Research data are all research-related analog data, documents, and objects that are to be digitized in the course of a given research process as well as to “born digital” (i.e., originally created in a digital medium) data, documents, and objects produced in the course of a research process and/or that are the object or result of such a process. Research data are also defined as any data that facilitate the documentation, transparency, and – depending on the research area – replication of research outcomes (metadata).

Common examples of such research data are digitizations, audiovisual data, digital representations of analog data, measurement data, observation data, survey data, texts and text editions, databases, object collections, protocols, methodological test procedures, questionnaires, software, and simulations. The German Research Foundation (DFG) also defines source code and software as research data where they represent central outcomes of scientific research. The broad spectrum of data types reflects the diversity of scientific disciplines and their different research methods and processes.

In the course of the research process, research data can take on several forms. They may vary in quality depending on how they are prepared or if additional data are added. The form of the data may also depend on the stage of processing, or they may be provided in different formats for presentation purposes. Furthermore, they may be subject to varying access regulations (open data, restricted data, closed data).

See: Deutsche Forschungsgemeinschaft. 2022. ‘Guidelines for Safeguarding Good Research Practice. Code of Conduct’. https://doi.org/10.5281/zenodo.6472827.