Abstract

Investigators in the translational research and systems medicine domains require highly usable, efficient and integrative tools and methods that allow for the navigation of and reasoning over emerging large-scale data sets. Such resources must cover a spectrum of granularity from bio-molecules to population phenotypes. Given such information needs, we report upon the initial design and evaluation of an ontology-anchored integrative query tool, Research-IQ, which employs a combination of conceptual knowledge engineering and information retrieval techniques to enable the intuitive and rapid construction of queries, in terms of semi-structured textual propositions, that can subsequently be applied to integrative data sets. Our initial results, based upon both quantitative and qualitative evaluations of the efficacy and usability of Research-IQ, demonstrate its potential to increase clinical and translational research throughput.

Original languageEnglish
Pages (from-to)S56-S62
JournalJournal of Biomedical Informatics
Volume44
Issue numberSUPPL. 1
DOIs
StatePublished - Dec 2011

Keywords

  • Clinical and translational research
  • Information retrieval
  • Knowledge discovery
  • Semantic web

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