Activities and Challenges in developing Discipline-Specific Data Management Plan Templates

Activities and Challenges in developing Discipline-Specific Data Management Plan Templates From Vertical to Horizontal Integration of RDM Practices

To provide tailored guidance on research data management, discipline-specific data management plan (DMP) templates are core. Different stakeholders are pursuing the development of such discipline-specific DMP templates in different ways. In this paper, we present three such approaches. First, we int...

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Enregistré dans:
Détails bibliographiques
Publié dans:Bausteine Forschungsdatenmanagement
Auteurs principaux: Netscher, Sebastian, Anders, Ivonne, Henzen, Christin
Format: Artikel (Zeitschrift)
Langue:allemand
Publié: Philipps-Universität Marburg 2022
Sujets:
Anleitungen
Data Management Plan
Template
Guidance
fachspezifisch
disciplin-specific
DMP
Accès en ligne:Accès en ligne
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Description
Résumé:To provide tailored guidance on research data management, discipline-specific data management plan (DMP) templates are core. Different stakeholders are pursuing the development of such discipline-specific DMP templates in different ways. In this paper, we present three such approaches. First, we introduce the concept of domain data protocols, describing the work of the project Domain Data Protocols for Empirical Educational Research (in Germany). Members of this project develop tailored guidance on research data management (RDM) vertically, i.e., within the educational research discipline. Second, we present the approach of the Research Data Alliance Working Group on Discipline-specific Guidance for DMPs. The working group identifies discipline-specific DMP characteristics and uses them to analyse common practices and differences in RDM horizontally across disciplines. Finally, we describe the approach of the Research Data Management Organiser Sub-Working Group on Guidance, which facilitates mapping of discipline-specific DMP templates across disciplines. Although these three approaches differ in their underlying concepts, combining them facilitates identifying differences and commonalities in RDM across disciplines. By assigning discipline-specific characteristics and mapping these characteristics across disciplines, the three approaches improve our understanding of data management and research data within a particular discipline, as well as across disciplines.
DOI:10.17192/bfdm.2022.1.8371

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