ART(AutoRuleTransform): Opensource Dataset and Algorithms for Automated Rule Interpretation of Building Codes


Sine early 2019, our group devotes most of our efforts on developing new methods for automated interpretation and understanding of regulatory documents. Starting from web crawling of regulatory texts, we developed a few tools to structurize, interprete, and transform regulatory texts into computer-interpretable formats. During this process, a large scale dataset and a few algorithms are developed. Various types of clauses, including simple clauses, complex clauses with multiple constraints, high-order constraints and implicit properties are considered when developing the dataset and algorithms. Here we opensource our work for future research and explorations such as automated compliance checking (automated rule checking), smart standards, etc. You can download the dataset and algorithms here for research and exploration purpose. Latest updates of the dataset and algorithms could be found at github page.

The dataset and algorithms are named as ART(short for AutoRuleTransform), with the hope to make civil engineering more artiful in the future:)

If our work is adopted or used in your work, please cite the following articles:

  1. Zheng, Z., Zhou, Y.C., Lin, J.R., Lu, X.Z. (2022). Integrating NLP and Context-Free Grammar for Complex Rule Interpretation towards Automated Compliance Checking. Computers in Industry, 142, 103746.

  2. Zheng, Z., Zhou, Y.C., Lu, X.Z., Lin, J.R. (2022). Knowledge-Informed Semantic Alignment and Rule Interpretation for Automated Compliance Checking. Automation in Construction, 142, 104524.

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