1. Re-learning Ontology Management for the Web Chris Welty IBM Research

2. Web-based Ontologies The symbols in the ontology are URIs The meaning of the ontology is distributed around the web The entire ontology may not always be accessible

3. The Web enables… Searching for, ranking ontologies –But not based on meaning

4. Searching, Ranking, & Quality Does quality matter? Good quality ontologies cost more –Coverage, correctness, richness, commitment [Kashyap, 2003] –Organization, meta-level consistency [Guarino & Welty, 2000] [Rector, 2002] –Required for some applications Improvements in quality can improve performance [Welty, et al, 2004] –18% f-improvement in search –Cleanup cost ~1mw/3000 classes –BUT … low quality ontology still improved base But to rank quality, it needs to be measured…

5. The Web enables… Searching for, ranking ontologies –But not based on meaning or quality Selection, Reuse of ontologies –Including misuse Partitioning ontologies –Reusing parts of an ontology … A problem looms

6. AT&T Definity System (c. 1992) 20,000,000 lines of C code 1,000 programmers High turnover –25% less than 1 year experience –75% less than 5 High reliability requirement –1 min/year –Handle Mothers day call volume 6+ dimensions of versioning –Country, Language, Major Rev, Minor Rev, Patchlevel, Feature set Sales force lack knowledge of cost Huge maintenance problem

7. Modern SE Packaged components available on the web The dream of reuse being realized For large projects, the nightmare of reuse being realized –n-dimensions of versioning Still, largely w/in control –Can choose when to include the latest jar

8. The Web Ontology Analogy Packaged components available on the web The dream of reuse being realized For large projects, the nightmare of reuse being realized –n-dimensions of versioning If using imports –CanNOT choose when to include the latest

9. owl:Ontology & Namespaces No Semantics –In a real sense, not part of the language –Imports, versioning What is an ontology? Not packaging mechanisms –Yet used that way

10. Imports for Layering Upper Ontology OWL-Time Fluents Ontology EventsObjects App-specific view

11. Imports for Language Levels RDFS- Axioms OWL-DL Axioms OWL-Full Axioms

12. Key Observation OWL&RDF are axiom-based languages –not frame-based or object-oriented The definition of a class or property is not in one place (despite some tools) (Class cdo:CarsDomainObject) (Class cdo:Car partial cdo:CarsDomainObject) (Class rdo:RacingDomainObject (Class cdo:Car partial rdo:CarsDomainObject)

13. Separating axioms by language (Class RigidClass partial (restriction oc:subClassOf allValuesFrom (complementOf(AntiRigidClass))) (Class NonRigidClass partial) (disjointClasses RigidClass NonRigidClass) (rdfs:subClassOf RigidClass owl:Class) (rdfs:subClassOf NonRigidClass owl:Class) (sameAs oc:subClassOf rdfs:subClassOf) (RigidClass cdo:Car)

14. The Dark Side (Class oc:RigidClass partial restriction oc:subClassOf allValuesFrom complementOf(oc:AntiRigidClass)) (Class oc:NonRigidClass partial) (disjointClasses oc:RigidClass oc:NonRigidClass) (Class oc:RigidClass partial oc:nonRigidClass) What does it mean?????

15. Wherefore Reasoning? Glorified Compiler Build a taxonomy [Rector] … The user community is still unsure what the purpose of reasoning is

16. A looming problem Prediction –Ontology maintenance will become the significant problem as ontologies become more mainstream –Will follow the SE model (80% of cost) Observation/Conjecture –High quality ontologies are easier to maintain

17. Software Maintenance Fixing Bugs Testing Enhancing

18. Ontology Maintenance Fixing Bugs –Inconsistent –Inaccurate –Inefficient Testing –Regression tests –Test Suites –Meta tag sets for test content –Ablation tests Enhancing –Tweaking Richness Correctness Organization Meta-level consistency Efficiency –Extending Improving coverage Extending commitment Integration –Refactoring

19. Of Chickens and Eggs Many other fields focus on large information artifacts –DB, DL, SE Other fields of information processing have hit a wall –IR, NLP, semantic integration Guess where theyre looking for help?

20. As ontologies become the cornerstone of more and more web applications, what little experience the community has with managing ontologies needs to be re-learned, because elements of semantic web technology that seemed at first quite trivial turn out to have significant impact on the process. In this talk I will discuss these issues and their impact, and propose a straw-man ontology management life- cycle that includes search, selection & ranking, partitioning, re-use & imports, and versioning & change management, among others.

21. Background Software Management Knowledge Management Document Management Management

22. Life-Cycle Create & Debug Modify

23. Requirements Engineering Model the stakeholders Model the domain Model the system … need ontologies

24. Software Engineering KIDS & SpecWare –Model the software

25. OSS Development Similar in size, scope Highly distributed workforce Generally high expertise level of contributors

26. OWL Imports Referencing elements of other Ontologies –Named Classes, Properties, Individuals –What do they mean when referenced?

27. OWL & RDF: axiom-based Frame-based & object oriented tools –Put a face on OWL & RDF that is insincere

28. Vocabulary A part of an ontology? Less semantics?