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Tracing Long-Term Outcomes of Basic Research Using Citation Networks
In recent years, the science of science policy has been facilitated by the greater availability of and access to digital data associated with the science, technology, and innovation enterprise. Historically, most of the studies from which such data are derived have been econometric or “scientometric...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8028394/ https://www.ncbi.nlm.nih.gov/pubmed/33870043 http://dx.doi.org/10.3389/frma.2020.00005 |
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author | Onken, James Miklos, Andrew C. Aragon, Richard |
author_facet | Onken, James Miklos, Andrew C. Aragon, Richard |
author_sort | Onken, James |
collection | PubMed |
description | In recent years, the science of science policy has been facilitated by the greater availability of and access to digital data associated with the science, technology, and innovation enterprise. Historically, most of the studies from which such data are derived have been econometric or “scientometric” in nature, focusing on the development of quantitative data, models, and metrics of the scientific process as well as outputs and outcomes. Broader definitions of research impact, however, necessitate the use of qualitative case-study methods. For many years, U.S. federal science agencies such as the National Institutes of Health have demonstrated the impact of the research they support through tracing studies that document critical events in the development of successful technologies. A significant disadvantage and barrier of such studies is the labor-intensive nature of a case study approach. Currently, however, the same data infrastructures that have been developed to support scientometrics may also facilitate historical tracing studies. In this paper, we describe one approach we used to discover long-term, downstream outcomes of research supported in the late 1970's and early 1980's by the National Institute of General Medical Sciences, a component of the National Institutes of Health. |
format | Online Article Text |
id | pubmed-8028394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80283942021-04-15 Tracing Long-Term Outcomes of Basic Research Using Citation Networks Onken, James Miklos, Andrew C. Aragon, Richard Front Res Metr Anal Research Metrics and Analytics In recent years, the science of science policy has been facilitated by the greater availability of and access to digital data associated with the science, technology, and innovation enterprise. Historically, most of the studies from which such data are derived have been econometric or “scientometric” in nature, focusing on the development of quantitative data, models, and metrics of the scientific process as well as outputs and outcomes. Broader definitions of research impact, however, necessitate the use of qualitative case-study methods. For many years, U.S. federal science agencies such as the National Institutes of Health have demonstrated the impact of the research they support through tracing studies that document critical events in the development of successful technologies. A significant disadvantage and barrier of such studies is the labor-intensive nature of a case study approach. Currently, however, the same data infrastructures that have been developed to support scientometrics may also facilitate historical tracing studies. In this paper, we describe one approach we used to discover long-term, downstream outcomes of research supported in the late 1970's and early 1980's by the National Institute of General Medical Sciences, a component of the National Institutes of Health. Frontiers Media S.A. 2020-09-08 /pmc/articles/PMC8028394/ /pubmed/33870043 http://dx.doi.org/10.3389/frma.2020.00005 Text en Copyright © 2020 Onken, Miklos and Aragon. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Research Metrics and Analytics Onken, James Miklos, Andrew C. Aragon, Richard Tracing Long-Term Outcomes of Basic Research Using Citation Networks |
title | Tracing Long-Term Outcomes of Basic Research Using Citation Networks |
title_full | Tracing Long-Term Outcomes of Basic Research Using Citation Networks |
title_fullStr | Tracing Long-Term Outcomes of Basic Research Using Citation Networks |
title_full_unstemmed | Tracing Long-Term Outcomes of Basic Research Using Citation Networks |
title_short | Tracing Long-Term Outcomes of Basic Research Using Citation Networks |
title_sort | tracing long-term outcomes of basic research using citation networks |
topic | Research Metrics and Analytics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8028394/ https://www.ncbi.nlm.nih.gov/pubmed/33870043 http://dx.doi.org/10.3389/frma.2020.00005 |
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