Ontology evolution under semantic constraints
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Ontology Evolution Under Semantic Constraints. Bernardo Cuenca Grau , Ernesto Jiménez-Ruiz Computer Science Department, University of Oxford Evgeny Kharlamov, Dmitriy Zheleznyakov KRDB research centre , Free University of Bozen -Bolzano KR 2012, Rome. Ontologies: schema + data.

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Ontology Evolution Under Semantic Constraints

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Ontology evolution under semantic constraints

Ontology EvolutionUnder Semantic Constraints

Bernardo Cuenca Grau, Ernesto Jiménez-RuizComputer Science Department, University of Oxford

Evgeny Kharlamov, DmitriyZheleznyakovKRDB research centre, Free University of Bozen-Bolzano

KR 2012, Rome


Ontologies schema data

Ontologies: schema + data

  • Schema provide

    • standard vocabularies for data

      • classes (concepts)

      • properties (roles)

    • a way to structure data

    • means for machines to be able to understand data

  • Data is a collections of facts

    • Instantiations of classes

    • Instantiations of properties


Domain ontologies

Domain Ontologies

  • Goal: to provide standard vocabularies to communities

  • Clinical sciencesontologies:

    • SNOMED CT: Systematized Nomenclature of Medicine - Clinical Terms

      • > 311k concepts

    • NCIt: National CancerInstitute thesaurus

      • ~ 89k concepts, 200m cross links between them [NCI]

    • FMA: Foundational Model of Anatomy

      • 75k classes, 168k relations, 120k terms, 3.1m relat. inst.


Evolution of domain ontologies

Evolution of Domain Ontologies

  • Evolution of SNOMED:

    • 5 geographically distributed teams making modifications

    • every 2 weeks the main team integrates changes, resolves conflicts

    • from 2002 to 2008 SNOMED went from 278k to 311k concepts [SM-1]

  • Evolution of NCIt:

    • 20 full time editors for NCI

    • Developers of NCI do over 900 monthly changes [HKR’08]

  • Evolution of FMA:

    • FMA “is an evolving computer-based knowledge source ...” [FMA]


Evolution of domain ontologies1

Evolution of Domain Ontologies

  • At the high level ontologies are changed by

    • addition of information

      • usually referred as revision or update

    • deletion of information

      • usually referred as contraction

  • Evolution may affect both

    • schema level

    • data level

  • A natural requirement: principle of minimal change;

    changes should minimally affect ontology

    • structure

    • semantics


Languages for domain o ntologies

Languages for Domain Ontologies

  • Evolution of ontologies is a classical problem in KR

    • intensively studied for propositional logic

      • there are different semantics for evolution

      • many complexity results

    • very few results beyond “propositional paradise”

  • Ontology Web Language: OWL 2 – W3C standard

    • OWL 2 (based on SROIQ)

    • OWL 2 QL (based on DL-Lite)

    • OWL 2 EL (based on EL, EL++)

      • e.g. SNOMED

these are not propositional


Basic dls el fl 0

Basic DLs EL & FL0


Outline

Outline

  • Existing approaches to evolution

    • Syntactic approach

    • Deductive approach

  • Our approach: evolution under constraints

  • Conclusion & directions


Sa evolution process

SA: Evolution Process

  • add/delete

  • minimal change(syntactic)

processing

  • ontologyin L

  • evolvedontologyin L

  • operator

  • newinfo

either axioms to add

or axioms to delete

E.g., contraction operator: takes a maximal subset (w.r.t. set inclusion) of the original ontology which does not entail axioms to be deleted


Syntactic approach to evolution

Syntactic Approach to Evolution

  • In the ontology:

    • “Oenophiles are gourmets”

    • “Oenophiles are not koalas”

  • To delete: “Oenophiles are gourmets”

  • To this end it is enough to delete

[HS’05]

[KPSCG’06]

[JRGHB’11]

and

  • In the resulted ontology:

    • “Oenophiles are not gourmets”

    • “Oenophiles are not koalas” is lost

OK

Not desirable


Outline1

Outline

  • Existing approaches to evolution

    • Syntactic approach

    • Deductive approach

  • Our approach: evolution under constraints

  • Conclusion & directions


Da evolution process

DA: Evolution Process

  • add/delete

  • minimal change

represent

expand

processing

processing

  • evolvedclosurein L

  • ontologyin L

  • closurein L

  • evolvedontologyin L

  • operator

  • newinfo

either axioms to add

or axioms to delete

E.g., contraction operator: takes a maximal subset (w.r.t. set inclusion)of the ontology deductive closure which does not entail axioms to be deleted


What is known

What Is Known?

  • DA have been studied for propositional logic

    • WIDTIO

    • Cross-product

  • What about ontologies?

  • Practical extensions of SA to preserve certain inference

    • [JRGHB’11] implemented in ContentCVS

    • “Manchester” grammar [GPS’12]: extension of [JRGHB’11]with combination of sub-concepts of the ontology

axiom  A ⊑ B | A ⊑ ¬ B | A ⊑ ∃ R.B | A ⊑ ∀ R.B


Syntactic approach to evolution1

Syntactic Approach to Evolution

  • In the resulted ontology:

    • “Oenophiles are not gourmets”

    • “Oenophiles are not koalas” is lost

  • ContentCVS & “Manchester” grammar allow to restore the missing disjointness

OK

Not desirable


Outline2

Outline

  • Existing approaches to evolution

    • Syntactic approach

    • Deductive approach

  • Our approach: evolution under constraints

  • Conclusion & directions


Our proposal in a nutshell

Our Proposal in a Nutshell

  • Generalization of SA and DA under a common framework

  • Our view of principle of minimal change

    • maximize preservation of ontology structure

    • maximize preservation of ontology entailments

  • Preservation language (LP) tells us which class of entailments should be maximized

  • ContentCVS & “Manchester grammar” are instantiations for particular “finite” LP


Syntactic deductive approach

Syntactic-Deductive Approach

SA

DA


Evolution process

Evolution Process

  • add/delete

  • minimal change

represent

expand

processing

  • sub-ontologyin L

  • sub-ontologyin LO

  • evolvedclosurein LP

  • evolvedclosurein L

  • ontologyin LI

  • closurein LP

  • ontologyin L

  • closurein L

  • evolvedontologyin L

  • evolvedontologyin LO

  • operator

  • newinfo

either axioms to add

or axioms to delete


Evolution under semantic constraints

Evolution under Semantic Constraints

processing

  • sub-ontologyin LO

  • ontologyin LI

  • closurein LP

  • operator

  • evolvedontologyin LO

  • evolvedclosurein LP

  • semanticconstraints

  • (C+,C-)

  • C+: axioms that should be present in the result

  • C−: axioms that should be absent in the result

  • General evolution encompasses both

    • contraction via C−

    • revision via C+


Example contraction

Example: Contraction

processing

  • sub-ontologyin LI

  • Task: delete an axiom A1 ⊑ A2 from an LI-ontology K

  • LO-ontology K’is a contraction of an LI-ontology Kw.r.t. A1 ⊑ A2 if:

    • K’⊭ A1 ⊑ A2

    • K⊨ K’

  • Contraction may not be optimal

  • ontologyin LI

  • closurein LP

  • operator

  • evolvedontologyin LO

  • evolvedclosurein LP

  • semanticconstraints

  • (∅,C-)

LI: input lang.

LO: output lang.

LP: preservation lang.


Example contraction1

Example: Contraction

processing

  • sub-ontologyin LI

  • ontologyin LI

  • closurein LP

  • operator

  • evolvedontologyin LO

  • evolvedclosurein LP

  • semanticconstraints

  • (∅,C-)

  • newdta

LI: input lang.

LO: output lang.

LP: preservation lang.

  • Task: delete an axiom A1 ⊑ A2 from and LI-ontology K

  • AcontractionK’ of K isoptimalw.r.t. LP if it maximally preserves:

    • structure of KK’ ∩ K⊄ K’’∩ Kfor every contr. K’’

    • LP-entailments of Knot true: if K’⊨α then K’’⊨α for every contr. K’’


Example contraction2

Example: Contraction

Delete: Gourmet ⊑ French

Contraction

Optimal

Contraction

Optimal


Evolution with finite lp

Evolution with Finite LP

processing

  • sub-ontologyin LO

  • Ontology language Lover a finite signatureΣisfinite if there are finitely many non-equivalent L-formulas over Σ

  • Examples of LP:

    • ContentCVS &”Manchester” grammarsfinite

    • OWL 2 QL (DL-Lite) finite

    • OWL 2 EL (EL, EL++, FL0)infinite

  • ontologyin LI

  • closurein LP

  • operator

  • evolvedontologyin LO

  • evolvedclosurein LP

  • semanticconstraints

  • (C+,C–)


Evolution with finite lp1

Evolution with Finite LP

processing

  • sub-ontologyin LO

  • ontologyin LI

  • closurein LP

  • operator

  • evolvedontologyin LO

  • evolvedclosurein LP

  • semanticconstraints

  • (C+,C–)

always exists

finite LP

Theorem: If the preservation language LP is finite, then

  • an optimal evolution always exists (provided an evolution exists)

  • both O and LP-closure of O are finite  we can simply write the result


Evolution with infinite lp

Evolution with Infinite LP

processing

  • sub-ontologyin LO

  • ontologyin LI

  • closurein LP

  • operator

  • evolvedontologyin LO

  • evolvedclosurein LP

  • semanticconstraints

  • (C+,C–)

finite representationmay not exist

infinite LP

  • What if LP is infinite?

  • We have a problem!

  • Optimal evolution may not exist!


Evolution with infinite lp1

Evolution with Infinite LP

processing

  • sub-ontologyin LO

  • ontologyin LI

  • closurein LP

  • operator

  • evolvedontologyin LO

  • evolvedclosurein LP

  • semanticconstraints

  • (C+,C–)

FL0

EL

FL0

EL

EL

FL0

Theorem:

  • If FL0 setting optimal evolution does not exist in general

  • If EL setting optimal evolution does not exist in general

    • complex interaction of cycles and recursions


Infinite lp exponential case

Infinite LP: Exponential Case

processing

  • sub-ontologyin LO

  • ontologyin LI

  • closurein LP

  • operator

  • evolvedontologyin LO

  • evolvedclosurein LP

  • semanticconstraints

  • (∅,C-)

acyclic EL

acyclic EL

chain EL

cyclic

  • ChainEL consists of inclusion assertions

    • A1⊑ ∃R1…Rn.A2or

    • ∃R1…Rn.A1 ⊑ A2

  • It is a simple infinite language to study expressibility

  • An acyclic ontology has acyclic canonical model

  • SNOMED and NCItare acyclic

  • opt. contraction always exists

  • EXP time computation


Infinite lp polynomial case

Infinite LP: Polynomial Case

processing

  • sub-ontologyin LO

  • ontologyin LI

  • closurein LP

  • operator

  • evolvedontologyin LO

  • evolvedclosurein LP

  • semanticconstraints

  • (∅,C-)

non-rec EL

non-rec EL

chain EL

non-recursive

  • An ontology is non-recursiveif concepts of the form ∃R.C donot appear at the left-hand side of axioms

  • Simplest non-recursive EL sub-language

  • opt. contraction always exists

  • PTimecomputation


Summary

Summary

ruled out by LP


Outline3

Outline

  • Existing approaches to evolution

    • Syntactic approach

    • Deductive approach

  • Our approach: evolution under constraints

  • Conclusion & directions


Conclusion directions

Conclusion & Directions

  • We introduced SDA:

  • a novel framework for ontology evolution

  • SDA generalizes:

    • syntactic approaches and

    • deductive approaches

  • it provides flexible means to navigate between SA and DA

We studied 4 settings for SDA:

  • Directions:

  • extend the current results to richer LP: chain EL  ?

    • evolution beyond EL


Ontology evolution under semantic constraints

Thank you!


References

References

  • [HKR’08] Hartung, M.; Kirsten, T.; and Rahm, E. 2008. Analyzing the evolution of life science ontologies and mappings. In Proc. of DILS, 11–27.

  • [SM-1] http://www.ihtsdo.org/snomed-ct/snomed-ct0/adoption-of-snomed-ct/

  • [FMA] http://sig.biostr.washington.edu/projects/fm/AboutFM.html

  • [NCI] https://wiki.nci.nih.gov/display/EVS/NCI+Thesaurus+versus+NCI+Metathesaurus

  • [HS’05]Haase, P., Stojanovic, L.: Consistent evolution of OWL ontologies. In: ESWC. (2005)

  • [KPSCG’06] Kalyanpur, A., Parsia, B., Sirin, E., Grau, B.C.: Repairingunsatisfiableconcepts in OWL ontologies. In: ESWC. (2006) 170–184

  • [JRCGHB’11] Jimenez-Ruiz, E., Cuenca Grau, B., Horrocks, I., Berlanga, R.: Supporting concurrent ontology development: Framework, algorithms and tool. DKE. 70:1 (2011)

  • [GPS’12]: Rafael S. Gonçalves, BijanParsia, Ulrike Sattler. 2012. Concept-based semantic difference in expressive description logics. In Proc. of DL


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