Research data

The term research data covers all types of digital data that are generated in the course of scientific or artistic research work or are the result of such work. This can include numerical data, interview data, audio and video recordings, texts and images, but also complex data such as AV content, 3D objects, software and more. Specific examples of research data that can typically be generated in the field of music research can be found in the position paper of the Gesellschaft für Musikforschung (Society for Music Research) on the handling of research data.

In order for research data to be (re)used in the sense of open science, it must comply with the so-called FAIR data principles. FAIR stands for:

• Findable. This can be achieved, for example, by ensuring that a dataset is clearly identifiable via a specific identifier (ISBN, DOI).
• Accessible, i.e. accessible. Researchers must be able to access the data easily, quickly and, if possible, from anywhere.
• Interoperable, i.e. they must be described by metadata that meets certain formal standards.
• Re-usable, i.e. reusable. This means, for example, that their origin and the conditions of their subsequent use must be clearly identified.