When and how to use bibliometrics as a screening tool for research performance
(2009) In Science and Public Policy 36(10). p.753-762- Abstract
Scientific performance is often evaluated by bibliometric indicators such as publication counts or citations. But this may neglect other relevant outputs from research units. An optimal evaluation would measure each dimension separately, but this would be costly. Luckily, cluster analyses show that units which specialise in other types of research activities (such as knowledge transfer or education of doctoral students), do not completely ignore publication-related activities. Publication-related outputs can also be disaggregated into quality (measured by citations) and quantity (measured by counts) dimensions. Thus, the performance of research groups can be screened using the Integral Citation (a new bibliometric indicator) which... (More)
Scientific performance is often evaluated by bibliometric indicators such as publication counts or citations. But this may neglect other relevant outputs from research units. An optimal evaluation would measure each dimension separately, but this would be costly. Luckily, cluster analyses show that units which specialise in other types of research activities (such as knowledge transfer or education of doctoral students), do not completely ignore publication-related activities. Publication-related outputs can also be disaggregated into quality (measured by citations) and quantity (measured by counts) dimensions. Thus, the performance of research groups can be screened using the Integral Citation (a new bibliometric indicator) which combines the quality and quantity dimensions. Units at the extremes need to be studied in more detail, to avoid measurement biases.
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- author
- Schmoch, Ulrich and Schubert, Torben LU
- publishing date
- 2009-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- bibliometrics, screening instrument, Research priorities
- in
- Science and Public Policy
- volume
- 36
- issue
- 10
- pages
- 10 pages
- publisher
- Oxford University Press
- external identifiers
-
- scopus:75849146274
- ISSN
- 0302-3427
- DOI
- 10.3152/030234209X481978
- language
- English
- LU publication?
- no
- id
- f042986d-b17d-4ff8-b200-82d4f8e15aaa
- date added to LUP
- 2016-05-18 13:34:51
- date last changed
- 2022-01-30 03:32:37
@article{f042986d-b17d-4ff8-b200-82d4f8e15aaa, abstract = {{<p>Scientific performance is often evaluated by bibliometric indicators such as publication counts or citations. But this may neglect other relevant outputs from research units. An optimal evaluation would measure each dimension separately, but this would be costly. Luckily, cluster analyses show that units which specialise in other types of research activities (such as knowledge transfer or education of doctoral students), do not completely ignore publication-related activities. Publication-related outputs can also be disaggregated into quality (measured by citations) and quantity (measured by counts) dimensions. Thus, the performance of research groups can be screened using the Integral Citation (a new bibliometric indicator) which combines the quality and quantity dimensions. Units at the extremes need to be studied in more detail, to avoid measurement biases.</p>}}, author = {{Schmoch, Ulrich and Schubert, Torben}}, issn = {{0302-3427}}, keywords = {{bibliometrics; screening instrument; Research priorities}}, language = {{eng}}, number = {{10}}, pages = {{753--762}}, publisher = {{Oxford University Press}}, series = {{Science and Public Policy}}, title = {{When and how to use bibliometrics as a screening tool for research performance}}, url = {{http://dx.doi.org/10.3152/030234209X481978}}, doi = {{10.3152/030234209X481978}}, volume = {{36}}, year = {{2009}}, }