Dataset Open Access
Tsueng, Ginger;
Alvarado Cano, Marco A.;
Bento, José;
Czech, Candice;
Pache, Lars;
Savidge, Tor C.;
Starren, Justin;
Rasmussen, Luke V.;
Mengjia (Marjorie) Kang;
Wu, Qinglong;
Xin, Jiwen;
Zhou, Xinghua;
Su, Andrew I.;
Wu, Chunlei;
Brown, Liliana;
Shabman, Reed S.;
Hughes, Laura D.
Data associated with "Developing a standardized but extendable framework to increase the findability of infectious disease datasets"
Includes:
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.
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