Towards an engineering methodology for multi-model scientific simulations

Complex physical phenomena are characterized by sub-systems that continuously interact with each other, and that can be modeled with different computational models. To study such phenomena we need to integrate the heterogeneous computational models of the different sub-systems to precisely analyze the interactions between the various aspects that characterize the phenomenon as a whole. While efficient methods and consolidated software tools are available to build and simulate single models, the problem of devising a general and effective approach to integrate heterogeneous models has been studied only recently and is still largely an open issue. In this paper, we propose an engineering methodology to automate the process of integrating heterogeneous computational models. The methodology is based on the novel idea of capturing the relevant information about the different models and their integration strategies by means of meta-data that can be used to automatically generate an efficient integration framework for the specific set of models and interactions. In this position paper we discuss the various aspects of the integration problem, highlight the limits of the current solutions and characterize the novel methodology by means of a concrete biological case study