Download
1 / 33
330 likes | 451 Views
University at Buffalo The Center for the Arts October 27, 2005. national center for ontological research. Department of Philosophy now largest group of core ontology faculty in the world New York State Center of Excellence in Bioinformatics & Life Science
E N D
University at Buffalo The Center for the Arts October 27, 2005
Department of Philosophy now largest group of core ontology faculty in the world • New York State Center of Excellence in Bioinformatics & Life Science • ORG: The Ontology Research Group http://ncor.us
Stanford Medical Informatics, • Director: Mark Musen • Protégé • Applied Ontology • National Center for Biomedical Ontology http://ncor.us
From chromosome to disease http://ncor.us
genomics • proteomics • reactomics • metabonomics • phenomics • behavioromics • toxicopharmacogenomics • … legacy of Human Genome Project http://ncor.us
-omics data • biochemical disease pathway data • biomedical image data • electronic health record data • hospital management data • hospital insurance data • public health data • Chinese chicken data http://ncor.us
a vast new problem of communication • medical researchers, clinical practitioners, first responders, customs agencies, pharmaceutical companies, disease control centers need to communicate in ways which involve huge amounts of data http://ncor.us
Problem • how to reason with data from different sources each of which uses its own system of classification http://ncor.us
Solution: • Ontology ! http://ncor.us
Ontology (phil.) • The branch of metaphysics that deals with the nature of being. • Ontologies (tech.) • Standardized classification systems which enable data from different sources to be combined http://ncor.us
The need • strong general purpose classification hierarchies created by domain specialists • clear, rigorous definitions • thoroughly tested in real use cases http://ncor.us
The actuality (too often) • myriad special purpose ‘light’ ontologies, prepared by ontology engineers and deposited in internet ‘repositories’ or ‘registries’ http://ncor.us
ontologies for ‘agent’ http://ncor.us
often do not generalize … • repeat work already done by others • are not interoperable • reproduce the very problems of communication which ontology was designed to solve • contain incoherent definitions • and incoherent documentation http://ncor.us
A tragic example • “Health Level 7 Reference Information Model” (HL7 RIM) • – a standard for exchange of information between clinical information systems http://ncor.us
The ultimate special purpose ontology • A healthcare messaging system used as the basis for an entire clinical record architecture, extending as far as core genomic data • Rather like using air-traffic control messaging as starting point for a science of airplane thermodynamics http://ncor.us
National Cancer Institute National Biospecimen Network (NBN) • “The NBN bioinformatics system should be standards-based (e.g., SNOMED, HL7, or MIAME for data; Internet for communications) to enable data and information exchange among system components and the researchers who use them.” http://ncor.us
HL7 Glossary • Animal • Definition: A subtype of Living Subject representing any animal-of-interest to the Personnel Management domain. • LivingSubject • Definition: A subtype of Entity representing an organism or complex animal, alive or not. http://ncor.us
HL7 Glossary • Person • Definition: A Living Subject representing single human being [sic] who is uniquely identifiable through one or more legal documents • – impossible to refer to undocumented persons http://ncor.us
HL7’s backbone ‘Act’ class • Act • Definition: An Act is the record of an Act • An X is the Y of an X • “There is no difference between an activity and its documentation” http://ncor.us
HL7 Incredibly Successful • adopted by Oracle as basis for its Electronic Health Record technology; supported by IBM, GE, Sun ... • embraced as US federal standard • central part of $18 billion program to integrate all UK hospital information systems http://ncor.us
What’s gone wrong? • People of good will are making mistakes because of lack of expertise • Money is wasted on megasystems that cannot be used • Even large ontologies are built in the spirit of the amateur hobbyist http://ncor.us
GlaxoSmithKline * • What we need is “industrial-strength” ontologies with a consistent and rich representation formalism that are amenable for use as an integration framework, and support reasoning capabilities. We anticipate that pharma’s need to bring together mountains of data and information and to properly analyse that information all depend on having a stable, well-developed semantic framework that links information/data and that allows reasoning systems to perform some of our more "mundane" analysis work. • *Robin McEntire http://ncor.us
Signs of hope • founding of National Center for Biomedical Ontology (an NIH Roadmap Center) • increased recognition of FMA • Open Biomedical Ontologies consortium • introduction of rigorous logical tools and scientific methods in the creation of content-rich ontologies for automatic reasoning and seamless integration http://ncor.us
Why NCOR? • NCOR will • advance ontology as a discipline employing rigorous scientific methods • develop objective, empirical measures of quality for ontologies in ways which will lead to the establishment of best practices http://ncor.us
Why NCOR? • NCOR will • provide coordination and support for investigators working on theoretical ontology and its applications • engage in outreach endeavors designed to foster the goals of high quality ontology in both theory and practice http://ncor.us
ontologies are ambitious classification systems • they rely on definitions, • on the logic of relations, • and on theories of high-level categories such as function, process, thing, event, constituent if you want to build a good ontology … WORK WITH A PHILOSOPHER http://ncor.us
