Research data management

Research data are (digital) data that are generated during a scientific activity (e.g. through measurements, surveys or sourcework) and/or on the basis of which one can conduct academic research (e.g. digitised documents). Depending on the discipline, different types of research data are generated and used: Interview transcripts, climate models, gene sequences, digitised manuscripts et cetera. This imposes different requirements on the preparation, processing and management of the data.

Research data management refers to all activities and decisions during the lifecycle of research data, ranging from the planning phase to the re-use of the data. Research data management is an indispensable part of the research process. Good data management facilitates the research process, increases the visibility and re-usability of research data, and thus contributes to the integrity and transparency of research. With good data management, the costs for the required infrastructure can be budgeted and legal issues clarified already during the project planning phase. In the long run, research data management can save time and resources and increase the efficiency of research, because it avoids unnecessary duplication of data and additional work.

The organisation, reusability and storage of research data is becoming increasingly important in the planning of research projects in all scientific disciplines. Not the least because research funders such as the SNSF promote and demand good research data management and open research data as part of their open science strategies.