Zitationsvorschlag

Fritze, Florian et al.: Efficient Data Curation by Automating Workflows, in Heuveline, Vincent et al. (Hrsg.): E-Science-Tage 2025: Research Data Management: Challenges in a Changing World, Heidelberg: heiBOOKS, 2025, S. 235–248. https://doi.org/10.11588/heibooks.1652.c23927

Lizenz (Kapitel)

Creative Commons License

Dieses Werk steht unter der Lizenz Creative Commons Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International.

Identifier (Buch)

https://doi.org/10.11588/heibooks.1652
ISBN 978-3-911056-51-9 (PDF)
ISBN 978-3-911056-52-6 (Softcover)

Veröffentlicht

05.11.2025

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Statistik

Autor/innen

Florian Fritze , Dorothea Iglezakis , Sarbani Roy , Björn Selent , Karoline Weinspach

Efficient Data Curation by Automating Workflows

Abstract: Data curation results in high-quality data description, but takes time and effort. To still enable an intensive data curation process at the institutional data repository DaRUS, different approaches support and automate the process: to support correct and standardized input as early as the metadata entry stage, the researchers are assisted by interfaces to registries like ORCID for authors, ROR for institutions, to terminology services for a topic classification and to the institutional research information system for research projects. Automatic checks for keywords, URLs and funding information are embedded in a REST API named pubWorkflow to help the curation team and manage the publication workflow. An integration with easyReview is planned to also support a scientific quality check. All integrations and tools build on the workflow engine and the controlled vocabulary support of Dataverse, the underlying repository platform. 

Keywords: Data Curation, Metadata, Data Repository, Automation