The mass digitization of sources that has been initiated by the project on the History of Max Planck Society (GMPG) is a challenge for computational history. The vast quantity of content is far too large to be read by the researchers in the project. Digital methods therefore have to be developed and applied in order to structure the sources. This involves the development of a database that contains the relevant information about actors and organizations, about the application of OCR (optical character recognition) to render the documents searchable, and text-mining methods to pinpoint the relevant sources but also to direct the process of selecting the sources and priorities for digitization. Network analytical methods help to uncover the cooperation structures that are documented in the sources. A combination of topic-modeling and network analysis allows the relation of topics mentioned in the context of a commission with persons also mentioned in the documents.
The focus so far was on getting first insights into how interdisciplinary cooperation within the Max Planck Society is structured. This is pursued by analyzing the background of members of commissions who decide on new institutions but also on the role of persons in the network based on their function within the society. At this stage of the project, the research question is directed primarily at finding significant differences in the data and the accepted narrative. This research aims to highlight the areas where more research and additional sources are needed rather than giving new explanations. Thus, the research is intended to help with the selection of case studies for deeper analysis and to place these case studies in a wider context.