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

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

3. 2 Ontology Explicit knowledge o Do ontologies differ from data bases? o Data bases: explicit knowledge only o Benedict XVI is a pope o Ontologies: explicit & implicit knowledge o Benedict XVI is a pope o Reasoning: Benedict XVI is a cleric reasoning Explicit knowledgeImplicit knowledge

4. o The focus of this work: ontology languages for the Semantic Web o Web Ontology Language: OWL 2 (W3C Standard) o OWL 2 QL o OWL 2 EL o Good computational properties o Efficient schema and data management o Used in practice 3 Ontology Languages

5. o Ontology-Based Data Access (OBDA) o provide unified query interface to heterogeneous data sources 4 OWL 2 QL: Ontology-Based Data Access

6. o Ontology-Based Data Access (OBDA) o provide unified query interface to heterogeneous data sources o EU FP7 project Optique will develop an OBDA system o use-case partners: Statoil, Siemens o Ontologies may change: o new knowledge about domain o new data source is added o Motivation for our work: o to address the dynamicity of OBDA systems by studying evolution of schema and data 4 OWL 2 QL: Ontology-Based Data Access

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

8. o To facilitate evolution of ontology-based systems o insertion of knowledge o deletion of knowledge o On two levels: o schema o data o With as little changes as possible 6 Our Goal Original ontology To insert To delete

9. 7 How to Approach the Problem? Original ontologyNew knowledge Resulting ontology 1.Define an operator and understand it a conceptual understanding of how to evolve ontologies checking its computational properties 2.Develop an algorithm to compute the result 3.Implement the algorithm

10. 8 Previous Work AI: 80’s – 90’s Propositional logic, weaker then OWL 2 QL & OWL 2 EL KR: 2004-20062007-2010 [AGM’85] [Borgida’85] [Dalal’88] [Satoh’88] [Winslett’90] Many evolution operators proposed [Winslett’88] [Katsuno&Mendelzon’91] Model-based operators Formula-based operators [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] Adaptation of some operators

11. 9 Model-based operators Formula-based operators General Overview of the Results OWL 2 QL OWL 2 EL Work for restriction of OWL 2 QL Propositional logic OWL 2 QL OWL 2 EL For OWL 2 QL & EL -inexpressibility -counterintuitive results -inexpressibility -counterintuitive results Works for OWL 2 QL Bold operator Works for OWL 2 QL & EL Tunable operator

12. Works for OWL 2 QL Bold operator Works for OWL 2 QL & EL Tunable operator Model-based operators Formula-based operators Understanding Model-Based Operators Work for restriction of OWL 2 QL Propositional logic 10 OWL 2 QL OWL 2 EL

13. 11 Understanding Model-Based Operators o We have shown: operators are determined by three parameters o this gives a three-dimensional space of operators o Classical operators fit in this space o Novel operators can be easily defined by changing parameters

14. 11 Understanding Model-Based Operators o We noticed: operators are determined by three parameters o this gives a three-dimensional space of operators o Classical operators fit in this space o Novel operators can be easily defined by changing parameters o We can add new values to dimensions! o more operators can be defined!

15. Works for OWL 2 QL Bold operator Works for OWL 2 QL & EL Tunable operator Model-based operators Formula-based operators Inexpressibility of Model-Based Operators Work for restriction of OWL 2 QL Propositional logic 12 -inexpressibility -counterintuitive results OWL 2 QL OWL 2 EL

16. 13 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. 13 Inexpressibility of Model-Based Operators Priest Adam Bob MaryJohn hasHusband Facts to add: John is a priest Under model-based operators: We incorporate new knowledge directly into models a model:

18. 13 Inexpressibility of Model-Based Operators Priest Adam Bob MaryJohn hasHusband John cannot be a husband of Mary anymore! What happens to her? Three options: 1.She divorced 2.She married some one else 3.She married to a former priest Priest Adam Bob John hasHusband 1.1. Priest Adam Bob John MaryJack hasHusband 2. Priest Adam John MaryBob hasHusband 3.

19. 13 Inexpressibility of Model-Based Operators We showed: all these options cannot be captured in OWL 2 QL and OWL 2 EL We need at least disjunction which is not in OWL 2 QL and OWL 2 EL Priest Adam Bob John hasHusband 1.1. Priest Adam Bob John MaryJack hasHusband 2. Priest Adam John MaryBob hasHusband 3. OR Priest Adam Bob MaryJohn hasHusband

20. Works for OWL 2 QL Bold operator Works for OWL 2 QL & EL Tunable operator Model-based operators Formula-based operators Bad Behaviour of Model-Based Operators Work for restriction of OWL 2 QL Propositional logic OWL 2 QL OWL 2 EL 14 -inexpressibility -counterintuitive results

21. 15 Bad Behaviour of Model-Based Operators Facts: Adam and Bob are priests Facts to add: John is a priest No schema Some of model-based operators behave as follows:

22. 15 Bad Behaviour of Model-Based Operators Priest Adam Bob Priest Adam Bob John Expected result: Priest John Actual result: Such behaviour is not useful for any application Some of model-based operators behave as follows:

23. Works for OWL 2 QL Bold operator Works for OWL 2 QL & EL Tunable operator Model-based operators Formula-based operators Restriction of OWL 2 QL Propositional logic OWL 2 QL OWL 2 EL 16 Work for restriction of OWL 2 QL

24. 17 Restriction of OWL 2 QL o We found the reason of the bad behaviour of model-base operators: A binary relation participates in disjointness o Priest cannot be husbands o What if we forbid this bad interaction? o We showed: most of model-based operators work! o this fragment captures (FO part of) RDFS (another W3C standard) Priest Adam Bob MaryJohn hasHusband disjoint with

25. 18 Summing up on Model-Based Operators o Model-based operators o suffer from inexpressibility o tend to lose too much of information o counterintuitive behaviour o Our verdict: o model-based operators are not suitable for the case of OWL 2 QL or OWL 2 EL o We turned to Formula-based operators!

26. Works for OWL 2 QL Bold operator Works for OWL 2 QL & EL Tunable operator Model-based operators Formula-Based Operators Propositional logic OWL 2 QL OWL 2 EL 19 Formula-based operators Work for restriction of OWL 2 QL -inexpressibility -counterintuitive results

27. 20 Formula-Based Operators Explicit schema Implicit schema o Preserve all the knowledge: both explicit and implicit o Example: delete Priests are Males o We do not want to lose info that Adam is Male Explicit data Implicit data

28. 20 Formula-Based Operators Explicit schema Implicit schema o Preserve all the knowledge: both explicit and implicit o Example: delete Priests are Males o How to delete it in such a way that it will not appear even implicitly? o Delete o either Priests are Clerics o or Clerics are Males

29. 20 Formula-Based Operators o Preserve all the knowledge: both explicit and implicit o Example: delete Priests are Males o How to delete it in such a way that it will not appear even implicitly? o Delete o either Priests are Clerics o or Clerics are Males o What to do with a multiple choice? Classical approaches: o Keeping both – impossible o Combining them o too much of information is lost o we proved: it is computationally hard The resulted schema: either or

30. Works for OWL 2 QL & EL Tunable operator Formula-based operators Model-based operators Bold Operator Propositional logic OWL 2 QL OWL 2 EL 21 Work for restriction of OWL 2 QL Works for OWL 2 QL Bold operator

31. 22 Bold Operator o Example: delete Priests are Males o How to delete it in such a way that it will not appear even implicitly? o Delete o either Priests are Clerics o or Clerics are Males

32. 22 Bold Operator o Example: delete Priests are Males o How to delete it in such a way that it will not appear even implicitly? o Delete o either Priests are Clerics o or Clerics are Males o What to do with a multiple choice? o We propose: Bold operator. It picks up one of them o The result is non-deterministic… o … But can be computed in polynomial time (for OWL 2 QL) o In the case of OWL 2 EL: o Implicit knowledge can be infinite o Bold operator does not work The resulted schema: either or There is no way to decide which result is better! This is application dependent and should be up to the user

33. Formula-based operators Model-based operators Tunable Operator Propositional logic OWL 2 QL OWL 2 EL 23 Work for restriction of OWL 2 QL Works for OWL 2 QL Bold operator Works for OWL 2 QL & EL Tunable operator

34. 24 Tunable Operator Explicit schema Implicit schema o Tunable operator o allows to choose what part of implicit knowledge will be preserved

35. 24 Tunable Operator o Tunable operator o allows to choose what part of implicit knowledge will be preserved Explicit schema Implicit schema

36. 25 Tunable Operator No implicit part Whole implicit part

37. 26 Summing up on Formula-Based Operators o Classical Formula-based operators o suffer from inexpressibility o tend to lose too much of information o Bold operator: o works for OWL 2 QL o fails for OWL 2 EL o Tunable operator: o works for both OWL 2 QL and OWL 2 EL

38. 27 Current Work o Applying our results to the Optique project o in progress o Incorporating evolution in transition systems o IJCAI’2013 o Information hiding & Controlled query evaluation o ISWC 2013 o submitted to an international conference