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CTSAconnect: A Linked Open Data approach to represent clinical and research expertise, activities, and resources

The CTSAconnect Consoritum was awarded an 18-month contract from Booz Allen Hamilton and the National Center for Advancing Translational Sciences (NCATS) to begin work on the CTSAconnect project. The CTSAconnect project is a collaboration between members of the OHSU Ontology Development Group, the Oregon Clinical & Translational Research Institute, eagle-i (eagle-i.net), VIVO (vivoweb.org), and ShareCenter (ctsasharecenter.org) and aims to integrate research and clinical activities and resources to better identify people's expertise and relevant resources.

Teams of scientists are now much more common than single scientists in the production of biologically meaningful and clinically consequential breakthroughs. There are myriad data sources about investigators, physicians, research resources, clinical encounters, and expertise to promote team interaction. However, it is still often difficult for investigators to find active researchers and research resources in their field much of this valuable information is locked in silos and is not easily connected. When discovery occurs, it is usually by a combination of personal connections, domain knowledge, and fortuitous discovery. The absence of efficient, reliable methods for discovering resources and expertise is a significant impediment to the basic sciences and to clinical and translational research. Moreover, there is a gap in connecting basic science research and researchers to clinical research and physicians. The Clinical and Translational Science Awards (CTSA) program is dedicated to advancing translational science by improving the sharing of resources and clinical expertise, but the CTSA Consortium has not yet adopted the data standards necessary to capitalize on the true semantic connections between these research facets.

This project addresses the problem of information fragmentation by creating an Integrated Semantic Framework (ISF) (draft files located in google code) that facilitates the production and consumption of publically available Linked Open Data (LOD; see http://linkeddata.org/) about investigators, physicians, biomedical research resources, services, and clinical activities. LOD refers to data that has been given a specific Uniform Resource Identifier (URI), for the purpose of sharing and linking data and information on the Semantic Web. While a large amount of data is published as LOD, there remains a significant gap in the representation of research resources and clinical expertise. Reseachers can be characterized by the organization to which they belong, the grants and research in which they have participated, the research topics and research resources (reagents, biospecimens, animal models) they have generated, as well as the publications they have (co)-authored. Clinician profiles on the other hand, can be defined by their credentials, clinical research topics, and the kinds of procedures and specialization that can be inferred from clinical encounter data. We believe that integrating and relating this diversity of information sources and platforms requires addressing the overlap between research resources and the attributes and activities of researchers and clinicians. To this end, CTSAConnect will provide linkage between semantic representations of a wide range of clinical and research data using controlled vocabularies mapped to the Unified Medical Language System (UMLS) as a bridge between the two subject areas. The data sources include data from Medicaid, hospital billing systems, CTSAShareCenter, and other CTSA resource data, eagle-i and VIVO.

CTSAconnect aims to promote integration and discovery of research activities, resources, and clinical expertise. To this end, we will publish our ontologies and LOD via our website, which will also illustrate repeatable methods and examples of how to extract, consume, and utilize this valuable new LOD using freely available tools like VIVO, eagle-i, and Google APIs.

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CTSAconnect: A Linked Open Data approach to represent clinical and research expertise, activities, and resources