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Feasibility of common bibliometrics in evaluating translational science
INTRODUCTION: A pilot study by 6 Clinical and Translational Science Awards (CTSAs) explored how bibliometrics can be used to assess research influence. METHODS: Evaluators from 6 institutions shared data on publications (4202 total) they supported, and conducted a combined analysis with state-of-the...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408837/ https://www.ncbi.nlm.nih.gov/pubmed/28480055 http://dx.doi.org/10.1017/cts.2016.8 |
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author | Schneider, M. Kane, C. M. Rainwater, J. Guerrero, L. Tong, G. Desai, S. R. Trochim, W. |
author_facet | Schneider, M. Kane, C. M. Rainwater, J. Guerrero, L. Tong, G. Desai, S. R. Trochim, W. |
author_sort | Schneider, M. |
collection | PubMed |
description | INTRODUCTION: A pilot study by 6 Clinical and Translational Science Awards (CTSAs) explored how bibliometrics can be used to assess research influence. METHODS: Evaluators from 6 institutions shared data on publications (4202 total) they supported, and conducted a combined analysis with state-of-the-art tools. This paper presents selected results based on the tools from 2 widely used vendors for bibliometrics: Thomson Reuters and Elsevier. RESULTS: Both vendors located a high percentage of publications within their proprietary databases (>90%) and provided similar but not equivalent bibliometrics for estimating productivity (number of publications) and influence (citation rates, percentage of papers in the top 10% of citations, observed citations relative to expected citations). A recently available bibliometric from the National Institutes of Health Office of Portfolio Analysis, examined after the initial analysis, showed tremendous potential for use in the CTSA context. CONCLUSION: Despite challenges in making cross-CTSA comparisons, bibliometrics can enhance our understanding of the value of CTSA-supported clinical and translational research. |
format | Online Article Text |
id | pubmed-5408837 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54088372017-05-04 Feasibility of common bibliometrics in evaluating translational science Schneider, M. Kane, C. M. Rainwater, J. Guerrero, L. Tong, G. Desai, S. R. Trochim, W. J Clin Transl Sci Research Methods and Technology INTRODUCTION: A pilot study by 6 Clinical and Translational Science Awards (CTSAs) explored how bibliometrics can be used to assess research influence. METHODS: Evaluators from 6 institutions shared data on publications (4202 total) they supported, and conducted a combined analysis with state-of-the-art tools. This paper presents selected results based on the tools from 2 widely used vendors for bibliometrics: Thomson Reuters and Elsevier. RESULTS: Both vendors located a high percentage of publications within their proprietary databases (>90%) and provided similar but not equivalent bibliometrics for estimating productivity (number of publications) and influence (citation rates, percentage of papers in the top 10% of citations, observed citations relative to expected citations). A recently available bibliometric from the National Institutes of Health Office of Portfolio Analysis, examined after the initial analysis, showed tremendous potential for use in the CTSA context. CONCLUSION: Despite challenges in making cross-CTSA comparisons, bibliometrics can enhance our understanding of the value of CTSA-supported clinical and translational research. Cambridge University Press 2017-01-31 /pmc/articles/PMC5408837/ /pubmed/28480055 http://dx.doi.org/10.1017/cts.2016.8 Text en © The Association for Clinical and Translational Science 2017 http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Pressmust be obtained for commercial re-use or in order to create a derivative work. |
spellingShingle | Research Methods and Technology Schneider, M. Kane, C. M. Rainwater, J. Guerrero, L. Tong, G. Desai, S. R. Trochim, W. Feasibility of common bibliometrics in evaluating translational science |
title | Feasibility of common bibliometrics in evaluating translational science |
title_full | Feasibility of common bibliometrics in evaluating translational science |
title_fullStr | Feasibility of common bibliometrics in evaluating translational science |
title_full_unstemmed | Feasibility of common bibliometrics in evaluating translational science |
title_short | Feasibility of common bibliometrics in evaluating translational science |
title_sort | feasibility of common bibliometrics in evaluating translational science |
topic | Research Methods and Technology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408837/ https://www.ncbi.nlm.nih.gov/pubmed/28480055 http://dx.doi.org/10.1017/cts.2016.8 |
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