Research Data Management
The management of research data includes the entire research cycle from the planning, data collection to long-term archiving. Generating and handling research data should be organised and monitored as efficiently and systematically as possible. Creating a data management plan serves to use the data effectively, make them reusable, publish them and archive them. Systematic research data management also helps to fulfil the guidelines of good research practice, to make Open Data available and to fulfil the requirements of specialist journals and funding institutions. There are also many practical advantages for your own day-to-day research, both if you are researching as an individual or as part of a working group. If you deal methodically with issues such as “how can records be stored so that they are still traceable and understandable in one, two, three or more years?”, this can in practice save you a lot of time and effort later. All researchers should therefore explore the topic of research data management. Ultimately, good data management helps you to enable group working on data within a research project right from the beginning, as well as to structure your work well and prevent data loss.
The Research Data Scarytales of the research data management competence network at the Thuringian higher education institutions show what can go wrong if research data management is not carried out systematically.
Further recommended information sources on research data management are:
- Information about the professional handling of research data at the University of Leicester.
- Frequently asked Questions about research data management at forschungsdaten.info.
- The Data Management Toolkit of the University of New Hampshire
- The guide “Data description in practice” of Utrecht University describes how to describe and document your own research data with Excel.
Tip: Practical Guide 6 “Planning data management” from the practical guide series of the Open Science magazine.