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Wide-Open: Accelerating public data release by automating detection of overdue datasets
Maxim Grechkin1, Hoifung Poon2, Bill Howe1,3
1Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, Washington, United States of America.
Plos Biology
|June 9, 2017
Summary
Automated text mining identifies overdue open science datasets. This system successfully prompted the release of 400 datasets from major repositories, enhancing data sharing and reproducibility.
Area of Science:
- Bioinformatics
- Open Science
Background:
- Enforcing open data policies is challenging due to manual efforts lagging behind automated biological data generation.
- Reproducibility, data reuse, and novel discoveries are hindered by delayed public data release.
Discussion:
- A novel text mining approach was developed to automatically identify datasets overdue for public release.
- The Wide-Open system analyzes published articles and repository query results to detect private datasets.
- Effectiveness demonstrated on National Center for Biotechnology Information (NCBI) repositories: Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA).
Key Insights:
- The Wide-Open system successfully identified a substantial number of overdue datasets.
- This automated identification spurred direct administrative action, leading to the release of 400 datasets within a week.
- The approach offers a scalable solution for enforcing open data policies in biological research.
Outlook:
- Potential for broader application across diverse scientific repositories and data types.
- Facilitates improved compliance with open science mandates.
- Accelerates scientific progress through timely access to research data.
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