Funding: Federal Ministry of Education and Research (BMBF)
Grant Term: 3 years (2019-2022)
Project Manager: Prof. Dr. Michael Bosnjak
Project Coordinator: Prof. Dr. Armin Günther
Project Staff: Martin Kerwer
The digital transformation in science opens up new possibilities for the storage and use of information and creates knowledge discovery. At the same time, new digital opportunities are leading to an ever-increasing amount of research data. In order to make the best possible use of the potential of this data both within and outside scientific contexts, however, there are high demands on the quality of the data. In the past quality assurance measures in the handling and curation of research data - i.e., the preparation, management, and storage of research outputs - received little attention and have therefore become central challenges for current research practice.
The project "Development and Testing of Curation Criteria and Quality Standards of Research Data in the Course of the Digital Transformation in the German Science System" supports research groups and associations at universities and nonuniversity research institutions in tackling the challenges mentioned. Thus, the goal pursued is to target and systematically promote curation mechanisms in all disciplines.
The joint project aims to develop Domain Data Protocols (DDPs) for the handling of research data for various relevant empirical educational research methods and guidelines for calculating the costs of curating research data. The DDPs are intended as public and citable standard sample protocols to help researchers in the field of empirical educational research to produce quality-assured and reusable data.
For this purpose, the protocols are tailored to the specific conditions of the data collection methods that are relevant in empirical educational research (e.g., cross-sectional and longitudinal studies, performance indicators, different survey modes, qualitative studies). The respective research processes with their methodological, organizational, and technical features as well as the specific conditions of the collection, sharing, and subsequent reuse of data are considered. In addition, benchmarks for cost estimation for the curation of research data depending on the type and size of the study or the research project are determined on the basis of the DDPs developed.
ZPID brings to the joint project the perspective of psychology with its discipline-specific features in research data management as well as the associated challenges in quality assurance.