We propose a systemic meta-model for the sustainable simulation of socio-environmental complex systems. The approach presented integrates data uncertainty management, for both representing and manipulating rigorously quantities which may have a finite number of possible or probable values with their interdependencies. We also provide an operationalization of such models for both data retrieving, via an object-relational mapping, and model simulation, via series of triples, which are linked to examples in the field of agriculture.