Ontologies in Biomedicine What is the “right” amount of semantics? Mark A. Musen Stanford University

The National Center for Biomedical Ontology One of three National Centers for Biomedical Computing launched by NIH in 2005 Collaboration of Stanford, Berkeley, Mayo, Buffalo, Victoria, UCSF, Oregon, and Cambridge Primary goal is to make ontologies accessible and usable Research will develop technologies for ontology indexing, alignment, and peer review

Why Develop an Ontology? To share common understanding of the structure of descriptive information –among people –among software agents –between people and software To enable reuse of domain knowledge –to avoid “re-inventing the wheel” –to introduce standards to allow interoperability

Supreme genus: SUBSTANCE Subordinate genera: BODYSPIRIT Differentiae: material immaterial Differentiae: animate inanimate Differentiae: sensitive insensitive Subordinate genera: LIVING MINERAL Proximate genera: ANIMALPLANT Species: HUMANBEAST Differentiae: rational irrational Individuals: Socrates Plato Aristotle … Porphyry’s depiction of Aristotle’s Categories

A Small Portion of ICD9-CM 724Unspecified disorders of the back 724.0Spinal stenosis, other than cervical Spinal stenosis, unspecified region Spinal stenosis, thoracic region Spinal stenosis, lumbar region Spinal stenosis, other 724.1Pain in thoracic spine 724.2Lumbago 724.3Sciatica 724.4Thoracic or lumbosacral neuritis 724.5Backache, unspecified 724.6Disorders of sacrum 724.7Disorders of coccyx Unspecified disorder of coccyx Hypermobility of coccyx Coccygodynia 724.8Other symptoms referable to back 724.9Other unspecified back disorders

The Foundational Model of Anatomy

The NCI Thesaurus in OWL

A Portion of the OBO Library

Some dimensions for characterizing ontologies Large vs. Small (e.g., FMA vs. SOFG Anatomy Entry List) Broad vs. Deep (e.g., UMLS Semantic Network vs. CYC) “Lite” vs. Heavy (e.g., Gene Ontology vs. FMA)

The fundamental paradox GO and other ontologies became popular because they assumed a simple semantics that required little of developers The lack of rich semantics has enabled errors to creep into ontologies such as GO and the meaning of terms and relations to drift Many ontology developers are now turning to rich representation formalisms (e.g., OWL) to overcome these problems—but are they shooting themselves in the foot by doing do?

The GO is elegant in its simplicity!

But there are clear advantages to having richer semantics

Our distinguished panelists Christopher Chute, Professor and Chair, Department of Medical Informatics, the Mayo Clinic Suzanna Lewis, Senior Staff Scientist, Lawrence Berkeley National Laboratory Barry Smith, Professor of Philosophy, University at Buffalo

What is the “right” amount of semantics?