Grid-Enabled Measures
Open accessAbstract
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).
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The Grid-Enabled Measures Project and the SIRC Instrument Review Project are organized around the Proctor 2011 taxonomy.
“The Grid-Enabled Measures Project [10] and The Society for Implementation Research Collaborative (SIRC) Instrument Review Project [11] are organized around the Proctor 2011 taxonomy.”
From Ten years of implementation outcomes research: a scoping review (2023) · cites this paper as [10]
The Principles Guiding Development section describes GEM’s interface as organized into constructs, measures, and data sets; the Abstract describes its Science 2.0 basis. Neither passage establishes whether GEM is organized around the Proctor 2011 taxonomy, and searches for Proctor and implementation-outcome terms found no such statement. This source does not address the separately cited SIRC project. (LLM, conf=0.75)
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Additional file 1 of Ten years of implementation outcomes research: a scoping review
Proctor, E. K., Bunger, A. C., Lengnick‐Hall, R., Gerke, D. R., Martin, J. K., Phillips, R. J., & Swanson, J. C. (2024) · Figshare · doi:10.6084/m9.figshare.26606383
- Authors
- Moser, R. P., Hesse, B. W., Shaikh, A. R., Courtney, P., Morgan, G., Augustson, E., Kobrin, S., Levin, K. Y., Helba, C., Garner, D., Dunn, M., & Coa, K.
- Affiliations
- National Institutes of Health (US)
- National Cancer Institute (US)
- Westat (United States) (US)
- Corresponding author
- Moser, Richard P.
- Venue
- American Journal of Preventive Medicine
- Publisher
- Elsevier BV
- Published
- 2011-05
- Volume
- 40
- Issue
- 5
- Pages
- S134-S143
- ISSN
- 0749-3797 (ISSN-L)
- PMC
- PMC3088871
- OpenAlex
- W1578674874
- Semantic Scholar
- d084998b3f9cbabaf3b1124868572d1d078097e3
- Cited by
- 44
- References
- 44
- Citations by year
- 2025: 3 · 2024: 2 · 2023: 1 · 2022: 3 · 2021: 2 · 2019: 3 · 2017: 3 · 2016: 4 · 2015: 3 · 2014: 5 · 2013: 4 · 2012: 5
- FWCI
- 18.41
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- American Journal of Preventive Medicine (publishedVersion, other-oa)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (Z99 CA999999)
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Keywords
- standardized outcome measures, cancer research, data harmonization, data sharing, ontology (information science), common data elements, Science 2.0, Web 2.0, virtual research communities
- MeSH terms
- Cooperative Behavior, Humans, Medical Informatics, Research, United States, Databases, Factual, Vocabulary, Controlled, Internet, National Cancer Institute (U.S.)
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