1. The National Center for Biomedical Ontology
Stanford – Berkeley Mayo – Victoria – Buffalo UCSF – Oregon – Cambridge

2. Ontologies are essential to make sense of biomedical data

3. Biologist have adopted ontologies
To provide canonical representation of scientific knowledge
To annotate experimental data to enable interpretation and comparison across databases
To facilitate knowledge-based applications for
Decision support
Natural language-processing
Data integration

5. A Portion of the OBO Library

7. Knowledge workers seem trapped in a pre-industrial age
Most ontologies are of relatively small scale
Most ontologies are built and refined by small groups working arduously in isolation
Success rests heavily on the particular talents of individual artisans, rather than on standard operating procedures
There is an urgent need for technologies to make this process “faster, better, cheaper”

10. A consortium that brings together investigators at
Founded in September 2005 to provide a national focus on the use of ontologies in the biomedical sciences
A consortium that brings together investigators at
Stanford University (Ontology-management technology)
Lawrence Berkeley Labs (Use of ontologies for data annotation)
University of Victoria (Ontology and data visualization)
Mayo Clinic (Access to controlled clinical terminologies)
SUNY Buffalo (Best practices for ontology development)
Our goal: Industrial-strength technology for use of ontologies in e-science

11. Capture and index experimental results
National Center for Biomedical Ontology
Capture and index experimental results
Open Biomedical Ontologies
(OBO)
Open Biomedical Data (OBD)
BioPortal
Revise biomedical understanding
Relate experimental data to results from other sources
2005

12. E-science needs technologies
To help build and extend ontologies
To locate ontologies and to relate them to one another
To visualize relationships and to aid understanding
To facilitate evaluation and annotation of ontologies

13. Goals for the National Center for Biomedical Ontology
Integrated ontology libraries in cyberspace
Meta-data standards for ontology annotation
Comprehensive methods for ontology indexing and retrieval
Easy-to-use portals for ontology access, annotation, and peer review
End-user platforms for putting ontologies to use for
Data annotation
Decision support
Natural-language processing
Information retrieval
And applications that we have not yet thought of!

15. Opportunities to collaborate with the Center
Using the Center’s technology
Contributing ontologies to the OBO library
Submitting a proposal to the NIH for a “collaborating R01” grant
Defining a biological driving project