IndShaker: A Knowledge-Based Approach to Enhance Multi-Perspective System Dynamics Analysis

Abstract

Decision making as a result of system dynamics analysis requires, in practice, a straightforward and systematic modeling capability as well as a high-level of customization and flexibility to adapt to situations and environments that may vary very much from each other. While in general terms a completely generic approach could be not as effective as ad hoc solutions, the proper application of modern technology may facilitate agile strategies as a result of a smart combination of qualitative and quantitative aspects. In order to address such complexity, we propose a knowledge-based approach that integrates the systematic computation of heterogeneous criteria with open semantics. The holistic understanding of the framework is described by a reference architecture and the proof-of-concept prototype developed can support high-level system analysis, as well as being suitable within a number of applications contexts—i.e., as a research/educational tool, communication framework, gamification and participatory modeling. Additionally, the knowledge-based philosophy, developed upon Semantic Web technology, increases the capability in terms of holistic knowledge building and re-use via interoperability. Last but not least, the framework is designed to constantly evolve in the next future, for instance by incorporating more advanced AI-powered features.