Describes current work in ontology in Buffalo, focusing especially on biomedical ontology

1. Ontology in Buffalo
June 6, 2013
Barry Smith

2. Watson’s law of
bioinformatics ontologies
“As the time spent discussing a
particular bioinformatics topic
grows longer, the probability that
someone will suggest the group
develops an ontology for that topic
approaches 1”
http://biomickwatson.wordpress.com

3. Watson’s Ontology of Bioinformaticians
Top level is
bioinformatician
bioinformation bioinformation
interested in ontology not interested in ontology

5. • Stanford University Biomedical Informatics Research
• Mayo Clinic Department of Biomedical Informatics
• University at Buffalo Department of Philosophy
Three US partner institutions:

7. RELATION
TO TIME
GRANULARITY
CONTINUANT OCCURRENT
INDEPENDENT DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical
Entity
(FMA,
CARO)
Organ
Function
(FMP, CPRO) Phenotypic
Quality
(PaTO)
Biological
Process
(GO)
CELL AND
CELLULAR
COMPONENT
Cell
(CL)
Cellular
Component
(FMA, GO)
Cellular
Function
(GO)
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
(GO)
Molecular Process
(GO)
Open Biomedical Ontologies (OBO) Foundry
(Gene Ontology marked in yellow)

10. © Ocean Informatics 2005 4.10
Enterprise
Comprehensive Basic
Components
EHR
Multimedia
genetics
workflow
identity
Clinical
ref data Clinical
models
terms
realtime
gateway
telemedicine
HILS
other
provider
UPDATE
QUERY
demographics
guidelines
protocols
Interactions DS
Local
modelling
notifications
DSS
PAS
billing
portal
Allied
health
patient
PAYER
Msg gateway
Imaging lab
ECG etc
Path lab
LAB
Secondary
users
Online drug,
Interactions DB Online
archetypes
Online
terminology
Online
Demographic
registries
Patient
Record
with thanks to Thomas Beale

11. 11

12. Explosion of “biomedical ontology” since 1999

13. Biomedical Ontologies co-developed at UB
BCO Biocollections Ontology
BFO Basic Formal Ontology
CL Cell Ontology
ENVO Environment Ontology
FMA Foundational Model of Anatomy
GO Gene Ontology
IDO Infectious Disease Ontology
ND Neurological Disease Ontology
MFO Mental Functioning Ontology
NPT Neuropsychological Testing Ontology
OBI Ontology for Biomedical Investigations
OGMS Ontology for General Medical Science
OHD Oral Health and Disease Ontology
PCO Population and Community Ontology
PO Plant Ontology
PRO Protein Ontology

14. Biomedical Ontologies co-developed at UB
BCO Biocollections Ontology
BFO Basic Formal Ontology
CL Cell Ontology
ENVO Environment Ontology
FMA Foundational Model of Anatomy
GO Gene Ontology
IDO Infectious Disease Ontology
ND Neurological Disease Ontology
MFO Mental Functioning Ontology
NPT Neuropsychological Testing Ontology
OBI Ontology for Biomedical Investigations
OGMS Ontology for General Medical Science
OHD Oral Health and Disease Ontology
PCO Population and Community Ontology
PO Plant Ontology
PRO Protein Ontology

16. http://www.ifomis.org/bfo/users

17. Biomedical Ontologies co-developed at UB
BCO Biocollections Ontology
BFO Basic Formal Ontology
CL Cell Ontology
ENVO Environment Ontology
FMA Foundational Model of Anatomy
GO Gene Ontology
IAO Information Artifact Ontology
IDO Infectious Disease Ontology
ND Neurological Disease Ontology
MFO Mental Functioning Ontology
NPT Neuropsychological Testing Ontology
OBI Ontology for Biomedical Investigations
OGMS Ontology for General Medical Science
PCO Population and Community Ontology
PO Plant Ontology
PRO Protein Ontology

18. Biomedical Ontology in Buffalo

19. BS, Alan Ruttenberg, Alex Diehl
Philosophy
Dental School,
IHI
Neurology

20. Werner Ceusters, Dagobert Soergel, Peter Elkin
Psychiatry, IHI
Dental School,
Library and
Information Studies
new Chair of
Biomedical
Informatics

21. IHI: Institute for Healthcare Informatics

22. IHI Ontology Machine

23. Strategy
• using BFO, OGMS and their extension ontologies
to provide a consistent framework for the
representation of the types of particulars
• developing systematic ways for the consistent
tracking of particulars (patients, disorders,
encounters …)
• putting these together to serve consistent
representation of the assertional knowledge in
the IHI repository

24. Strategy
• using BFO, OGMS and their extension ontologies
to provide a consistent framework for the
representation of the types of particulars
• developing systematic ways for the consistent
tracking of particulars (patients, disorders,
encounters …)
• putting these together to serve consistent
representation of the assertional knowledge in
the IHI repository

25. Acknowledgement
• IDO: Immune System Biological Networks: A Case
Study in Improved Data Integration & Analysis (NIH /
NIAID)
• ImmPort: Bioinformatics Integration Support
Contract (NIH/NIAID)
• Plant Ontology (NSF)
• OPMQoL: Ontology for Pain and Related Disability,
Mental Health and Quality of Life (NIH/National
Institute of Dental and Craniofacial Research)
• PRO: A Protein Ontology in Open Biomedical
Ontologies (NIH/NIGMS)
• NCBO: National Center for Biomedical Ontology
(NIH/NHGRI)

26. Further reading
National Center for Ontological Research
http://ncor.buffalo.edu
Contact
phismith@buffalo.edu