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Data Quality Assurance at Research Data Repositories Cover

Data Quality Assurance at Research Data Repositories

Open Access
|Nov 2022

Abstract

This paper presents findings from a survey on the status quo of data quality assurance practices at research data repositories.

The personalised online survey was conducted among repositories indexed in re3data in 2021. It covered the scope of the repository, types of data quality assessment, quality criteria, responsibilities, details of the review process, and data quality information and yielded 332 complete responses.

The results demonstrate that most repositories perform data quality assurance measures, and overall, research data repositories significantly contribute to data quality. Quality assurance at research data repositories is multifaceted and nonlinear, and although there are some common patterns, individual approaches to ensuring data quality are diverse. The survey showed that data quality assurance sets high expectations for repositories and requires a lot of resources. Several challenges were discovered: for example, the adequate recognition of the contribution of data reviewers and repositories, the path dependence of data review on review processes for text publications, and the lack of data quality information. The study could not confirm that the certification status of a repository is a clear indicator of whether a repository conducts in-depth quality assurance.

Language: English
Submitted on: May 10, 2022
Accepted on: Oct 28, 2022
Published on: Nov 22, 2022
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2022 Maxi Kindling, Dorothea Strecker, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.