Robustness against data availability problems in urban energy planning support software

Using an existing decision support system in different data availability situations is a challenge. This is due to the significant variance in terms of what data can be acquired as input for such systems. In urban energy planning, the problem of data availability is even more crucial because of the large amount of data that is required. This problem affects the portability and the viability of such systems. i.e. they can only be used in one single specific situation at a certain point of time, as long as data are available in the same way. This paper presents an ontology-based approach for developing and keeping such systems more robust against data availability problems. The methodology allows integrating the initial requirements of the system, the domain semantics, and a multiple level-of-detail answering mechanism. The results presented in this paper are validated against an application in modeling a modular ontology-based urban energy planning support system. The proposed solution, in this paper, allows the flexibility of these systems in terms of input data. Furthermore, it allows better traceability of how the system fulfills the initial requirements.