There are some specific framework conditions when dealing with research data on material and immaterial cultural heritage. In terms of global application, these relate to the human right to cultural participation and scientific progress, which, together with the right to education, has been firmly enshrined in German federal legislation under the UN Social Covenant since 1968.
In addition to the national fundamental rights derived from international law, the management of cultural research data must also take into account certain inherent academic paradigms. Due to the fundamental focus of cultural studies on questions of contextualizing lived realities or historical contexts, material or immaterial, often non-digital, objects of study hold a special position as authentic carriers of information, serving as sources of scientific knowledge. Such objects may include physical items like baroque ceiling paintings, Chinese theatre masks, posters from European mobile cinemas, or site plans of buildings destroyed in war, as well as intangible cultural assets like the craft of musical instrument making in Saxony or the German orchestra and theatre landscape, which is also listed as a UNESCO cultural heritage. They could also be recordings of human activities, such as film recordings of performances or phonograph cylinders with vocal recordings, or even biographical data. Therefore, digital data about material and immaterial cultural assets are always merely a media representation of the object of research and not the object of research itself. Even though an increasing amount of cultural works will exist digitally in the future, data will continue to be generated that deals with non-digital works as carriers of information and thus extend their scholarly relevance beyond digital contexts.
The term ‘research data’ in the field of cultural research explicitly includes the data that catalogue the holdings of memorial institutions such as libraries, archives, museums, and monument offices. Digital data often make collection objects, which are the subject of research, discoverable and uniquely identifiable in the first place. The descriptive data of historical material objects already encompass the effort of historical and material inventory and contextualisation—they explain why an object is significant as a cultural heritage item and usable as a research subject. Research data thus already convey fundamental research findings and provide the basis and starting point for further research, often even being the precondition for its very possibility.
Cultural studies have been somewhat hesitant to develop digital methods, unlike the natural, life, and social sciences, which often work with metric data. Since cultural studies primarily deal with non-metric information, even digital data related to the research object is often still analysed using non-digital methods.
However, cultural scholars using digitally available data are increasingly working multimodally: they address their research questions by jointly analysing data related to textual, visual, or auditory objects. In doing so, they often use hybrid, non-integrated software environments. This significantly complicates the effective management, archiving, and reuse of the research data generated in such workflows.
Furthermore, cultural studies research data, oriented around specific heuristic perspectives, can be highly individual: researchers often prepare their sources in a way that is immediately useful for the specific research goal of the project. What works well for one research question and its associated epistemic tools may be of little or no use to other research groups.
Data management in line with the FAIR Principles supports the transition to data that can be understood not only by humans but also by machines. It requires a significant degree of methodological reflection and an IT-oriented perspective in the ‘interpretive' disciplines of cultural studies. The FAIR provision of cultural studies research data, along with open licensing, creates many new opportunities for the scientifically productive reuse of data. At both the European and national levels, support for sharing data across all disciplines is gaining momentum and is already becoming the default approach for publicly funded research and digitisation. Consequently, funding programmes relevant to cultural studies are increasingly aligning their guidelines and required data management plans with the FAIR Principles.