Data associated with "Developing a standardized but extendable framework to increase the findability of infectious disease datasets"
Creators
- 1. Scripps Research
- 2. Boston College
- 3. Sanford Burnham Prebys Medical Discovery Institute
- 4. Baylor College of Medicine
- 5. Northwestern University Feinberg School of Medicine
- 6. National Institute of Allergy and Infectious Diseases
Description
Data associated with "Developing a standardized but extendable framework to increase the findability of infectious disease datasets"
Includes:
- NIAID Dataset schema
- NIAID ComputationalTool schema
- Crosswalk between NIAID schemas and common schemas
- Survey of Schema.org-compliant repositories
The open access movement and scientific reproducibility concerns have led the biomedical research community to embrace efforts to make scientific datasets openly accessible. While many datasets are now available, there are still challenges in ensuring that they are Findable, Accessible, Interoperable, and Reusable (FAIR). To improve the FAIRness of datasets, we evaluated dataset repositories for compliance with Schema.org standards – a collection of standards developed to increase metadata searchability across the internet. Adoption of the Schema.org Dataset standard was highly variable in biomedical research datasets, and the standard omitted many desirable metadata fields. We customized the Schema.org Dataset standard to catalog datasets collected across a Systems Biology research consortium consisting of 15 Centers. We developed a reusable process for creating a schema which is interoperable with other standards, but still extendable and customizable to a particular context. Here, we describe our process along with the associated gains in FAIRness, and discuss ongoing challenges with dataset discoverability – the first step to ensure that the vast amount of open data published by the research community is reused to its maximum value.
Notes
Files
File 2 - NIAID Systems Biology Dataset Schema and Crosswalk.pdf
Files
(642.4 kB)
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