Abstracts Category : Other

Data curation with ontology functional dependences

by Alexander Keller

Poor data quality has become a pervasive issue due to the increasing complexity and size of modern datasets. Functionaldependencies have been used in existing cleaning solutions to model syntactic equivalence. They are not able to modelsemantic equivelence, however. We advance the state of data quality constraints by defining, discovering, and cleaningOntology Functional Dependencies. We define their theoretical foundations, including sound and complete axioms, andlinear inference procedure. We develop algorithms for data verification, constraint discovery, data cleaning, ontologyversus data inconsistency identification, and optimizations to each. Our experimental evaluation shows the scalability andaccuracy of our algorithms. We show that ontology FDs are useful to capture domain attribute relationships, and cansignificantly reduce the number of false positive errors in data cleaning techniques that rely on traditional FDs.Advisors/Committee Members: Szlichta, Jaroslaw.