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Automating Instance Migration in Response to Ontology Evolution

Automating Instance Migration in Response to Ontology Evolution. Mark Fischer – Queen’s Juergen Dingel – Queen’s Maged Elaasar – Carleton Steven Shaw – IBM. Agenda. Overview Approach Comparing Two Ontologies Creating a Transformation Oital

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Automating Instance Migration in Response to Ontology Evolution

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  1. Automating Instance Migration in Response to Ontology Evolution Mark Fischer – Queen’s JuergenDingel– Queen’s MagedElaasar – Carleton Steven Shaw – IBM

  2. Agenda • Overview • Approach • Comparing Two Ontologies • Creating a Transformation • Oital • Analyzing a Transformation • Case Study • Future Work • Conclusion

  3. Overview • Migration • Move individuals from one ontology to another. • Motivation • This setup reflects the way IBM’s Design Management tool stores models as Ontologies.

  4. Overview • Developed: • Automated:

  5. Approach • We let the Migration be performed via a Transformation • Creating this transformation is hard. • Add steps to make it easier • What would help? • Some way of comparing two ontologies • An easy way to write a transformation • Ways to test/analyze transformations for correctness

  6. Comparing Two Ontologies • There are many competing ways to compare ontologies • For creating these sorts of transformations, only those parts of an ontology that may effect individuals are of any interest. • We are interested in Axioms • For any axiom, C, the axiom and all other axioms it is influenced by is called the context of C

  7. Comparing Two Ontologies

  8. Comparing Two Ontologies: Original

  9. Comparing Two Ontologies: Updated

  10. Creating a Transformation • Use domain-specific language • We created Oital • About Oital • Syntax based off of the Manchester Owl syntax • Becomes a form of documentation • Has an integrated development environment called Oital-T

  11. Oital • An Oital transformation consists of: • Actions which delete or create individuals and their properties • TransformationClasseswhich define a category of individual based off of a query • The order of actions does matter • TransformationClasses change depending on their context

  12. Analyzing a Transformation • We currently support a form of Abstract Interpretation • How does it help? • Lets you isolate specific properties of the input and output of a transformation • Example: Abstract Interpretation of Class Membership can answer the following questions • Does every individual which is a member of a removed class get migrated so that it is a member of an existing class? • Which classes are guaranteed to have no individuals? • Are individuals being migrated into more restrictive classes?

  13. Case Study • Use IBM’s Ontology encoding of UML 2.1.1, UML 2.2, and UML 2.4.1 to recreate their migration using this approach. • UML 2.4.1 has: • 255 Named Classes • 801 Anonymous Classes (enumerated, union, complement, intersection, restriction) • 594 properties • Comparing UML 2.1.1 and UML 2.2: • # of must investigate axioms: 38 • # of should investigate axioms: 118 • # of ok axioms: 4361

  14. When to use this approach • It is often faster to migrate manually • Transformation are general and can make no assumptions about any specific set of individuals • When does this approach make most sense? • When ontology developers and users are different people. • When there are many users (applications) using the evolving ontology • When there is no way of predicting how an ontology will be used

  15. Future Work • More analysis! • Abstract interpretation isn’t the only helpful form of analysis possible. • Continue development on Oital-T • Discover usage patterns for Oital • Integrate them into the language or tool to insure ease of use. • Case study. • Continue with IBM UML case study

  16. Conclusion • Of great importance to the efficient use of an ontology is the ability to easily effect change. • The approach described here facilitates a way of keeping certain types of ontological artifacts up to date in a way that is, potentially, very scalable.

  17. References • Natalya F. Noy and Michel Klein. Ontology evolution: Not the same as schema evolution. Knowledge and Information Systems, 6(4):428–440. • Peter Plessers, Olga De Troyer, and Sven Casteleyn. Understanding ontology evolution: A change detection approach. Web Semantics: Science, Services and Agents on the World Wide Web, 5(1):39–49, 2007. • AsadMasoodKhattak, Zeeshan Pervez, Sungyoung Lee, and Young-Koo Lee. After effects of ontology evolution. 5th International Conference on Future Information Technology. IEEE, 2010. • Matthew Horridge and Peter F. Patel-Schneider. OWL 2 Web Ontology Language Manchester Syntax. W3C Working Group Note. Dec 11, 2012. • Sean Bechhofer, Frank van Harmelen, Jim Hendler, Ian Horrocks, Deborah L. McGuinness, Peter F. Patel-Schneider, and Lynn Andrea Stein. Owl web ontology language reference. February 2004.

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