Construction Data Standards and AI: Ontologies and Crosswalks (IFC, Uniclass, COBie)
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Register Now →Construction data does not join up. IFC, Uniclass 2015, COBie and BOT each describe the same building in different vocabularies, and the same word means different things in each.
This course explains those standards in plain language, then shows how to build and check a crosswalk between them, including the false friends that break AI classification silently.
15 lessons with a graded quiz on every lesson. Free and open to access.
What you will learn
- Read IFC, Uniclass 2015, COBie and BOT without a specification in front of you
- Recognise a good crosswalk and the false friends that wreck a bad one
- Understand why falsifiability matters more than a clean validation report
- See where AI classification fails on construction data without a safety net
- Apply an open, published crosswalk to your own project
Course curriculum
15 lessons, each with a graded quiz.
Module 1: Why the data does not join up
The joining problem, and what an ontology means in construction terms.
Module 2: The four standards
IFC, Uniclass 2015, COBie and BOT, each in plain language.
- IFC in plain language
- Uniclass 2015: the tables that classify everything
- COBie: the handover workbook
- BOT: the smallest useful building ontology
Module 3: Crosswalks and how they fail
What a good crosswalk looks like, the false friend problem, and falsifiability.
- What a crosswalk is, and what a good one looks like
- The false friend: one word, three standards, two meanings
- Falsifiability: when a machine can tell you that you are wrong
Module 4: AI on construction data
The zero percent problem, part versus kind, and the element, system and product strata.
- The zero percent problem: AI classification without a safety net
- Part or kind? The framed structures trap
- Strata: element, system, product, and the as-supplied line
Module 5: Using the open crosswalk
How the crosswalk was built and checked, what it means for AI on your project, and how to apply it.
