ReviewDigital health
Data governance and open sharing in the fields of life sciences and medicine: A bibliometric analysis.
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Introducing Data Descriptors: A New Article Type to Advance Data-Driven Science.Journal of biomedical physics & engineering · 2026Article
- Tripartite evolutionary game analysis of medical data governance: interactions among government, medical institutions, and third-party assessment agencies.Frontiers in public health · 2026Article
- Reducing bias and enhancing equity in AI-enabled precision nutrition: addressing measurement error across wearables, multiomics, and dietary data.Frontiers in digital health · 2026Review
- Smart CAR-T Nanosymbionts: archetypes and proto-models.Frontiers in immunology · 2025Review
- From infectious diseases to chronic diseases: the paradigm shift of spatial epidemiology in disease prevention and control.Frontiers in public health · 2025Review
- Artificial intelligence in primary health care: A bibliometric analysis of publications from 2015 to 2024.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aims to conduct a bibliometric analysis of literature related to data governance and open sharing in the fields of life sciences and medicine, so as to clarify the characteristics of publications and explore research hotspots and trends. Methods: A total of 2529 valid documents published in the Web of Science Core Collection database from 2000 to 2024 were included in this study. VOSviewer was used for co-occurrence analysis, while CiteSpace was employed for clustering, burst detection, and thematic evolution analysis. Results: Between 2000 and 2024, the number of studies on data governance and open sharing in the fields of life sciences and medicine has increased annually, indicating the growing importance of research in this area. The USA led as the country with the most research output in this field. The University of Oxford was the institution with the highest publication volume, Amy L. McGuire was the most active author, and the Conclusions: Topics such as the FAIR principles, ethical issues, public attitudes toward data sharing, data quality, databases, and big data analysis techniques are hotspots in this field. Potential research frontiers include the FAIR principles, data quality, public trust and attitudes toward data sharing, the application of artificial intelligence technology in data governance and sharing, governance and sharing of epidemiological and public health data, governance and sharing of data on chronic diseases such as diabetes, and the construction of data governance models.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.