Event Files are Common, But Semantic Event Metadata Remain Uneven in OpenNeuro BIDS Datasets.

Overview

1. College of Computing, Georgia Institute of Technology, Atlanta, GA USA

Abstract

Open neuroscience repositories support reuse by making datasets accessible, but event level reuse also depends on whether task and stimulus annotations can be interpreted by software. I audited public latest OpenNeuro BIDS snapshots using public GraphQL metadata, recursive file trees, small events.json sidecars, and bounded events.tsv header ranges. Raw neural data were left untouched. Among 1,713 public latest snapshots, 1,483 had task metadata or observed event TSV files and formed the primary event relevant denominator. Event TSV files were present in 1,175/1,483 snapshots (79.2%; Wilson 95% CI 77.1%-81.2%). Candidate event JSON sidecars were present in 604/1,483 snapshots (40.7%), but an inheritance aware path and entity check found applicable JSON sidecars for 590/1,483 (39.8%), descriptive applicable sidecars for 550/1,483 (37.1%), and experiment specific applicable sidecars for 491/1,483 (33.1%). Across the full recursive file tree, 162,034/301,681 event TSV files (53.7%) had an applicable event JSON sidecar, and 147,412/301,681 (48.9%) had an applicable experiment specific sidecar. HED was detected in event JSON for 45/1,483 snapshots (3.0%) and in sampled TSV headers for 2/1,483 (0.13%). EEG had higher sidecar coverage and HED detection than fMRI, but 21.2% of EEG candidate JSON files were bookkeeping only. These results identify a repository visible metadata gap: event timing is common, but software interpretable event meaning remains uneven.

Supplementary Information: The online version contains supplementary material available at 10.1007/s12021-026-09797-y.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper links to its data, not to its authors' code: see the Data section.

Code Availability

Online Resource 1 includes the analysis and validation code needed to reproduce the reported audit tables and figures. The validation checks required files, result table consistency, figure non blankness and PDF validity, manifest hashes when present, family summary consistency, and key audit invariants. The advisory prototype is implemented as analysis output rather than as a standalone BIDS Validator plugin; the dataset metrics table includes the advisory category for each snapshot.

Reproduced under the paper's license (CC BY), from the paper cited above.

Tracing map

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Data

Datasets cited

• docs.openneuro.org/api.html, at docs.openneuro.org; found in the references
• docs.openneuro.org/policy/data_management_plans.html, at docs.openneuro.org; found in the references
• openneuro.org/crn/graphql, at openneuro.org; found in “Data Availability”

Data Availability Statement

Source dataset and latest snapshot metadata are publicly accessible through OpenNeuro and the OpenNeuro GraphQL API at https://openneuro.org/crn/graphql. The submitted Online Resource 1 supplementary package contains derived dataset level metrics, family summaries, summary JSON, figure outputs, code, requirements, validation outputs, and reproducibility notes. No raw neural data are redistributed.

Online Resource 1 includes the analysis and validation code needed to reproduce the reported audit tables and figures. The validation checks required files, result table consistency, figure non blankness and PDF validity, manifest hashes when present, family summary consistency, and key audit invariants. The advisory prototype is implemented as analysis output rather than as a standalone BIDS Validator plugin; the dataset metrics table includes the advisory category for each snapshot.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 2, 28 September 2026

• Publisher: n/a → Springer Science+Business Media

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 1 author, 6 keywords, 7 MeSH terms, 9 references.

Cite

This paper

Xu, Y. (2026). Event Files are Common, But Semantic Event Metadata Remain Uneven in OpenNeuro BIDS Datasets. Neuroinformatics, 24(3), 40. https://doi.org/10.1007/s12021-026-09797-y

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