Building data models and data sharing. Purpose, approaches, and a case study on explainable demand response

There are several approaches to building data modelling and there is a well-established rationale for the various related standards emerging in the area. In this work we acknowledge the importance of these approaches but also discuss their limitations. To this extent we draw the line between open data and open sharing and discuss its relevance. We also introduce a case study of a demand response application integrated with a XAI (explainable artificial intelligence) demand forecasting and we use it to practically highlight how open data and open sharing features interplay and integrate. We also discuss how open building model design will need to develop, so as to account for vital, in some cases, explainability information.

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