Pursuing transparency: How research performing organizations in Germany collect data on publication costs
Dorothea Strecker, Heinz Pampel, Jonas H\"ofting

TL;DR
This study surveys German research organizations on how they collect publication cost data, revealing partial recording practices, varied data reliability, and limited strategic use despite recognizing its importance for open access policies.
Contribution
First comprehensive survey on publication cost data collection practices at German research organizations, highlighting challenges and implications for open access transformation.
Findings
Most RPOs record publication costs at least partially
Data collection procedures are often non-binding
Data is used for strategic decisions in 59% of RPOs
Abstract
This article presents the results of a survey conducted in 2024 among research performing organizations (RPOs) in Germany on how they collect data on publication costs. Of the 583 invitees, 258 (44.3%) completed the questionnaire. This survey is the first comprehensive study on the recording of publication costs at RPOs in Germany. The results show that the majority of surveyed RPOs recorded publication costs at least in part. However, procedures in this regard were often non-binding. Respondents' ratings of the reliability of the collection of data on publication costs varied by the source of publication funding. Eighty percent of respondents rated the contribution of collecting data on publication costs to shaping the open access transformation as "very important" or "important." Yet, these data were used as a basis for strategic decisions in only 59% of the surveyed RPOs. Moreover,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
Topicsscientometrics and bibliometrics research · Research Data Management Practices · Data Analysis and Archiving
