Abstract:

The built environment has a data problem. The buildings, cities, water treatment plants, and other human-made systems produce more data now than ever before, opening new possibilities of using data to optimize operation, reduce energy consumption, predict performance, and identify faults. However, the complexity, heterogeneity, and high degree of churn of these systems makes it expensive and difficult to develop software for them. Models, control sequences, data analytics, and other software-based solutions must often be rewritten from scratch for each environment in which they will be deployed. The process of discovering and accessing data is further exacerbated by the lack of standardized structured representations of built environment systems. These challenges significantly impede the adoption of data-driven sustainable practices at societal scale.

This talk will explore the use of semantic knowledge graphs to normalize descriptions of the built environment, specifically smart buildings, and reduce the cost of developing and deploying data-driven software in these settings. First, I will describe how ontologies can constrain knowledge graphs to produce useful abstractions of complex cyber-physical systems, as typified by the Brick ontology for smart buildings. Elements of this work are being adapted into new knowledge graph standards for buildings. Next, I will show how knowledge graphs enable novel programming models for “portable software” where programs can adapt their own operation to individual environments, based on queries against the knowledge graph. The talk will also show how these emerging use cases for knowledge graphs contrast with prevailing approaches towards knowledge graph maintenance and management and give rise to new methods for specifying and repairing knowledge graphs. Finally, I will show how these new technologies enable novel applications for smart buildings.

Speaker(s): , Dr. Fierro

Virtual: https://events.vtools.ieee.org/m/418393