1. Automating Instance Migration in Response to Ontology Evolution Mark Fischer – Queen’s Juergen Dingel – Queen’s Maged Elaasar – Carleton Steven Shaw – IBM

2. Agenda  Overview  Approach  Comparing Two Ontologies  Creating a Transformation  Oital  Analyzing a Transformation  Case Study  Future Work  Conclusion MODELS 2013 Workshop2

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. MODELS 2013 Workshop3

4. Overview  Developed:  Automated: MODELS 2013 Workshop4

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 MODELS 2013 Workshop5

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 MODELS 2013 Workshop6

7. Comparing Two Ontologies MODELS 2013 Workshop7

8. Comparing Two Ontologies: Original MODELS 2013 Workshop8

9. Comparing Two Ontologies: Updated MODELS 2013 Workshop9

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 MODELS 2013 Workshop10

11. Oital  An Oital transformation consists of:  Actions which delete or create individuals and their properties  TransformationClasses which define a category of individual based off of a query  The order of actions does matter  TransformationClasses change depending on their context MODELS 2013 Workshop11

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? MODELS 2013 Workshop12

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 MODELS 2013 Workshop13

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 MODELS 2013 Workshop14

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 MODELS 2013 Workshop15

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. MODELS 2013 Workshop16

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.  Asad Masood Khattak, 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. MODELS 2013 Workshop17