OBO-Foundry

1. OBO-Foundry

2. OBO was conceived and announced in in 2001 10 october 2001 Michael Ashburner and Suzanna Lewis with acknowledgements of others in the GO community. open biology ontologies - obo.org The success of GO leads us to propose the formation of an umbrella body which we call OBO - open biology ontologies. OBO would act as an umbrella site for GO and other ontologies within the broad domain of biology.

3. Open Biomedical Ontology It is critical that ontologies are developed cooperatively so that their classification strategies augment one another.

4. Original OBO Criteria • The ontology must be OPEN and available to be used by all without any constraint other than (a) its origin must be acknowledged and (b) it is not to be altered and subsequently redistributed under the original name or with the same identifiers. • The ontologies are in, or can be instantiated in, a COMMON SHARED SYNTAX. This may be either the OBO syntax, extensions of this syntax, or OWL. • The ontology must be ORTHOGONAL to other ontologies already lodged within OBO. • The ontologies possesses a UNIQUE IDENTIFIER space within the OBO Foundry. • The ontologies include TEXTUAL DEFINITIONS for all terms.

5. Implicit ontologies • cysteine biosynthesis (ChEBI) • myoblast fusion (Cell Type Ontology) • hydrogen ion transporter activity (ChEBI) • snoRNA catabolism (Sequence Ontology) • wing disc pattern formation (Drosophila anatomy) • epidermal cell differentiation (Cell Type Ontology) • regulation of flower development (Plant anatomy) • interleukin-18 receptor complex (not yet in OBO) • B-cell differentiation (Cell Type Ontology)

6. Relations to Other Ontologies CL GO blood cell cell differentiation lymphocyte differentiation lymphocyte B-cell activation B-cell is_a B-cell differentiation

7. CELL Ontology [Term] id: CL:0000236 name: B-cell is_a: CL:0000542 ! lymphocyte develops_from: CL:0000231 ! B-lymphoblast Augmented GO [Term] id: GO:0030183 name: B-cell differentiation is_a: GO:0042113 ! B-cell activation is_a: GO:0030098 ! lymphocyte differentiation intersection_of: is_a GO:0030154 ! cell differentiation intersection_of: has_participant CL:0000236 ! B-cell

8. TIGR, December 6-7, 2002

9. Anatomy Cell Chemical Drug Disease Environmental context . . . Qualifier Unit GO - biological process GO - molecular function GO - cellular component There are many ontologies needed

10. Latest OBO Criteria • The ontology is OPEN and available to be used by all. • The ontology is in, or can be instantiated in, a COMMON FORMAL LANGUAGE. • ORTHOGONALITY: They commit to working with other Foundry members to ensure that, for any particular domain, there is community convergence on a single controlled vocabulary. • IDENTIFIERS: The ontology possesses a unique identifier space within OBO. • The ontology includes TEXTUAL DEFINITIONS and where possible equivalent formal definitions of its terms.

11. New OBO Criteria • The developers of the ontology agree in advance to COLLABORATE with developers of other OBO Foundry ontology where domains overlap. • UPDATE: The developers of each ontology commit to its maintenance in light of scientific advance, and to soliciting community feedback for its improvement. • VERSIONING: The ontology provider has procedures for identifying distinct successive versions to ensure BACKWARDS COMPATIBITY with annotation resources already in common use • CLEARLY BOUNDED: The ontology has a clearly specified and clearly delineated content. • DOCUMENTATION: The ontology is well-documented. • USERS: The ontology has a plurality of independent users. • COMMON ARCHITECTURE: The ontology uses relations which are unambiguously defined following the pattern of definitions laid down in the OBO Relation Ontology.*

12. The success of ontology alignment demands that ontological relations (is_a, part_of, ...) have the same meanings in the different ontologies to be aligned. Agree on relations Genome Biology 6:R46, 2005.

13. Orthogonality of ontologies implies additivity of annotations • If we annotate a database or body of literature with one high-quality biomedical ontology, we should be able to add annotations from a second such ontology without conflicts

14. To create the conditions for a step-by-step evolution towards robust gold standard reference ontologies in the biomedical domain. • To introduce some of the features of scientific peer review into biomedical ontology development. • obofoundry.org

15. Building out from the original GO

16. Why Survey Domain covered? Public? Community? Active? Salvage Develop Applied? Improve yes no Collaborate & Learn (Listen to Barry)

17. Necessary character of a computational environment for biological research • Sustainable • There must be mechanism for maintaining the environment (that is less than the initial cost). • Adaptable • It must work for the complete spectrum of data types, from genomics to clinical trials • It must continually adapt to new knowledge and new technologies • Interoperable • The capability of easily integrating data from a variety of sources. • Evolvable • Mechanisms must be put in place to respond to the needs of the biomedical research community. They provide the primary selection pressure on the evolution of the technology.

18. There is no requirement that ontology construction be done using any particular technology.

19. The Scientific Method • A body of techniques for investigating phenomena and acquiring new knowledge, as well as for correcting and integrating previous knowledge. It is based on observable, empirical, measurable evidence, and subject to rules of reasoning. • Isaac Newton (1687, 1713, 1726). "Rules for the study of natural philosophy", Philosophiae Naturalis Principia Mathematica, Book 3, The System of the World. Third edition, the 4 rules as reprinted on pages 794-796 of I. Bernard Cohen and Anne Whitman's 1999 translation, University of California Press ISBN 0-520-08817-4, 974 pages.

20. No text search can retrieve all of the correct results, and nothing more Serine/threonine-protein kinase pef1 Negative Regulator of the PHO system CDC2-like serine/threonine-protein kinase CRP Hypothetical protein T27E9.3 CDK5 protein Protein kinase ENSANGP00000018692 Hypothetical protein Cyclin-dependent protein kinase 5 Cell division protein kinase 5

21. Contrast—two types of ontology • Natural-science ontologies capture terminology-level knowledge underlying the best current science (e.g. GO, PATO, SO) • Administrative ontologies prepared for specific, local purposes (e.g. billing, bloodbank, lab workflow, literature indices) • Scientific ontologies are realism-based

22. Elements for Success 2 • Keep It Simple: • lowest possible barrier to entry • Technology independence • “With new data, we change our minds” • An ontology must adapt to reflect current understanding of reality • Plan for and anticipate changes • Stay close to your users • biologists and medical researchers

23. Truth springs from arguments amongst friends. David Hume

24. BIRN • DictyBase • FlyBase • MGI • NESCENT • ZFIN • And more… Others… • Seth Carbon • John Day-Richter • Karen Eilbeck • Mark Gibson • Chris Mungall • Shu Shengqiang • Nicole Washington • Mark Musen • Barry Smith • Monte Westerfield • Michael Ashburner • Daniel Rubin • And more… Berkeley BOP NCBO • Michael Ashburner • Judith Blake • J. Michael Cherry • David Hill • Midori Harris • Rex Chisholm • And many more… With thanks to* GO *Without even going into our other projects: Apollo, SO, Chado, GMOD, DAS, Reactome…