Research data, as the term is used in this policy, is the evidence that underpins answers to research questions, and which is necessary to validate research findings. Data can come in various forms and types, characteristic to specific disciplines of research. For example, data can be quantitative or qualitative information collected by researchers in the course of their work by experimentation, observation, modelling, interview or other methods, or information derived from existing evidence. Research data also includes elements that make the data reusable or re-workable, e.g. documentation of the research process (e.g., in lab- or notebooks), underlying software/code, or algorithms and runtime environments. Research data can be stored at different granularity and can be classified as:
- Raw or primary data: measurements, information recorded as notes, images, video footage, computer files etc. (the raw data may be impossible to store always)
- Processed data: analyses, descriptions and conclusions in the form of reports or papers, and
- Published data: information (i.e., publication and plotted data) distributed to others than those involved in data acquisition and administration.