Desiderata for discoverability and FAIR adoption of health data hubs

IF 4 2区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Celia Alvarez-Romero , Máximo Bernabeu-Wittel , Carlos Luis Parra-Calderón , Silvia Rodríguez Mejías , Alicia Martínez-García
{"title":"Desiderata for discoverability and FAIR adoption of health data hubs","authors":"Celia Alvarez-Romero ,&nbsp;Máximo Bernabeu-Wittel ,&nbsp;Carlos Luis Parra-Calderón ,&nbsp;Silvia Rodríguez Mejías ,&nbsp;Alicia Martínez-García","doi":"10.1016/j.jbi.2024.104700","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>The future European Health Research and Innovation Cloud (HRIC), as fundamental part of the European Health Data Space (EHDS), will promote the secondary use of data and the capabilities to push the boundaries of health research within an ethical and legally compliant framework that reinforces the trust of patients and citizens.</p></div><div><h3>Objective</h3><p>This study aimed to analyse health data management mechanisms in Europe to determine their alignment with FAIR principles and data discovery generating best.</p><p>practices for new data hubs joining the HRIC ecosystem. In this line, the compliance of health data hubs with FAIR principles and data discovery were assessed, and a set of best practices for health data hubs was concluded.</p></div><div><h3>Methods</h3><p>A survey was conducted in January 2022, involving 99 representative health data hubs from multiple countries, and 42 responses were obtained in June 2022. Stratification methods were employed to cover different levels of granularity. The survey data was analysed to assess compliance with FAIR and data discovery principles. The study started with a general analysis of survey responses, followed by the creation of specific profiles based on three categories: organization type, function, and level of data aggregation.</p></div><div><h3>Results</h3><p>The study produced specific best practices for data hubs regarding the adoption of FAIR principles and data discoverability. It also provided an overview of the survey study and specific profiles derived from category analysis, considering different types of data hubs.</p></div><div><h3>Conclusions</h3><p>The study concluded that a significant number of health data hubs in Europe did not fully comply with FAIR and data discovery principles. However, the study identified specific best practices that can guide new data hubs in adhering to these principles. The study highlighted the importance of aligning health data management mechanisms with FAIR principles to enhance interoperability and reusability in the future HRIC.</p></div>","PeriodicalId":15263,"journal":{"name":"Journal of Biomedical Informatics","volume":"157 ","pages":"Article 104700"},"PeriodicalIF":4.0000,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1532046424001187/pdfft?md5=8528674c63bb931855f719c8a92b3d67&pid=1-s2.0-S1532046424001187-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biomedical Informatics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1532046424001187","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

Background

The future European Health Research and Innovation Cloud (HRIC), as fundamental part of the European Health Data Space (EHDS), will promote the secondary use of data and the capabilities to push the boundaries of health research within an ethical and legally compliant framework that reinforces the trust of patients and citizens.

Objective

This study aimed to analyse health data management mechanisms in Europe to determine their alignment with FAIR principles and data discovery generating best.

practices for new data hubs joining the HRIC ecosystem. In this line, the compliance of health data hubs with FAIR principles and data discovery were assessed, and a set of best practices for health data hubs was concluded.

Methods

A survey was conducted in January 2022, involving 99 representative health data hubs from multiple countries, and 42 responses were obtained in June 2022. Stratification methods were employed to cover different levels of granularity. The survey data was analysed to assess compliance with FAIR and data discovery principles. The study started with a general analysis of survey responses, followed by the creation of specific profiles based on three categories: organization type, function, and level of data aggregation.

Results

The study produced specific best practices for data hubs regarding the adoption of FAIR principles and data discoverability. It also provided an overview of the survey study and specific profiles derived from category analysis, considering different types of data hubs.

Conclusions

The study concluded that a significant number of health data hubs in Europe did not fully comply with FAIR and data discovery principles. However, the study identified specific best practices that can guide new data hubs in adhering to these principles. The study highlighted the importance of aligning health data management mechanisms with FAIR principles to enhance interoperability and reusability in the future HRIC.

Abstract Image

健康数据中心的可发现性和 FAIR 采用的预期目标
背景未来的欧洲健康研究与创新云(HRIC)作为欧洲健康数据空间(EHDS)的重要组成部分,将促进数据的二次利用,并在符合道德和法律的框架内推动健康研究的发展,从而加强患者和公民的信任。目标本研究旨在分析欧洲的健康数据管理机制,以确定其是否符合公平与公正原则(FAIR)和数据发现,为加入 HRIC 生态系统的新数据中心提供最佳实践。研究方法 2022 年 1 月进行了一项调查,涉及多个国家的 99 个具有代表性的健康数据中心,2022 年 6 月获得了 42 份回复。采用了分层方法,以覆盖不同的粒度水平。对调查数据进行了分析,以评估其是否符合 FAIR 和数据发现原则。研究首先对调查回复进行了总体分析,然后根据组织类型、职能和数据聚合程度这三个类别创建了具体的概况。研究还概述了调查研究的情况,以及考虑到不同类型的数据中心,从类别分析中得出的具体概况。结论研究得出结论,欧洲有相当数量的健康数据中心没有完全遵守 FAIR 和数据发现原则。不过,研究发现了一些具体的最佳实践,可以指导新的数据中心遵守这些原则。该研究强调了使健康数据管理机制符合 FAIR 原则的重要性,以提高未来 HRIC 的互操作性和可重用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Biomedical Informatics
Journal of Biomedical Informatics 医学-计算机:跨学科应用
CiteScore
8.90
自引率
6.70%
发文量
243
审稿时长
32 days
期刊介绍: The Journal of Biomedical Informatics reflects a commitment to high-quality original research papers, reviews, and commentaries in the area of biomedical informatics methodology. Although we publish articles motivated by applications in the biomedical sciences (for example, clinical medicine, health care, population health, and translational bioinformatics), the journal emphasizes reports of new methodologies and techniques that have general applicability and that form the basis for the evolving science of biomedical informatics. Articles on medical devices; evaluations of implemented systems (including clinical trials of information technologies); or papers that provide insight into a biological process, a specific disease, or treatment options would generally be more suitable for publication in other venues. Papers on applications of signal processing and image analysis are often more suitable for biomedical engineering journals or other informatics journals, although we do publish papers that emphasize the information management and knowledge representation/modeling issues that arise in the storage and use of biological signals and images. System descriptions are welcome if they illustrate and substantiate the underlying methodology that is the principal focus of the report and an effort is made to address the generalizability and/or range of application of that methodology. Note also that, given the international nature of JBI, papers that deal with specific languages other than English, or with country-specific health systems or approaches, are acceptable for JBI only if they offer generalizable lessons that are relevant to the broad JBI readership, regardless of their country, language, culture, or health system.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信