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Presentation . 2022
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Presentation . 2022
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Forschung unterstützen: Empfehlungen für Data Stewardship an akademischen Forschungsinstitutionen - Ergebnisse des Projektes DataStew

Authors: Eva Seidlmayer; Jens Dierkes;

Forschung unterstützen: Empfehlungen für Data Stewardship an akademischen Forschungsinstitutionen - Ergebnisse des Projektes DataStew

Abstract

### English description below ### Präsentation der DataStew-Projektergebnisse im Rahmen des "Tags der Forschungsdaten 2022" von fdm.nrw. Aufgrund der gesteigerten Bedarfe an Forschungsdatenkompetenz durch den digitalen Wandel der Forschung und neu entstehende Dateninfrastrukturen wie die Nationale Forschungsdaten Infrastruktur (NFDI) oder die European Open Science Cloud (EOSC) ist eine breite Verständigung über die Anforderungen an das Forschungsdatenmanagement (u. a. Standards, Infrastruktur) sowie an Personen, die Aufgaben in diesem Kontext übernehmen (Aufgaben, Ausbildung), notwendig. Das vor allem in der englischsprachigen Forschung verwendete Konzept Data Stewardship greift die Aufgaben im Forschungsdatenmanagement gebündelt auf. Die genauen Rollen von Data Stewards sind im deutschen Kontext jedoch bisher nicht eindeutig geklärt. Um das aktuelle Verständnis zu untersuchen und Handlungsempfehlungen für die Aus- und Weiterbildung von Data Stewards zu ermitteln, wurden im Rahmen des Projektes DataStew durch verschiedene Methoden Expert*innenwissen zusammengeführt. Neben der Literaturauswertung und Analyse von Stellenanzeigen wurden Expert*innen der Stakeholdergruppen Infrastruktur, Hochschulausbildung, Wissenschaft, Politikberatung sowie aktive Data Stewards in Interviews und Fokusgruppendiskusionen befragt. In diesem Vortrag werden Ergebnisse aus dem zehnmonatigen Projekt präsentiert. DataStew wird gemeinsam von ZB MED Informationszentrum Lebenswissenschaften und der Universitäts- und Stadtbibliothek (USB) Köln durchgeführt. Das Projekt wird gefördert durch das BMBF. ##### Presentation of the DataStew project results as part of the "Research Data Day 2022" by fdm.nrw. Due to the increased need for research data expertise as a result of the digital transformation of research and emerging data infrastructures such as the National Research Data Infrastructure (NFDI) or the European Open Science Cloud (EOSC), there is a need for a broad understanding of the requirements for research data management (including standards, infrastructure) as well as for people who take on tasks in this context (tasks, training). The concept of data stewardship, which is used primarily in English-language research, takes up the tasks in research data management in a bundled way. However, the exact roles of data stewards have not yet been clearly clarified in the German context. In order to investigate the current understanding and to develop recommendations for the education and training of data stewards, the DataStew project used a variety of methods to gather expert knowledge. In addition to the literature review and analysis of job advertisements, experts from the stakeholder groups infrastructure, higher education, science, policy consulting as well as active data stewards were surveyed in interviews and focus group discussions. This talk will present findings from the ten-month project. DataStew is jointly conducted by ZB MED Information Centre for Life Sciences and the University and City Library Cologne (USB). The project is funded by the BMBF.

Keywords

Data Steward, Research Data Management, Data Stewardship, Task Profiles

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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