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Ontology in Buffalo August 27, 2012. Barry Smith. Problems. How to find data How to reason with data when you find it How to integrate with other data How to label the data you are collecting Answer annotate your data with a common ontology
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Ontology in BuffaloAugust 27, 2012 Barry Smith
Problems How to find data How to reason with data when you find it How to integrate with other data How to label the data you are collecting Answer annotate your data with a common ontology How to build a common ontology = an ontology that will integrate well with ontologies built for neighboring domains?
Science requires a common suite of ontologies covering all scientific domainsScience is global and seamlessScientific data is public
Ontologists in UB • Barry Smith (Philosophy, Bioinformatics) • Werner Ceusters (Psychiatry, Bioinformatics) • Alan Ruttenberg (Director of UB Clinical and Translational Data Exchange) • Alex Diehl (Neurology, Director of Ontology Services for School of Medicine)
Pain Ontology grant with NIDCR • Protein Ontology grant with NIGMS • Infectious Disease Ontology grant with NIAID • National Center for Biomedical Ontology grant with NIHGR • Cell Ontology grant with NIHGR • SNOMED grant with NLM • ARGOS on EU/US cooperation in Health IT • VIVO / eagle-I collaboration
Collaborations Center for Brain and Behavior Informatics (http://cbbi.buffalo.edu) Stroke Patient Registry Alzheimers Patient Registry Degenerative Disease Ontology Immunology Ontology Roswell Park Cancer Institute (Malignancy Ontology) School of Dental Medicine (Pain Ontology, Picasso EHR)
Institute for Healthcare Informatics • http://ahc.buffalo.edu/ihi/ Center of Excellence in Bioinformatics and Life Sciences • http://www.bioinformatics.buffalo.edu/
Ontologists in Buffalo • Jason Corso (Computer Science – video analysis) • Albert Goldfain (Blue Highway, Inc. – Infectious Disease Ontology, data exchange between devices) • Dagobert Soergel (Information Studies – online advanced certificate program in ontology)
National Center for Biomedical Ontology (NCBO) Stanford University Biomedical Research Mayo Clinic University at Buffalo
GO provides a controlled system of terms for use in annotating (describing, tagging) data • multi-species, multi-disciplinary, open source • contributing to the cumulativity of scientific results obtained by distinct research communities • compare use of kilograms, meters, seconds in formulating experimental results
US $200 mill. invested in literature and data curation using GO over 11 million annotations relating gene products described in the UniProt, Ensembl and other databases to terms in the GO experimental results reported in 52,000 scientific journal articles manually annoted by expert biologists using GO
GO is amazingly successful in overcoming the data balkanization problem but it covers only generic biological entities of three sorts: • cellular components • molecular functions • biological processes and it does not provide representations of diseases, symptoms, …
Original OBO Foundry ontologies (Gene Ontology in yellow)
environments are here Environment Ontology
The OBO Foundry: a step-by-step, evidence-based approach to expand the GO • Developers commit to working to ensure that, for each domain, there is community convergence on a single ontology • and agree in advance to collaboratewith developers of ontologies in adjacent domains. http://obofoundry.org
OBO Foundry Principles • Common governance (coordinating editors) • Common training • Common architecture • simple shared top level ontology • shared Relation Ontology: www.obofoundry.org/ro
Open Biomedical Ontologies Foundry Seeks to create high quality, validated terminology modules across all of the life sciences which will be • non-redundant • close to language use of experts • evidence-based • incorporate a strategy for motivating potential developers and users • revisable as science advances
The OBO Foundry is a collective experiment involving many biological and clinical communities attempting to create terminology resources which will support the goal of modularity one ontology for each domain No need for ‘mappings’
OBO Foundry (example ontologies) GO Gene Ontology CL Cell Ontology SO Sequence Ontology ChEBI Chemical Ontology PATO Phenotype (Quality) Ontology FMA Foundational Model of Anatomy Ontology ChEBI Chemical Entities of Biological Interest PRO Protein Ontology Plant Ontology Environment Ontology Ontology for Biomedical Investigations RNA Ontology
The central distinction universal vs. instance human being vs. Arnold Schwarzenegger science text vs. diary catalog vs. inventory
Ontologies arerepresentations of universals in realityaka kinds, types, categories, species, genera, ...
inventory catalog
instances universals
object organism animal cat instances siamese universals mammal frog
Organ Part Organ Subdivision Anatomical Space Anatomical Structure Organ Cavity Subdivision Organ Cavity Organ Organ Component Serous Sac Tissue Serous Sac Cavity Subdivision Serous Sac Cavity is_a Pleural Sac Pleura(Wall of Sac) Pleural Cavity part_of Parietal Pleura Visceral Pleura Interlobar recess Mediastinal Pleura Mesothelium of Pleura
An example of a simple rule:Each term in an ontology represents exactly one universal For this reason ontology terms should be singular nouns organism headache drug administration
The Pre-History of BFO Aristotle (4th Century BC) Edmund Husserl’s Logical Investigations (1900-01) “Truthmaker” (1984) Patrick Hayes, “Naïve Physics Manifesto” (1985) Qualitative spatial reasoning (1990 – ) DOLCE (1991 – ) GO, FMA (2004 – )
Aristotle’s Ontological Square Universal Particular
Edmund Husserl Universal Particular Coined ‘formal ontology’ Introduced formal mereology First formal account of dependence relations
Truthmaker (1984) Kevin Mulligan, Peter M. Simons and Barry Smith, “Truth-Makers”, Philosophy and Phenomenological Research, 44 (1984), 287–321. Q: What is it in reality in virtue of which a true assertion such as “John has a headache” is true? A: John’s current headache
John Searle mind-to-world direction of fit – have truthmakers Belief Statement Photograph Scientific theory world-to mind direction of fit Plan Instruction Request Command
Hayes’ Naïve Physics Manifesto BFO 1.n: How can we construct a formal ontology (= an ontology formalized using first-order predicate logic) that will represent the entities we experience in our everyday perception and action? BFL 2.n: How can we do this in a way that will alsobe compatible with what we know from physics?
Qualitative spatial reasoning / mereotopology • COSIT Conferences on Spatial Information Theory • http://www.cosit.info/ • Leeds Qualitative Spatial Reasoning Group • http://www.comp.leeds.ac.uk/qsr/ • Anthony Galton • http://empslocal.ex.ac.uk/people/staff/apgalton/ • Thomas Bittner • http://www.buffalo.edu/~bittner3 • Roberto Casati and Achille Varzi, Parts and Places (MIT Press, 1999)
The History of BFO 2004 BFO 1.0 2005 OBO Relation Ontology (RO) 2006 BFO 1.1 adds generically dependent continuants 2012 BFO 2.0 incorporates top-level relations from RO addresses problem of process measurement data (e.g. heart rates)
BFO: A First Look Continuant Occurrent (Process, Event) Independent Continuant Dependent Continuant universals ..... ..... ..... instances
Basic Formal Ontology a true upper level ontology no interference with domain ontologies no interference with issues of cognition no putative fictions
Main reason to use BFO BFO has the largest body of users (compare: This telephone network has the largest number of subscribers) Snowballing network effects: data annotated using BFO-conformant ontologies becomes more valuable numbers of people with expertise in building BFO-conformant ontologies increases
How BFO is constructed and maintained Simplicity BFO has objects BFO has qualities of objects BFO has no qualities of qualities Simplicity BFO has particulars BFO has universals Only particulars instantiate universals (no ‘meta-universals’)
How BFO is constructed and maintained Perspectivalism: Ontologies are windows on reality There is a multiplicity of windows (perspectives), all equally veridical, i.e. transparent to reality For example we can view an organism as a single object or as a collection of molecules (granular perspectives)
Ontological realism reality exists behind a transparent grid = a veridical partition Barry Smith, “Beyond Concepts, or: Ontology as Reality Representation”, (FOIS 2004), http://ontology.buffalo.edu/bfo/Beyond_Concepts.pdf
Many veridical partitions The common sense partitions of folk physics, folk psychology, folk biology, are to a large degree transparent to realityIt is such common sense partitions that are involved, for instance, when someone takes your temperature in the hospital Common sense involves many verdical partitions otherwise we would all be dead
The fundamental thesis of ontological realism • that many of our natural-language and scientific partitions are transparent to reality • is in fact quite trivial
Three Fundamental Dichotomies • Universal/Type vs. instance • Continuant vs. occurrent • Dependent vs. independent http://ontology.buffalo.edu/bfo/