ArticleGigaScience2020
The Data Tags Suite (DATS) model for discovering data access and use requirements.
Article in GigaScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- WeChat in China's mobile health: a bibliometric analysis of trends, hotspots, and academic contributions.JAMIA open · 2026Review
- Datagraphy: toward a systematic approach to dataset discovery.GigaScience · 2025Article
- Getting your DUCs in a row - standardising the representation of Digital Use Conditions.Scientific data · 2024Article
- FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research.Frontiers in neuroinformatics · 2023Article
- The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR.Frontiers in neuroinformatics · 2023Review
- The role of metadata in reproducible computational research.Patterns (New York, N.Y.) · 2021Review
- Up-to-the-Minute Privacy PoliciesFrontiers in big data · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundData reuse is often controlled to protect the privacy of subjects and patients. Data discovery tools need ways to inform researchers about restrictions on data access and re-use.
resultsWe present elements in the Data Tags Suite (DATS) metadata schema describing data access, data use conditions, and consent information. DATS metadata are explained in terms of the administrative, legal, and technical systems used to protect confidential data.
conclusionsThe access and use metadata items in DATS are designed from the perspective of a researcher who wants to find and re-use existing data. We call for standard ways of describing informed consent and data use agreements that will enable automated systems for managing research data.
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.