Data Quality Assurance at Research Data Repositories

Authors : Maxi Kindling, Dorothea Strecker

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.

URL : Data Quality Assurance at Research Data Repositories

DOI : http://doi.org/10.5334/dsj-2022-018

The Landscape of Research Data Repositories in 2015: A re3data Analysis

Authors : Maxi Kindling, Heinz Pampel, Stephanie van de Sandt, Jessika Rücknagel, Paul Vierkant, Gabriele Kloska, Michael Witt, Peter Schirmbacher, Roland Bertelmann, Frank Scholze

This article provides a comprehensive descriptive and statistical analysis of metadata information on 1,381 research data repositories worldwide and across all research disciplines.

The analyzed metadata is derived from the re3data database, enabling search and browse functionalities for the global registry of research data repositories. The analysis focuses mainly on institutions that operate research data repositories, types and subjects of research data repositories (RDR), access conditions as well as services provided by the research data repositories.

RDR differ in terms of the service levels they offer, languages they support or standards they comply with. These statements are commonly acknowledged by saying the RDR landscape is heterogeneous.

As expected, we found a heterogeneous RDR landscape that is mostly influenced by the repositories’ disciplinary background for which they offer services.

URL : http://www.dlib.org/dlib/march17/kindling/03kindling.html