Developing a standardized but extendable framework to increase the findability of infectious disease datasets

Author:

Tsueng GingerORCID,Alvarado Cano Marco A.ORCID,Bento JoséORCID,Czech Candice,Kang MengjiaORCID,Pache LarsORCID,Rasmussen Luke V.ORCID,Savidge Tor C.ORCID,Starren Justin,Wu QinglongORCID,Xin JiwenORCID,Yeaman Michael R.ORCID,Zhou XinghuaORCID,Su Andrew I.ORCID,Wu ChunleiORCID,Brown Liliana,Shabman Reed S.ORCID,Hughes Laura D.ORCID,

Abstract

AbstractBiomedical datasets are increasing in size, stored in many repositories, and face challenges in FAIRness (findability, accessibility, interoperability, reusability). As a Consortium of infectious disease researchers from 15 Centers, we aim to adopt open science practices to promote transparency, encourage reproducibility, and accelerate research advances through data reuse. To improve FAIRness of our datasets and computational tools, we evaluated metadata standards across established biomedical data repositories. The vast majority do not adhere to a single standard, such asSchema.org, which is widely-adopted by generalist repositories. Consequently, datasets in these repositories are not findable in aggregation projects like Google Dataset Search. We alleviated this gap by creating a reusable metadata schema based onSchema.organd catalogued nearly 400 datasets and computational tools we collected. The approach is easily reusable to create schemas interoperable with community standards, but customized to a particular context. Our approach enabled data discovery, increased the reusability of datasets from a large research consortium, and accelerated research. Lastly, we discuss ongoing challenges with FAIRness beyond discoverability.

Publisher

Cold Spring Harbor Laboratory

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