The iTHRIV Commons: a cross-institution information and health research data sharing architecture and web application

Abstract

Objective: The integrated Translational Health Research Institute of Virginia (iTHRIV) aims to develop an information architecture to support data workflows throughout the research lifecycle for cross-state teams of translational researchers.

Materials and methods: The iTHRIV Commons is a cross-state harmonized infrastructure supporting resource discovery, targeted consultations, and research data workflows. As the front end to the iTHRIV Commons, the iTHRIV Research Concierge Portal supports federated login, personalized views, and secure interactions with objects in the ITHRIV Commons federation. The canonical use-case for the iTHRIV Commons involves an authenticated user connected to their respective high-security institutional network, accessing the iTHRIV Research Concierge Portal web application on their browser, and interfacing with multi-component iTHRIV Commons Landing Services installed behind the firewall at each participating institution.

Results: The iTHRIV Commons provides a technical framework, including both hardware and software resources located in the cloud and across partner institutions, that establishes standard representation of research objects, and applies local data governance rules to enable access to resources from a variety of stakeholders, both contributing and consuming.

Discussion: The launch of the Commons API service at partner sites and the addition of a public view of nonrestricted objects will remove barriers to data access for cross-state research teams while supporting compliance and the secure use of data.

Conclusions: The secure architecture, distributed APIs, and harmonized metadata of the iTHRIV Commons provide a methodology for compliant information and data sharing that can advance research productivity at Hub sites across the CTSA network.

Keywords: computer systems; data commons; health research software; information storage and retrieval; patient-generated health data.