ArticleScientific data2022
Machine actionable metadata models.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed, 28 citations in OpenAlex.
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- When machines misread science: creating guardrails for human and AI interpretation of biomedical research.NPJ digital medicine · 2026Article
- The FAIR Case for A Coherent Interoperability to support NHS 10 Year Health Plan.Scientific data · 2026Article
- Large-scale manual curation and harmonization of metadata from metagenomic and cancer genomic repositories: challenges and solutions.Database : the journal of biological databases and curation · 2026Article
- Assessing the adoption of the FAIR principles in Italian environmental research infrastructures.Patterns (New York, N.Y.) · 2026Article
- Large-scale Manual Curation and Harmonization of Metadata from Metagenomic and Cancer Genomic Repositories: Challenges and Solutions.bioRxiv : the preprint server for biology · 2025Article
- The systematic assessment of completeness of public metadata accompanying omics studies in the Gene Expression Omnibus data repository.Genome biology · 2025Article
- Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies.Cell genomics · 2025Review
- Spatial and Temporal Analysis, and Machine Learning-Based Prediction of PCB Water Concentrations in U.S. Natural Water Systems.ACS ES&T water · 2025Article
- FAIR Header Reference genome: a TRUSTworthy standard.Briefings in bioinformatics · 2024Article
- Recording provenance of workflow runs with RO-Crate.PloS one · 2024Article
- Metadata recommendations for light logging and dosimetry datasets.BMC digital health · 2024Article
- SMetaS: A Sample Metadata Standardizer for Metabolomics.Metabolites · 2023Article
- Ten quick tips for avoiding pitfalls in multi-omics data integration analyses.PLoS computational biology · 2023Article
- FAIR in action - a flexible framework to guide FAIRification.Scientific data · 2023Article
- EGAsubmitter: A software to automate submission of nucleic acid sequencing data to the European Genome-phenome Archive.Frontiers in bioinformatics · 2023Article
- Modeling community standards for metadata as templates makes data FAIR.Scientific data · 2022Article
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 at 2 institutions in 1 country.
Funding
Abstract
Community-developed minimum information checklists are designed to drive the rich and consistent reporting of metadata, underpinning the reproducibility and reuse of the data. These reporting guidelines, however, are usually in the form of narratives intended for human consumption. Modular and reusable machine-readable versions are also needed. Firstly, to provide the necessary quantitative and verifiable measures of the degree to which the metadata descriptors meet these community requirements, a requirement of the FAIR Principles. Secondly, to encourage the creation of standards-driven templates for metadata authoring, especially when describing complex experiments that require multiple reporting guidelines to be used in combination or extended. We present new functionalities to support the creation and improvements of machine-readable models. We apply the approach to an exemplar set of reporting guidelines in Life Science and discuss the challenges. Our work, targeted to developers of standards and those familiar with standards, promotes the concept of compositional metadata elements and encourages the creation of community-standards which are modular and interoperable from the onset.
Indexed as
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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.