Semantic model-to-model translation To capture the nexus complex predicate

We propose a model-to-model translation approach to operationalize the solving strategy for a problem in complexity: quantitatively addressing the water-energy-food nexus at different hierarchical levels (national, regional and sectoral). In the framework of a four-year EU funded Research and Innovation project (H2020 MAGIC, G.A. n. 689669 – www.magic-nexus.eu) data scientists and software engineers teamed up to capture the quantitative aspects of the nexus that are to be considered relevant to inform governance and policy making processes. In order to deploy a practical tool-kit, the team is in charge of developing a Nexus Information System capable of backing-up a Dialogue Space where stakeholders could interact and discuss toward consensus. The MAGIC project approach to nexus embodies a perspective rooted in bieconomics toward the accounting of technical and environmental resources required to assure the living standards of our societies. It aims at suitably tackling the nexus among energy, food and water to assess the sustainability as a complex predicate. The analysis of integrated accounting applied to EU state members through a systemic quantitative approach (Multi Scale Integrated Analysis of Social Ecological Metabolism, MuSIASEM) allows to identify relevant metabolic patterns to diagnose their long-term sustainability and also check for opportunities for changes and innovations via scenario simulation. The last two features are realized by means of a custom solver module, capable of being fed by the MuSIASEM representation model specifically designed for MAGIC and to be integrated into the Nexus Information System software suite. This contribution is aimed at presenting the rationale of the problem modeling, key choices made to develop the solver and some details of the way to specify the model.