SCOOP - System For Collaborative Open Ontology Production

1. SCOOP - System For Collaborative Open Ontology Production “A Knowledge Management tool that understands the content it manages.” AAAI-SSS AMKM 26 March 2003 Adam Pease, John Li Teknowledge [apease | jli]@teknowledge.com http://projects.teknowledge.com/RKF http://ontology.teknowledge.com

2. System Overview GUI Language Interface Simple Workflow Theorem Prover Formal Ontology

3. Problem Addressed • Developers need to know whether they • Share content with other developers • Conflict with other developers’ content

4. What’s New • Using theorem-proving to maintain consistency among KEs/SMEs • Vertical Consistency – consistency among theories used by a single developer • Horizontal Consistency – consistency among theories created by several developers • Building on existing SCOOP workflow, coordination and voting support

5. Consistency Support • Redundancy results in warnings • Redundacy among developers triggers suggestion for statement lifting • Lifting results in redundant statement being moved to a common file/theory • Contradiction results in errors • Users must retract contradiction among his own files/theories • Users may keep contradictions with respect to other developer’s files, at the price of prohibiting further diagnostics with respect to those files

6. Voting • Majority vote • Author’s vote is a tie-breaker • Other weighted voting schemes easily adopted

7. Text Documents English Statements Structured Sources Structured Dialogs Candidate Inferences/ Statements FOL Dimensions of Knowledge Person/Source/Domain KnowledgeModules KnowledgeCompartments Formality KnowledgeVersions Time

8. Benefits of history • Regression to earlier versions • problematic content can be removed and the system returned to an earlier state • Change tracking • track the evolution of system components • understand why things were done • understand how system must be modified to support other changes

9. System Overview GUI Language Interface Simple Workflow Theorem Prover Formal Ontology

10. SUMO • Incorporates over 50 publicly available sources of high-level ontological content • Available in KIF (first order logic), DAML and LOOM • May be used without fee for any purpose (including for profit) • Refined extensively on the basis of input from SUO mailing list participants • Mapped by hand to all 100,000 WordNet synsets • 47 publicly released versions created over two years (approximately 1,000 concepts, 4000 assertions, and 750 rules so far)

11. What’s in the SUMO? • Structural Ontology • Set/Class Theory • Number Hierarchy • Quantities and Units of Measure • Biological Taxonomy • Temporal Concepts • Mereotopology

12. SUMO Structure Structural Ontology Base Ontology Set/Class Theory Numeric Temporal Mereotopology Graph Measure Processes Objects Qualities

13. SUMO Sources • Ontolingua ontologies • component-assemblies - Gruber and Olsen • product-ontology - Fikes • physical-quantities - Brauch • scalar-quantities - Gruber and Olsen • unary-scalar-functions - Gruber and Olsen • abstract-algebra authored - Genesereth, Gruber and Olsen • kif-extensions • kif-relations • kif-sets • frame-ontology - Mribiere • okbc-ontology - Xpetard • Standard Dimensions - U Madrid, Spain • Simple-Time - Mribiere • Standard-Units - Loeser + Pinto • Agents - Arnaoudova • KIF-Numbers • Allen - temporal ontology • Pease - Core Plan Representation • Borgo, Guarino, and Masolo's - Formal Theory of Physical Objects • Casati and Varzi - Theory of Holes • Level – verb taxonomy • Russell and Norvig - upper ontology • Smith - Formal Theory of Fiat/Bona Fide Boundaries/Objects • Sowa - upper ontology • Whitten - Starter KB • PSL • Enterprise Ontology • ITBM-CNR ontologies • Unrestricted-Time • Representation • Anatomy • Biologic-Functions • Biologic-Substances • topics • meronymy • topology • topo-morphology • localization • assessment • structuring-concepts • physical-concepts • top-level • social-objects • Quantities • Actors • Positions • Natural-Kinds

14. Domain Specific Ontologies • Finance and investment • Real Estate • Terrain features • Computers and Networks (Quality of Service) • Periodic table of elements • North American Industrial Coding System • ECommerce services • Terrorism and Weapons of Mass Destruction • Air force planning and operations • Army planning • Ontologies developed outside Teknowledge • Biological viruses • Intellectual property • Linguistic elements

15. System Overview GUI Language Interface Simple Workflow Theorem Prover Formal Ontology

16. Simple Language Example • "The dog bites the man" • Shows both simple noun mappings and a simple verb mapping (exists (?D ?M ?E) (and (instance ?E Biting) (instance ?D Canine) (instance ?M MalePerson) (agent ?E ?D) (patient ?E ?M))) There exists a biting event, a canine and a male person such that the canine is the agent of the biting and the male person is the patient of the biting. d,m,e : Biting(e)  Canine(d)  MalePerson(m)  agent(e,d)  patient (e,m)

17. System Overview GUI Language Interface Simple Workflow Theorem Prover Formal Ontology

18. Simple Language Generation • Term translation • Relation templates • Use C-like printf statements • Result is awkward but usually grammatical • Preserves deep meaning • English (Sevcenko), German (Wulf), Czech (Sevcenko), Italian (Ulivieri & Molino) • Hindi, Telugu, Tagalog, Chinese, Russian in progress

19. Plans • Problem resolution heuristics - Knowing which statement to retract • Metrics for statement use • Statement assertion recency • User weighting • Proof summarization • Tree-based visibility selection, hide transformations with one premise • Hardening • Improved control panel • Testing • Installation packaging

20. Plans • Scaleup • How to handle 10 users, 100 users • Coordination techniques change • Refine the agenda • Avoid deadlock • Hierarchical conflict detection • Misc • Better voting tabulation • Pluggable voting policy • Inference-based relevance searching