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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月8日

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  • Yuxuan Xu

摘要

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.