Explaining Complex System Scenarios Through Advanced Temporal Query Processing: A Temporal Logic-Based Framework

We propose a novel framework for supporting analysis of complex systems described by many temporal variables, such as integrated scenarios, aiming at studying the possible effects on the society of sustainable innovation policies. Integrated scenarios are possible future states of different aspects of the world (e.g., energy, environment, technology, economy, societal system) representing plausible conditions under different assumptions. Temporal queries aim at detecting a specified behavior for the system over time and, hence, at analyzing what variables and dependencies verify some given temporal properties. The proposed framework, called TEMPORal ANAlysis (TEMPORANA), consists of a modular logic language, with a method to specify temporal queries that may be of interest for the analysis at hand, and a software application implementing them. TEMPORANA is experimented on post-processing analysis of a real-life environmental scenario for the Italian system GAINS-Italy (Greenhouse Gas—Air Pollution Interactions and Synergies), which focused on greenhouse gas pollution by involving an expert who actively working in this field. Here, we report on the performance and usefulness of the proposed approach. In order to finely evaluate TEMPORANA’s performance, it is crucial to assess its effectiveness against existing methodologies. To this end, we compare the performance of TEMPORANA with the one of two state-of-the-art techniques from the active literature on event analysis. The latter have been adapted to the context of our research. The study reveals that TEMPORANA is recommended when performing exploratory analysis of complex scenarios involving many variables.