Author
Listed:
- Thomas Scheidsteger
(IVS-CPT, Max Planck Institute for Solid State Research)
- Robin Haunschild
(IVS-CPT, Max Planck Institute for Solid State Research)
- Lutz Bornmann
(IVS-CPT, Max Planck Institute for Solid State Research
Administrative Headquarters of the Max Planck Society)
Abstract
OpenAlex is a freely available bibliographic database that can be used for bibliometric studies. In this study, we compared certain field-normalized citation scores (NCS) from OpenAlex with those from three commercial databases (Web of Science, Scopus, and Dimensions). We were interested in the question whether the NCS from OpenAlex are comparable to those from the commercial databases and can be alternatively used in evaluative bibliometrics. The NCS have been calculated for nearly 335,000 papers published by 48 German universities in four main subject areas between 2013 and 2017. We found varying but overall strong agreement between the scores according to Lin’s concordance correlation coefficient. Separating the publication set along the single universities and moreover along the four main subject areas involved revealed significant differences at the level of single papers but also gave indications on how to possibly mitigate outlier cases. We calculated mean normalized citation scores for the 48 universities and found that the agreements across different databases are low. On the one hand, the results suggest that comparisons of universities using NCS across different databases should be avoided. On the other hand, the difference of the concordance correlation coefficients at paper and university level is a good example for the problem of ecological fallacy in bibliometrics: The mean impact is not representative for the single papers’ impact in the set.
Suggested Citation
Thomas Scheidsteger & Robin Haunschild & Lutz Bornmann, 2025.
"How similar are field-normalized citation impact scores obtained from OpenAlex and three popular commercial databases? An empirical comparison based on large German universities,"
Scientometrics, Springer;Akadémiai Kiadó, vol. 130(7), pages 3537-3569, July.
Handle:
RePEc:spr:scient:v:130:y:2025:i:7:d:10.1007_s11192-025-05338-7
DOI: 10.1007/s11192-025-05338-7
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:130:y:2025:i:7:d:10.1007_s11192-025-05338-7. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.