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Horned-OWL: Building Ontologies at Big Data Scale

Lookup NU author(s): Dr Phillip Lord, Dr Jennifer Warrender


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© 2021 Copyright for this paper by its authors.Ontologies have been widely used for representing data in biomedicine. The largest have 100,000s of concepts, and taken together all the ontologies in bioportal there are nearly 10 million classes. The computational infrastructure that we have to support these efforts though will often not scale to this size, requiring either splitting the ontology into parts or high memory computers. We have designed and built a new library, Horned-OWL, implemented in Rust that can scale to 10 million classes on a standard desktop machine, with large performance differences compared to the Java based OWL API. We believe that as well as enabling scalability, higher levels of performance can alter the way we build ontologies by making what is currently difficult, simple, and fast.

Publication metadata

Author(s): Lord P, Warrender J

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: CEUR Workshop Proceedings

Year of Conference: 2021

Pages: 134-136

Acceptance date: 16/09/2021

Publisher: CEUR-WS