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Measuring the impact of health research data in terms of data citations by scientific publications
Health is a representative domain data-driven research since health research data are growingly generated at a massive scale. There is an intuitive logic that the degree to which disease burden and the number of data resources align. In order to figure out disease-specific data sharing and reuse lev...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9661461/ https://www.ncbi.nlm.nih.gov/pubmed/36406005 http://dx.doi.org/10.1007/s11192-022-04559-4 |
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author | Bai, Yongmei Du, Jian |
author_facet | Bai, Yongmei Du, Jian |
author_sort | Bai, Yongmei |
collection | PubMed |
description | Health is a representative domain data-driven research since health research data are growingly generated at a massive scale. There is an intuitive logic that the degree to which disease burden and the number of data resources align. In order to figure out disease-specific data sharing and reuse level, we took the number of data records and their citations in the scientific literature in the Data Citation Index platform as approximate indicators. The results indicated that only a small percentage (7.5%) of health data records had received documented citations by scientific publications. We find the level of data sharing and reuse varies across diseases. Our study suggested that the more socioeconomic burden and the more research funding, the more likely scientific data for diseases will be produced and made available. But such a correlation could not be observed for the activity of data reuse. Secondary reuse of scientific data is a complex behavior. |
format | Online Article Text |
id | pubmed-9661461 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-96614612022-11-14 Measuring the impact of health research data in terms of data citations by scientific publications Bai, Yongmei Du, Jian Scientometrics Article Health is a representative domain data-driven research since health research data are growingly generated at a massive scale. There is an intuitive logic that the degree to which disease burden and the number of data resources align. In order to figure out disease-specific data sharing and reuse level, we took the number of data records and their citations in the scientific literature in the Data Citation Index platform as approximate indicators. The results indicated that only a small percentage (7.5%) of health data records had received documented citations by scientific publications. We find the level of data sharing and reuse varies across diseases. Our study suggested that the more socioeconomic burden and the more research funding, the more likely scientific data for diseases will be produced and made available. But such a correlation could not be observed for the activity of data reuse. Secondary reuse of scientific data is a complex behavior. Springer International Publishing 2022-11-14 2022 /pmc/articles/PMC9661461/ /pubmed/36406005 http://dx.doi.org/10.1007/s11192-022-04559-4 Text en © Akadémiai Kiadó, Budapest, Hungary 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Bai, Yongmei Du, Jian Measuring the impact of health research data in terms of data citations by scientific publications |
title | Measuring the impact of health research data in terms of data citations by scientific publications |
title_full | Measuring the impact of health research data in terms of data citations by scientific publications |
title_fullStr | Measuring the impact of health research data in terms of data citations by scientific publications |
title_full_unstemmed | Measuring the impact of health research data in terms of data citations by scientific publications |
title_short | Measuring the impact of health research data in terms of data citations by scientific publications |
title_sort | measuring the impact of health research data in terms of data citations by scientific publications |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9661461/ https://www.ncbi.nlm.nih.gov/pubmed/36406005 http://dx.doi.org/10.1007/s11192-022-04559-4 |
work_keys_str_mv | AT baiyongmei measuringtheimpactofhealthresearchdataintermsofdatacitationsbyscientificpublications AT dujian measuringtheimpactofhealthresearchdataintermsofdatacitationsbyscientificpublications |