The ARIES team combines an innovative simulation platform and a domain-specific programming language to address the task of integrated social ecological systems. Our approach reconciles strong semantics with modelling practice to achieve advantages (such as modularity, flexibility, validation, and integration of multiple paradigms and spatio-temporal scales) that have largely remained unrealized in environmental modeling to this day. The software and programming language, developed by Prof. Ferdinando Villa, are fully open source. The modelling framework facilitates collaborative model development by using advanced web-based technologies like version control and cloud-based data sharing to accommodate the effective use of big data for environmental analysis.
Concept-based (or more technically, semantically driven) approaches have been discussed as a strategy to improve current modelling practices for decades. However, no approach has yet shown enough results to emerge as an accepted standard, making the k.LAB prototype a first real opportunity to reach this stage. k.LAB’s integrated modelling paradigm is ideal for use on the “cloud,” and allows users to query the existing knowledge base and independently contribute data and models that can be shared and linked automatically for other users. This creates a potentially Wikipedia-like archive of community sourced models that grows in value to the scientific community with increasing use. Secure certificates enable us to permit access to certain network-available models to different user groups, allowing very easy access to scientific data and models. The provision of integrative data and models has applicability to numerous fields (e.g., evaluation of disease transmission, commercial modelling of customer behaviors, or financial analysis of the resilience of loan applicants in the face of economic shocks). The diverse uses of k.LAB have not been fully explored.