for rare diseases screening

Landscape analysis of available European data sources amenable for machine learning and recommendations on usability for rare diseases screening

Landscape analysis of available European data sources amenable for machine learning and recommendations on usability for rare diseases screening

Incomplete COVID-19 Data: The Curation of Medical Health Data by the Virus Outbreak Data Network-Africa

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