The Biomedical Research Hub: a federated platform for patient research data
Author(s) -
Craig Barnes,
Binam Bajracharya,
Matthew Cannalte,
Zakir Gowani,
Will Haley,
Taha KassHout,
Kyle M. Hernandez,
Michael Ingram,
Hara Prasad Juvvala,
Gina Kuffel,
Plamen Martinov,
Joe Maxwell,
John M. McCann,
Ankit Malhotra,
Noah Metoki-Shlubsky,
Chris Meyer,
Andre Paredes,
Jawad Qureshi,
Xenia Ritter,
L. Philip Schumm,
Mingfei Shao,
Urvi Sheth,
Trevar Simmons,
Alexander VanTol,
Zhenyu Zhang,
Robert L. Grossman
Publication year - 2021
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.614
H-Index - 150
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1093/jamia/ocab247
Subject(s) - computer science , cloud computing , interoperability , data sharing , world wide web , data access , metadata , identifier , middleware (distributed applications) , database , authentication (law) , computer security , computer network , operating system , medicine , alternative medicine , pathology
Objective The objective was to develop and operate a cloud-based federated system for managing, analyzing, and sharing patient data for research purposes, while allowing each resource sharing patient data to operate their component based upon their own governance rules. The federated system is called the Biomedical Research Hub (BRH). Materials and Methods The BRH is a cloud-based federated system built over a core set of software services called framework services. BRH framework services include authentication and authorization, services for generating and assessing findable, accessible, interoperable, and reusable (FAIR) data, and services for importing and exporting bulk clinical data. The BRH includes data resources providing data operated by different entities and workspaces that can access and analyze data from one or more of the data resources in the BRH. Results The BRH contains multiple data commons that in aggregate provide access to over 6 PB of research data from over 400 000 research participants. Discussion and conclusion With the growing acceptance of using public cloud computing platforms for biomedical research, and the growing use of opaque persistent digital identifiers for datasets, data objects, and other entities, there is now a foundation for systems that federate data from multiple independently operated data resources that expose FAIR application programming interfaces, each using a separate data model. Applications can be built that access data from one or more of the data resources.
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