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Standardizing Survey Data Collection to Enhance Reproducibility: Development and Comparative Evaluation of the ReproSchema Ecosystem

Standardizing Survey Data Collection to Enhance Reproducibility: Development and Comparative Evaluation of the ReproSchema Ecosystem

The findability, accessibility, interoperability, and reusability (FAIR) principles [15] provide high-level guidance for data management and sharing, ensuring that research data are well documented, discoverable, and reusable. While FAIR does not directly address study reproducibility, its principles support transparency and consistency in data handling, which are critical for reproducibility efforts.

Yibei Chen, Dorota Jarecka, Sanu Ann Abraham, Remi Gau, Evan Ng, Daniel M Low, Isaac Bevers, Alistair Johnson, Anisha Keshavan, Arno Klein, Jon Clucas, Zaliqa Rosli, Steven M Hodge, Janosch Linkersdörfer, Hauke Bartsch, Samir Das, Damien Fair, David Kennedy, Satrajit S Ghosh

J Med Internet Res 2025;27:e63343

Toward Interoperable Digital Medication Records on Fast Healthcare Interoperability Resources: Development and Technical Validation of a Minimal Core Dataset

Toward Interoperable Digital Medication Records on Fast Healthcare Interoperability Resources: Development and Technical Validation of a Minimal Core Dataset

Responding to the need to make digital data assets and their associated metadata more usable by machines and reusable by humans, Wilkinson et al [33], developed a set of 15 guiding principles for scientific data management and stewardship, which are grouped into the four higher principles of Findability, Accessibility, Interoperability, and Reusability (FAIR). Implementing the FAIR Principles is relevant to improving efficiency and access to research and health care data.

Eduardo Salgado-Baez, Raphael Heidepriem, Renate Delucchi Danhier, Eugenia Rinaldi, Vishnu Ravi, Akira-Sebastian Poncette, Iris Dahlhaus, Daniel Fürstenau, Felix Balzer, Sylvia Thun, Julian Sass

JMIR Med Inform 2025;13:e64099

Exploring Metadata Catalogs in Health Care Data Ecosystems: Taxonomy Development Study

Exploring Metadata Catalogs in Health Care Data Ecosystems: Taxonomy Development Study

To define the meta-dimensions, the FAIR framework was used [7]. These well-known data principles postulate an accepted approach to the discoverability and usability of RWD [19]. While FAIR emphasizes making data interoperable and reusable, it inherently involves considerations related to data governance and harmonization [40]. In step 2 in Figure 1, ending conditions for the iterative part of the process are defined, determining its termination criteria.

Simon Scheider, Mostafa Kamal Mallick

JMIR Form Res 2025;9:e63396

Toward Better Semantic Interoperability of Data Element Repositories in Medicine: Analysis Study

Toward Better Semantic Interoperability of Data Element Repositories in Medicine: Analysis Study

Practice of FAIR principles: finally, analyzing the repository’s adherence to the FAIR principles as a supplementary assessment. Data resources and services dimensions are primarily determined by repository and portal characteristics, while resource organization, quality control, and semantics leverage insights from relevant literature and the ISO/IEC 11179 standard. Practice of FAIR adheres to the FAIR principle and its 15 subprinciples.

Zhengyong Hu, Anran Wang, Yifan Duan, Jiayin Zhou, Wanfei Hu, Sizhu Wu

JMIR Med Inform 2024;12:e60293