Exploring and Improving Workflows for the Donation and Curation of Research Data
Keywords:Research Data Management, Research Data Center, Workflows, Efficiency, Interoperability, Controlled Vocabularies
Managing research data and preparing it for long term archiving at a research data center is a time-consuming, repetitive and error prone process without obvious rewards or incentives. To address these challenges, we aim at the integration of a standard data management tool into one of the research data centers of the German Network of Educational Research Data. The goal is to improve workflows for both, data donors and curators and to explore transferable solutions that allow researchers and curators to work on the same platform when entering and editing metadata.
C. L. Borgman and I. V. Pasquetto, Why data sharing and reuse are hard to do, 2017.
[Online]. Available: https://escholarship.org/uc/item/0jj17309.
N. Kiesler and D. Schiffner, “On the lack of recognition of software artifacts and it infrastruc-
ture in educational technology research,” in 20. Fachtagung Bildungstechnologien (DELFI),
P. A. Henning, M. Striewe, and M. W ̈olfel, Eds., Bonn: Gesellschaft f ̈ur Informatik e.V.,
, pp. 201–206. [Online]. Available: https://doi.org/10.18420/delfi2022-034.
M. D. Wilkinson, M. Dumontier, I. J. Aalbersberg, et al., “The fair guiding principles for
scientific data management and stewardship,” Scientific data, vol. 3, no. 1, pp. 1–9, 2016.
J. Klar, Research data management organiser, 2023. [Online]. Available: https : / /
T. Miksa, Rda-dmp-common-standard, 2020. [Online]. Available: https://github.com/
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