ArticleScientific data2016
The FAIR Guiding Principles for scientific data management and stewardship.
Article in Scientific data, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5,558 papers, 1 of them a synthesis that pooled it.
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
5,558 citing papers in PubMed, 1 synthesis or guideline pooled it, 16,981 citations in OpenAlex.
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- The community engagement and empowerment cycle: FAIRagro's framework to foster cultural change towards FAIR RDM practices in agrosystem science and beyond.Journal of integrative bioinformatics · 2026Article
- Integrating cross-omics research through FAIR Digital Objects with DataPLANT.Journal of integrative bioinformatics · 2026Article
- Fragment-level FAIRness: annotating scientific data and its provenance using data fragment selectors.Journal of integrative bioinformatics · 2026Article
- Advancing methodological guidance for audio- and video-based observational studies of communication in nurse-patient encounters: A discussion paper.International journal of nursing studies advances · 2026Review
5,498 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
- Commented on by
- Erratum issued
Authors and funding
53 authors at 20 institutions in 10 countries.
Funding
Abstract
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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.