Data on our cultural heritage hold enormous potential for Europe’s economic growth, for the construction of a more inclusive narrative of its past, and for the future collective identity of its citizens. The biggest obstacle to unlocking that potential is the current lack of integration and interoperability among the countless datasets describing the holdings of European heritage institutions. ManuscriptAI will help remove that obstacle for the data on Europe’s medieval written heritage, manuscripts. Premodern handwritten books are a pivotal category of our heritage, yet they are currently underrepresented in large research infrastructures and their catalog data locked in digital silos. ManuscriptAI will employ machine learning algorithms to construct a model capable of facilitating the automatic integration of distinct data sources describing medieval manuscripts, under a predefined set of machine-understandable vocabulary terms. The model will be made accessible through a human engagement interface and tested during a pilot in a real-world setting. The project will fill two important desiderata: (1) a user-friendly AI-tool to allow heritage professionals to convert their metadata on manuscripts to Linked Open Data, and (2) a dedicated ontology for the description of medieval manuscripts to complete CIDOC-CRM extensions for the cultural heritage domain. The project, building on the achievements of the ERC-2018-stg PASSIM, is supported by a strong consortium of domain experts, heritage professionals and institutes, and (inter)national research infrastructures. ManuscriptAI will advance the EU’s agenda for digital heritage. The tool will help democratise datafication, making Linked Open Data accessible to small heritage institutions and actively involving them in its development. This integration tool for data on medieval manuscripts will be a huge step forward for the digital preservation and usability of Europe’s unique handwritten heritage.

The Portuguese ecThe Portuguese ecosystems belong to the most nitrogen (N) sensitive in the world and are being threatened by N deposition. Current assessments indicate that the scenario’s compliant to the National Emissions Ceiling (NEC) Directive show that this situation is not about to change even with the significant emission reductions planned until 2030 in Europe. Hence, the Portuguese ecosystems remain at risk, but current research and policy support capacity are lacking. FONDA twinning proposal aims to further develop the expertise of University of Aveiro (UAVR, Portugal) in the field of modelling & mapping the emissions, transport, transformation and deposition of reactive nitrogen (Nr) compounds, through a strategic research partnership with TNO (the Netherlands) and the Free University of Berlin (FUB, Germany) - moving towards a highly productive scientific research group. Understanding the budget of N species is of great importance to better understand the interactions/feedbacks between atmospheric chemistry, biodiversity and climate change. The two internationally leading groups are complementary in their orientation towards fundamental science and education (FUB) and applied science and policy support (TNO). Together, they are responsible for the N deposition mapping for Germany and the innovation therein. The key role of UAVR will be to coordinate this consortium of excellence in the air quality modelling field, while developing and increasing its knowledge, expertise and reputation on N science. Besides the strength of UAVR excellence in the field of air quality by building a national capacity and infrastructure to independently quantify nation-wide N deposition; FONDA aims to train a new generation of highly skilled researchers by offering innovative education and advanced training programs for researchers in their early career stages & develop an innovation framework that is sustainable and allows for strategic collaboration after the project.