Published September 29, 2023 | Version v1
Presentation Open

Data stewardship in CRC 1280 "Extinction Learning": From policy to dedicated workflows in an institutional data management system

  • 1. CRC 1280 "Extinction Learning", Biopsychology, Ruhr University Bochum, Germany
  • 2. IT.SERVICES, Ruhr University Bochum, Germany
  • 3. Cognitive Psychology, Ruhr University Bochum, Germany

Description

Slides of the presentation "Data stewardship in CRC 1280 Extinction Learning: From policy to dedicated workflows in an institutional data management system", given at the workshop "Data Stewardship goes Germany" in Dresden, Germany, on September 25, 2023.

 

Abstract:

Data stewards of Collaborative Research Centers (CRCs) funded by the German Research Foundation (DFG) support the establishment and operation of sustainable infrastructures for the management of research data and metadata in their CRC (Schwandt 2019). There exist clear technical challenges such as the resource-saving adaptation of existing infrastructure systems to discipline-specific requirements instead of the new development of systems from scratch. However, also organizational factors such as lack of access to researchers' needs, unclear roles and governance, and lack of acceptance in the CRC were identified as major problems for the success of information management (INF) projects in which data stewards are often embedded (Brand & Dierkes 2020; Engelhardt & Kusch 2021). To address these critical issues, many useful steps can be taken to engage researchers and thereby increase their commitment to research data management (RDM) as well as the usability of (further) developed and implemented infrastructure systems. Based on the experiences of the CRC 1280 “Extinction Learning” successful measures and processes were presented that can ideally be extended to other CRCs or even the broader research institution.

Notes

This work was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), SFB 1280 Extinction Learning (316803389—Project INF).

Files

MarlenePacharra_et_al_DataStewardshipInCRC1280ExtinctionLearning_DSgG2023.pdf