ReviewBriefings in bioinformatics2024
Sharing sensitive data in life sciences: an overview of centralized and federated approaches.
Review in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Enhancing semantic interoperability in precision medicine: converting OMOP CDM to Beacon v2 in the Spanish IMPaCT-Data project.BMC medical informatics and decision making · 2026Article
- Unlocking the Power of Data Harmonization in Environmental Health Sciences: A Comprehensive Exploration of Significance, Use Cases, and Recommendations for Standardization Efforts.Environmental health perspectives · 2026Review
- Toward a Common Set of Interface Requirements for Genomic Data Management: Scoping Review.Journal of medical Internet research · 2026Article
- Topic-specific living databases of clinical trials: A scoping review of public databases.Clinical trials (London, England) · 2026Article
- Beyond the dataset: integrating public voices in data science.Research involvement and engagement · 2026Article
- A maturity model framework for federated networks of trusted research environments.Frontiers in digital health · 2026Article
- From data silos to actionable insights: a comparative evaluation of data access models and practical guidelines for animal health surveillance.Frontiers in veterinary science · 2026Article
- Federated, governed, and interoperable? The emerging architecture of public human genomic data infrastructures: a European perspective.Frontiers in genetics · 2026Review
- Turning data into insights in Jub, an extensible generic big data platform for life science and healthcare applications.Scientific reports · 2025Article
- MINDDS-connect: a federated data platform integrating biobanks for meta cohort building and analysis.European journal of human genetics : EJHG · 2025Article
- How the world of biobanking is changing with artificial intelligence.Frontiers in digital health · 2025Review
- Publicly available continuously updated topic specific databases of randomised clinical trials: A scoping review.medRxiv : the preprint server for health sciences · 2024Article
- Lessons from federated networks for implementing the European health data space. Empirical study.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
22 authors.
Funding
Abstract
Biomedical data are generated and collected from various sources, including medical imaging, laboratory tests and genome sequencing. Sharing these data for research can help address unmet health needs, contribute to scientific breakthroughs, accelerate the development of more effective treatments and inform public health policy. Due to the potential sensitivity of such data, however, privacy concerns have led to policies that restrict data sharing. In addition, sharing sensitive data requires a secure and robust infrastructure with appropriate storage solutions. Here, we examine and compare the centralized and federated data sharing models through the prism of five large-scale and real-world use cases of strategic significance within the European data sharing landscape: the French Health Data Hub, the BBMRI-ERIC Colorectal Cancer Cohort, the federated European Genome-phenome Archive, the Observational Medical Outcomes Partnership/OHDSI network and the EBRAINS Medical Informatics Platform. Our analysis indicates that centralized models facilitate data linkage, harmonization and interoperability, while federated models facilitate scaling up and legal compliance, as the data typically reside on the data generator's premises, allowing for better control of how data are shared. This comparative study thus offers guidance on the selection of the most appropriate sharing strategy for sensitive datasets and provides key insights for informed decision-making in data sharing efforts.
Indexed as
Identifiers
What Socratic 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 Socratic graph.