Why Can’t We All Just Agree?

1. Why Can’t We All Just Agree? Dave McComb August 11, 2010 Federal Data Architecture Subcommittee Semantic Arts

2. Your Current Situation (Greatly Simplified) • Each of your agencies has evolved, over long periods of time, complex systems • In aggregate each agency has at least tens of thousands, and mostly hundreds of thousands and some of you may have millions, of distinctions coded into those systems • Each agency already relies on more distinctions than anyone could possibly understand • And, you’ve been asked to “interoperate”

4. UnitOfMeasure Magnitude A Semantic Intermediary Collections Concepts Organization Time Place Landmark Person/UniqueItem Substance Documents Agreements Behavior Intention

5. Desirable Attributes of a Semantic Intermediary • Simplicity • Coverage • Unambiguous • Specificity • Modular • Fractal

6. A candidate that meets these criteria • And is free • As in free speech • Available under Creative Commons License • And free beer • At no charge • gist.owl

7. UnitOfMeasure Magnitude Simplicity (130 classes in 14 groups) Collections Concepts Time Place Landmark Person/UniqueItem Substance Organization Documents Agreements Behavior Intention

8. 132 Properties in six families (Mereology) (Subject exclusively possesses Object ) [CarAhasDirectPartEngineB] [Person1 hasMagnitudeWeight100] (Teleology) (Spatial Relations) [Dave produce Presentation2] [FortCollins geoContains MyHouse] (About or descriptive) (GenericAssociations) [Message1 fromAgent Dave] [ThisBookabout Lincoln]

9. Coverage

10. Coverage

11. Coverage • An Enterprise Ontology we built recently contained 600 classes • All but 2 were derived from or defined in terms of gist

12. Unambiguous • Almost all these high level concepts are disjoint • Which means classes derived from them also cannot have overlapping/ ambiguous membership • This helps ontologists make some difficult but necessary decisions as they map their domain into the common

13. Unambiguous ? BankAccount GLAccount Account

14. Specific • gist itself and the classes derived from it have rigorous definitions

15. Modular (Each ontology is “human scale” ) gist Gist2/3 SM R&D FEI Div1 Div2

16. UnitOfMeasure Magnitude Fractal (as you “zoom in” more detail is revealed) Collections Concepts Time Place Landmark Person/UniqueItem Substance Organization Documents Agreements Behavior Intention

17. Fractal (as you “zoom in” more detail is revealed)

18. Fractal (as you “zoom in” more detail is revealed)

19. UnitOfMeasure Magnitude Cooks Tour Collections Concepts Time Place Landmark Person/UniqueItem Substance Organization Documents Agreements Behavior Intention

20. ‘avago

22. Your examples

23. Summary • Semantic Integration is going to be greatly aided by having an intermediary that is: • Simple, to promote adoption • Broad enough to cover most of the concepts • Unambiguous to prevent promoting vagueness • Rigorous in its specification • Modular to allow mix and match • Fractal to allow people to understand it by degree www.semanticarts.com/gist Documentation ontologies.semanticarts.com/gist/gist.owl Ontology

24. Semantic Arts Clients

25. Semantic Arts Scope of Work • We work with large organizations • To help them reduce complexity and remove costs from their enterprise applications and architecture • We specialize in: • Enterprise Architecture and SOA • Application of Semantic Technology • Building Enterprise Ontologies • Semantic MDM

26. Contact Dave McComb mccomb@semanticarts.com (970) 490-2224 www.semanticarts.com Twitter @semanticarts