Medieval research objects are part of the cultural heritage. Preserving, developing and making them accessible in a variety of ways for further analysis is a core task of medievalists. Digital approaches and practices are constantly creating new possibilities for this, which is gradually changing the mode of research: The ‘Network Linked Open Middle Ages’ is intended to offer qualified young researchers an interdisciplinary platform to enrich relevant existing sources of digital medieval studies with innovative procedures, to evaluate these methods and to research the resources together in pilot studies.

Linked-Open-Data-Procedures (LOD) are intended to optimise the quality and depth of data access in such a way that new approaches to the research objects are opened up, which are not only sustainably developed, but whose contextualisation also contributes to a better understanding of the data. The evaluation of the applied methods and the identification of the resulting research potential form two equal pillars within the framework of the envisaged network. LOD is a pragmatically sensible option to tap and further enrich resources and thus make them visible, available and usable for very different research approaches. At the same time, LOD procedures adhere to the FAIR principles (“Findable, Accessible, Interoperable, and Re-usable”) and thus reflect the claim of the open network outlined here in terms of Open Science.

Digitisation turns objects into research data with a high level of evidence for a contemporary expert discourse. While LOD procedures are established for the registration of cultural assets, they have so far played hardly any role in the indexing of research data. Medieval studies, which is interdisciplinary per se, offers a suitable use case for a research-oriented adaptation of these procedures. Based on concrete resources and research contexts of the participating researchers, the network will systematically test for the first time to what extent LOD procedures can be implemented in order to improve the quality of the data and thus also the possibilities and quality of their research. The gained knowledge can be transferred to other disciplines and will be made available to the scientific community as ‘best practices’. This goes hand in hand with an exchange with various specialist communities and actors from the field of research data management. 

The increased interconnectedness of the data is accompanied by an intensive cross-disciplinary exchange between the participating scientists and their institutions. The resulting networks promise a sustainable foundation for the future, which not only connects the data, but also the researchers involved.