TY - GEN
T1 - Applying Linked Data principles to represent patient's electronic health records at Mayo Clinic
T2 - 2nd ACM SIGHIT International Health Informatics Symposium, IHI'12
AU - Pathak, Jyotishman
AU - Kiefer, Richard C.
AU - Chute, Christopher G.
PY - 2012
Y1 - 2012
N2 - The Linked Open Data (LOD) community project at the World Wide Web Consortium (W3C) is publishing various open data sets as Resource Description Framework (RDF) on the Web and extending it by setting RDF links between data items from different data sources containing information about genes, proteins, pathways, diseases, and drugs. While this presents a very powerful platform for federated querying and heterogeneous data integration, its true potential can only be realized when combining such information with "real" patient data from electronic health records. In this paper, we report our early experiences in applying Linked Data principles and technologies for representing patient data from electronic health records (EHRs) at Mayo Clinic in RDF. In particular, we demonstrate a proof-of-concept case study leveraging publicly available data from the Linked Open Drug Data cloud to federated querying for type 2 diabetes patients. Our study highlights several challenges and opportunities in using Semantic Web tools and technologies within a healthcare setting for enabling clinical and translational research.
AB - The Linked Open Data (LOD) community project at the World Wide Web Consortium (W3C) is publishing various open data sets as Resource Description Framework (RDF) on the Web and extending it by setting RDF links between data items from different data sources containing information about genes, proteins, pathways, diseases, and drugs. While this presents a very powerful platform for federated querying and heterogeneous data integration, its true potential can only be realized when combining such information with "real" patient data from electronic health records. In this paper, we report our early experiences in applying Linked Data principles and technologies for representing patient data from electronic health records (EHRs) at Mayo Clinic in RDF. In particular, we demonstrate a proof-of-concept case study leveraging publicly available data from the Linked Open Drug Data cloud to federated querying for type 2 diabetes patients. Our study highlights several challenges and opportunities in using Semantic Web tools and technologies within a healthcare setting for enabling clinical and translational research.
KW - Electronic Health Record (EHR)
KW - Linked data
KW - Semantic web
KW - Translational research
UR - http://www.scopus.com/inward/record.url?scp=84857711929&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84857711929&partnerID=8YFLogxK
U2 - 10.1145/2110363.2110415
DO - 10.1145/2110363.2110415
M3 - Conference contribution
AN - SCOPUS:84857711929
SN - 9781450307819
T3 - IHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
SP - 455
EP - 464
BT - IHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Y2 - 28 January 2012 through 30 January 2012
ER -