Semantic ontologies offer a formalized, machine-readable frame-work for representing knowledge, enabling the structured descrip-tion of complex systems. In the building domain, the adoption of ontologies like the Brick schema has transformed how buildings and their systems are modeled by providing a standardized, inter-operable language. However, the complexity and the steep learning curve involved in developing and querying semantic models present substantial challenges, often requiring a workforce with specialized expertise. This paper builds on our experience in investigating how Large Language Models (LLMs) can help address these challenges, focusing on their role in constructing and querying of semantic models, particularly using the Brick Schema. Our study outlines the requirements and metrics for evaluating the scalability and effectiveness of LLM-based tools, while also discussing the current challenges and limitations in developing such tools. Ultimately, this paper aims to orient research efforts as various groups experiment with diverse techniques, while enabling more effective comparison of emerging solutions and fostering collaboration across the field.
BT - Proceedings of the 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation DA - 29/10/2024 DO - 10.1145/3671127.3698792 N2 -Semantic ontologies offer a formalized, machine-readable frame-work for representing knowledge, enabling the structured descrip-tion of complex systems. In the building domain, the adoption of ontologies like the Brick schema has transformed how buildings and their systems are modeled by providing a standardized, inter-operable language. However, the complexity and the steep learning curve involved in developing and querying semantic models present substantial challenges, often requiring a workforce with specialized expertise. This paper builds on our experience in investigating how Large Language Models (LLMs) can help address these challenges, focusing on their role in constructing and querying of semantic models, particularly using the Brick Schema. Our study outlines the requirements and metrics for evaluating the scalability and effectiveness of LLM-based tools, while also discussing the current challenges and limitations in developing such tools. Ultimately, this paper aims to orient research efforts as various groups experiment with diverse techniques, while enabling more effective comparison of emerging solutions and fostering collaboration across the field.
PB - ACM PY - 2024 SP - 312 EP - 317 T2 - Proceedings of the 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation T3 - BuildSys '24: The 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation TI - Large Language Models for the Creation and Use of Semantic Ontologies in Buildings: Requirements and Challenges UR - https://doi.org/10.1145/3671127.3698792 ER -