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Ontology Mapping and Data Discovery for the Translational Investigator
Conference Proceeding
Reference:
R. Wynden, M. G. Weiner, I. Sim, D. Gabriel, M. Casale, S. Carini, S. Hastings, D. Ervin, S. W. Tu, J. Gennari, N. Anderson, K. Mobed, P. Lakshminarayanan, M. Massary, R. Cucina. AMIA CRI Summit, San Francisco, CA, 66-70. Published in 2010.
Abstract:

An integrated data repository (IDR) containing aggregations of clinical, biomedical, economic, administrative, and public health data is a key component of an overall translational research infrastructure. But most available data repositories are designed using standard data warehouse architecture using arbitrary data encoding standards, making queries across disparate repositories difficult. In response to these shortcomings we have designed a Health Ontology Mapper that translates terminologies into formal data encoding standards without altering the underlying source data. The Health Ontology Mapper system can dramatically lower the barrier to developing and using an IDR at biomedical research institutions to support biomedical and translational research, and will furthermore promote inter-institutional data sharing and research collaboration.

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Information last updated: Tue Oct 11 2011
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Stanford School of Medicine