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International Open Data Repository Survey: Description of collection, collected data, and analysis methods

von der Heyde, Markus

This article summarizes the process of data collection and data preprocessing for the International Repository Survey we conducted, and provides a simple descriptive analysis of the data collected.
In the context of the Open Data Repository Landscape Analysis in Switzerland (von der Heyde, 2019b), this international survey was primarily designed to gather information about the repositories which are used by Swiss scientists. Most scientists indicated in the landscape survey, and also their recent data management plans, their intentions to use international repositories. Therefore, the broad spectrum of internationally known repositories was addressed in this survey. Overall, 1,953 contacts from international data repositories were invited to participate.
This paper documents the study design and the process of data preprocessing. It thus describes methods that are largely independent of the results and interpretations of the data. This contribution forms the basis for reusing the dataset in other scientific projects.
Overall, 249 representatives of international repositories participated in the survey (12.7% of all 1,953 invited). The preprocessing included anonymization, a plausibility check, and dataset selection. Overall, 53 records were corrected for plausibility. After these plausibility measures, the data selection was applied. In total, 39 data records without any useful data were excluded, and twice records contained identical data where participants restarted the survey due to technical reasons communicated via email (total excluded = 41 records). In consequence, a total of 208 data records were available for analysis after the quality assurance measures had been applied.
Overall, these 208 dataset represent about 10% of the current international landscape of open data repositories.

The study was jointly commissioned in 2018 by the SNSF and swissuniversities.



Swiss National Science Foundation (SNSF)

Open Research Data Group




Program "Scientific Information"

Gabi Schneider


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