Document Type
Workshop
Abstract
The causal pattern is a proposed ontology design pattern for representing the structure of causal relations in a knowledge graph. This pattern is grounded in the concepts defined and used by the CausalAI community i.e., Causal Bayesian Networks and do-calculus. Specifically, the pattern models three primary concepts: (1) causal relations, (2) causal event roles, and (3) causal effect weights. Two use cases involving a sprinkler system and asthma patients are provided along with their relevant competency questions.
Publication Info
Reprinted from Workshop on Ontology Designs and Patterns at International Semantic Web Conference, 2023.
Jaimini, U., Henson, C., & Sheth, A. (2023). An ontology design pattern for representing causality. WOP’23: Workshop on Ontology Designs and Patterns.
APA Citation
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