Evolution in OWL 2 QL & OWL 2 EL Ontologies

1. Evolution in OWL 2 QL & OWL 2 EL Ontologies Dmitriy Zheleznyakov 28thof January, 2014, Oslo

2. Ontology General rules: • To use ontologies in applications,we need special, formal syntax  All popes are clerics Facts: Benedict XVI is a pope

3. Explicit knowledge Ontology • Do ontologies differ from data bases? • Data bases: explicit knowledge only • Benedict XVI is a pope • Ontologies: explicit & implicit knowledge • Benedict XVI is a pope • Reasoning:Benedict XVI is a cleric Explicit knowledge Implicit knowledge reasoning

4. Ontology Languages • The focus of this work: ontology languages for the Semantic Web • Web Ontology Language: OWL 2 (W3C Standard) • OWL 2 QL • OWL 2 EL • Good computational properties • Efficient schema and data management • Used in practice

5. OWL 2 QL: Ontology-Based Data Access • Ontology-Based Data Access (OBDA) • provide unified query interface to heterogeneous data sources

6. OWL 2 QL: Ontology-Based Data Access • Ontology-Based Data Access (OBDA) • provide unified query interface to heterogeneous data sources • EU FP7 project Optiquewill developan OBDA system • use-case partners: Statoil, Siemens • Ontologies may change: • new knowledge about domain • new data source is added • Motivation for our work: • to address the dynamicity of OBDA systemsby studying evolution of schema and data

7. OWL 2 EL: Clinical Science, Bio Ontologies • Ontologies enable communication and knowledge sharingbetween doctors, scientists, etc. • SNOMED CT: > 311k terms • constantly under development: • 5 modification teams • every 2 weeks the main team integrates changes, • 2002  2008 SNOMED went 278k  311k terms • It is the standard to describe the results of experiments in the US clinical labs • Motivation for our work: • to provide techniques that facilitate ontology development for such a vast community

8. Our Goal • To facilitate evolution of ontology-based systems • insertion of knowledge • deletion of knowledge • On two levels: • schema • data • With as little changesas possible Original ontology To insert To delete

9. How to Approach the Problem? • Define anoperator and understand it • a conceptual understanding of how to evolve ontologies • checking its computational properties • Develop an algorithm to compute the result • Implement the algorithm Original ontology New knowledge Resulting ontology

10. Previous Work Model-based operators Formula-based operators Many evolution operators proposed Adaptationof some operators [AGM’85] [Borgida’85] [Dalal’88] [Satoh’88] [Winslett’90] [Kang&Lau’04] [Flouris&al’04] [Flouris&al’05] [Qi&al’06] [Liu& al’06] [Qi&Du’09] [DeGiacomo&al’07-09] [Wang&al’10] [Winslett’88] [Katsuno&Mendelzon’91] AI: 80’s – 90’s Propositional logic, weaker then OWL 2 QL & OWL 2 EL KR: 2004-2006 2007-2010

11. General Overview of the Results Work for restriction of OWL 2 QL • For OWL 2 QL & EL • inexpressibility • counterintuitive results OWL 2 QLOWL 2 EL 1 2 3 Model-based operators Tunableoperator Boldoperator • inexpressibility • counterintuitive results Works for OWL 2 QL & EL Works for OWL 2 QL 6 Formula-based operators 4 5 Propositionallogic OWL 2 QL OWL 2 EL

12. Understanding Model-Based Operators Work for restriction of OWL 2 QL 1 2 3 Model-based operators Boldoperator Tunableoperator Works for OWL 2 QL & EL Works for OWL 2 QL 6 Formula-based operators 4 5 Propositionallogic OWL 2 QL OWL 2 EL

13. Understanding Model-Based Operators • We have shown: operators are determined by three parameters • this gives a three-dimensional spaceof operators • Classical operators fit in this space • Novel operators can be easily definedby changing parameters

14. Understanding Model-Based Operators • We noticed: operators are determined by three parameters • this gives a three-dimensional spaceof operators • Classical operators fit in this space • Novel operators can be easily definedby changing parameters • We can add new values to dimensions! • more operators can be defined!

15. Inexpressibility of Model-Based Operators Work for restriction of OWL 2 QL • inexpressibility • counterintuitive results 1 2 3 Model-based operators Tunableoperator Boldoperator Works for OWL 2 QL & EL Works for OWL 2 QL 6 Formula-based operators 4 5 Propositionallogic OWL 2 QL OWL 2 EL

16. Inexpressibility of Model-Based Operators Schema: Wives are married to their husbands Priest cannot be husbands Facts: Mary is married to John and Adam and Bob are priests

17. Inexpressibility of Model-Based Operators a model: Under model-based operators:We incorporate new knowledge directly into models Facts to add: John is a priest

18. Inexpressibility of Model-Based Operators 1. John cannot be a husband of Mary anymore! What happens to her? 2. Three options: She divorced She married some one else She married to a former priest 3.

19. Inexpressibility of Model-Based Operators 1. OR We showed: all these options cannot be capturedin OWL 2 QL and OWL 2 EL We need at least disjunction which is not in OWL 2 QL and OWL 2 EL 2. OR 3.

20. Bad Behaviour of Model-Based Operators Work for restriction of OWL 2 QL • inexpressibility • counterintuitive results 1 2 3 Model-based operators Boldoperator Tunableoperator Works for OWL 2 QL & EL Works for OWL 2 QL 6 Formula-based operators 4 5 Propositionallogic OWL 2 QL OWL 2 EL

21. Bad Behaviour of Model-Based Operators Some of model-based operators behave as follows: No schema Facts: Adam and Bob are priests Facts to add: John is a priest

22. Bad Behaviour of Model-Based Operators Some of model-based operators behave as follows: Such behaviour is not usefulfor any application Expectedresult: Actualresult:

23. Restriction of OWL 2 QL Work for restriction of OWL 2 QL 1 2 3 Model-based operators Boldoperator Tunableoperator Works for OWL 2 QL & EL Works for OWL 2 QL 6 Formula-based operators 4 5 Propositionallogic OWL 2 QL OWL 2 EL

24. Restriction of OWL 2 QL • We found the reason of the bad behaviour of model-base operators: A binary relation participates in disjointness • Priest cannot be husbands • What if we forbid this bad interaction? • We showed: most of model-based operators work! • this fragment captures (FO part of) RDFS(another W3C standard) disjoint with

25. Summing up on Model-Based Operators • Model-based operators • suffer from inexpressibility • tend to lose too much of information • counterintuitivebehaviour • Our verdict: • model-based operators are not suitable for the case of OWL 2 QL or OWL 2 EL • We turned to Formula-based operators!

26. Formula-Based Operators Work for restriction of OWL 2 QL 1 2 3 Model-based operators Boldoperator Tunableoperator • inexpressibility • counterintuitive results Works for OWL 2 QL & EL Works for OWL 2 QL 6 Formula-based operators 4 5 Propositionallogic OWL 2 QL OWL 2 EL

27. Formula-Based Operators • Preserve all the knowledge:both explicit and implicit • Example: delete Priests are Males • We do not want to lose info thatAdam is Male Explicit schema Implicitschema Explicit data Implicitdata

28. Formula-Based Operators • Preserve all the knowledge:both explicit and implicit • Example: delete Priests are Males • How to delete it in such a way that it will not appear even implicitly? • Delete • either Priests are Clerics • or Clerics are Males Explicit schema Implicitschema

29. Formula-Based Operators • Preserve all the knowledge:both explicit and implicit • Example: delete Priests are Males • How to delete it in such a way that it will not appear even implicitly? • Delete • either Priests are Clerics • or Clerics are Males • What to do with a multiple choice?Classical approaches: • Keeping both – impossible • Combining them • too much of information is lost • we proved: it is computationally hard The resulted schema: either or

30. Bold Operator Work for restriction of OWL 2 QL 1 2 3 Model-based operators Tunableoperator Boldoperator Works for OWL 2 QL & EL Works for OWL 2 QL 6 Formula-based operators 4 5 Propositionallogic OWL 2 QL OWL 2 EL

31. Bold Operator There is no way to decide which result is better! This is application dependentand should be up to the user • Example: delete Priests are Males • How to delete it in such a way that it will not appear even implicitly? • Delete • either Priests are Clerics • or Clerics are Males • What to do with a multiple choice? • We propose: Bold operator.It picks up one of them • The result is non-deterministic… • … But can be computed in polynomial time (for OWL 2 QL) • In the case of OWL 2 EL: • Implicit knowledge can be infinite • Bold operator does not work The resulted schema: either or

32. Tunable Operator Work for restriction of OWL 2 QL 1 2 3 Model-based operators Boldoperator Tunableoperator Works for OWL 2 QL & EL Works for OWL 2 QL 6 Formula-based operators 4 5 Propositionallogic OWL 2 QL OWL 2 EL

33. Tunable Operator • Tunable operator • allows to choose what part of implicit knowledge will be preserved Explicit schema Implicitschema

34. Tunable Operator • Tunable operator • allows to choose what part of implicit knowledge will be preserved Explicit schema Implicitschema

35. Tunable Operator No implicit part Whole implicit part

36. Summing up on Formula-Based Operators • Classical Formula-based operators • suffer from inexpressibility • tend to lose too much of information • Bold operator: • works for OWL 2 QL • fails for OWL 2 EL • Tunable operator: • works for both OWL 2 QL and OWL 2 EL

37. Current Work • Applying our results to the Optique project • in progress • Incorporating evolution in transition systems • IJCAI’2013 • Information hiding & Controlled query evaluation • ISWC 2013 • submitted to an international conference