EnergonQL: A Building Independent Acquisitional Query Language for Portable Building Analytics.

Emerging building analytics heavily rely on data-driven machine learning algorithms. However, writing these analytics is still challenging: developers not only need to know what data is required but also where this data is in each individual building when writing applications. To bridge this gap between analytics and the actual resources in buildings, we present EnergonQL, a building independent acquisitional data query language that extracts data for building analytics with a declarative query processor. EnergonQL provides logic views of building resources that universally apply to all buildings, thus allowing portable building analytics across buildings. We evaluate EnergonQL with four different building analytics and show that with EnergonQL the line-of-code and development efforts can be effectively reduced.