Literature DB >> 21521586

Grid-enabled measures: using Science 2.0 to standardize measures and share data.

Richard P Moser1, Bradford W Hesse, Abdul R Shaikh, Paul Courtney, Glen Morgan, Erik Augustson, Sarah Kobrin, Kerry Y Levin, Cynthia Helba, David Garner, Marsha Dunn, Kisha Coa.   

Abstract

Scientists are taking advantage of the Internet and collaborative web technology to accelerate discovery in a massively connected, participative environment--a phenomenon referred to by some as Science 2.0. As a new way of doing science, this phenomenon has the potential to push science forward in a more efficient manner than was previously possible. The Grid-Enabled Measures (GEM) database has been conceptualized as an instantiation of Science 2.0 principles by the National Cancer Institute (NCI) with two overarching goals: (1) promote the use of standardized measures, which are tied to theoretically based constructs; and (2) facilitate the ability to share harmonized data resulting from the use of standardized measures. The first is accomplished by creating an online venue where a virtual community of researchers can collaborate together and come to consensus on measures by rating, commenting on, and viewing meta-data about the measures and associated constructs. The second is accomplished by connecting the constructs and measures to an ontological framework with data standards and common data elements such as the NCI Enterprise Vocabulary System (EVS) and the cancer Data Standards Repository (caDSR). This paper will describe the web 2.0 principles on which the GEM database is based, describe its functionality, and discuss some of the important issues involved with creating the GEM database such as the role of mutually agreed-on ontologies (i.e., knowledge categories and the relationships among these categories--for data sharing). Published by Elsevier Inc.

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Year:  2011        PMID: 21521586      PMCID: PMC3088871          DOI: 10.1016/j.amepre.2011.01.004

Source DB:  PubMed          Journal:  Am J Prev Med        ISSN: 0749-3797            Impact factor:   5.043


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