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Measuring the evolution and output of cross-disciplinary collaborations within the NCI Physical Sciences–Oncology Centers Network
Development of effective quantitative indicators and methodologies to assess the outcomes of cross-disciplinary collaborative initiatives has the potential to improve scientific program management and scientific output. This article highlights an example of a prospective evaluation that has been dev...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3814300/ https://www.ncbi.nlm.nih.gov/pubmed/24808632 http://dx.doi.org/10.1093/reseval/rvt025 |
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author | Basner, Jodi E. Theisz, Katrina I. Jensen, Unni S. Jones, C. David Ponomarev, Ilya Sulima, Pawel Jo, Karen Eljanne, Mariam Espey, Michael G. Franca-Koh, Jonathan Hanlon, Sean E. Kuhn, Nastaran Z. Nagahara, Larry A. Schnell, Joshua D. Moore, Nicole M. |
author_facet | Basner, Jodi E. Theisz, Katrina I. Jensen, Unni S. Jones, C. David Ponomarev, Ilya Sulima, Pawel Jo, Karen Eljanne, Mariam Espey, Michael G. Franca-Koh, Jonathan Hanlon, Sean E. Kuhn, Nastaran Z. Nagahara, Larry A. Schnell, Joshua D. Moore, Nicole M. |
author_sort | Basner, Jodi E. |
collection | PubMed |
description | Development of effective quantitative indicators and methodologies to assess the outcomes of cross-disciplinary collaborative initiatives has the potential to improve scientific program management and scientific output. This article highlights an example of a prospective evaluation that has been developed to monitor and improve progress of the National Cancer Institute Physical Sciences—Oncology Centers (PS-OC) program. Study data, including collaboration information, was captured through progress reports and compiled using the web-based analytic database: Interdisciplinary Team Reporting, Analysis, and Query Resource. Analysis of collaborations was further supported by data from the Thomson Reuters Web of Science database, MEDLINE database, and a web-based survey. Integration of novel and standard data sources was augmented by the development of automated methods to mine investigator pre-award publications, assign investigator disciplines, and distinguish cross-disciplinary publication content. The results highlight increases in cross-disciplinary authorship collaborations from pre- to post-award years among the primary investigators and confirm that a majority of cross-disciplinary collaborations have resulted in publications with cross-disciplinary content that rank in the top third of their field. With these evaluation data, PS-OC Program officials have provided ongoing feedback to participating investigators to improve center productivity and thereby facilitate a more successful initiative. Future analysis will continue to expand these methods and metrics to adapt to new advances in research evaluation and changes in the program. |
format | Online Article Text |
id | pubmed-3814300 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-38143002014-10-31 Measuring the evolution and output of cross-disciplinary collaborations within the NCI Physical Sciences–Oncology Centers Network Basner, Jodi E. Theisz, Katrina I. Jensen, Unni S. Jones, C. David Ponomarev, Ilya Sulima, Pawel Jo, Karen Eljanne, Mariam Espey, Michael G. Franca-Koh, Jonathan Hanlon, Sean E. Kuhn, Nastaran Z. Nagahara, Larry A. Schnell, Joshua D. Moore, Nicole M. Res Eval Special Section: Recent Developments in Data Sources and Analysis for R&D Evaluation, Papers Presented at the American Evaluation Association Conference in October 2012. Development of effective quantitative indicators and methodologies to assess the outcomes of cross-disciplinary collaborative initiatives has the potential to improve scientific program management and scientific output. This article highlights an example of a prospective evaluation that has been developed to monitor and improve progress of the National Cancer Institute Physical Sciences—Oncology Centers (PS-OC) program. Study data, including collaboration information, was captured through progress reports and compiled using the web-based analytic database: Interdisciplinary Team Reporting, Analysis, and Query Resource. Analysis of collaborations was further supported by data from the Thomson Reuters Web of Science database, MEDLINE database, and a web-based survey. Integration of novel and standard data sources was augmented by the development of automated methods to mine investigator pre-award publications, assign investigator disciplines, and distinguish cross-disciplinary publication content. The results highlight increases in cross-disciplinary authorship collaborations from pre- to post-award years among the primary investigators and confirm that a majority of cross-disciplinary collaborations have resulted in publications with cross-disciplinary content that rank in the top third of their field. With these evaluation data, PS-OC Program officials have provided ongoing feedback to participating investigators to improve center productivity and thereby facilitate a more successful initiative. Future analysis will continue to expand these methods and metrics to adapt to new advances in research evaluation and changes in the program. Oxford University Press 2013-12 2013-10-31 /pmc/articles/PMC3814300/ /pubmed/24808632 http://dx.doi.org/10.1093/reseval/rvt025 Text en © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com |
spellingShingle | Special Section: Recent Developments in Data Sources and Analysis for R&D Evaluation, Papers Presented at the American Evaluation Association Conference in October 2012. Basner, Jodi E. Theisz, Katrina I. Jensen, Unni S. Jones, C. David Ponomarev, Ilya Sulima, Pawel Jo, Karen Eljanne, Mariam Espey, Michael G. Franca-Koh, Jonathan Hanlon, Sean E. Kuhn, Nastaran Z. Nagahara, Larry A. Schnell, Joshua D. Moore, Nicole M. Measuring the evolution and output of cross-disciplinary collaborations within the NCI Physical Sciences–Oncology Centers Network |
title | Measuring the evolution and output of cross-disciplinary collaborations within the NCI Physical Sciences–Oncology Centers Network |
title_full | Measuring the evolution and output of cross-disciplinary collaborations within the NCI Physical Sciences–Oncology Centers Network |
title_fullStr | Measuring the evolution and output of cross-disciplinary collaborations within the NCI Physical Sciences–Oncology Centers Network |
title_full_unstemmed | Measuring the evolution and output of cross-disciplinary collaborations within the NCI Physical Sciences–Oncology Centers Network |
title_short | Measuring the evolution and output of cross-disciplinary collaborations within the NCI Physical Sciences–Oncology Centers Network |
title_sort | measuring the evolution and output of cross-disciplinary collaborations within the nci physical sciences–oncology centers network |
topic | Special Section: Recent Developments in Data Sources and Analysis for R&D Evaluation, Papers Presented at the American Evaluation Association Conference in October 2012. |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3814300/ https://www.ncbi.nlm.nih.gov/pubmed/24808632 http://dx.doi.org/10.1093/reseval/rvt025 |
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