tailoring temporal description logics for reasoning over temporal conceptual models

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Tailoring Temporal Description Logics forReasoning over Temporal Conceptual Models

A. Artale1

R. Kontchakov2, V. Ryzhikov1, and M. Zakharyaschev2

1 KRDB Research Centre, Free University of Bozen-Bolzano2 Department of Comp. Science and Inf. Sys., Birkbeck College, London

University of KwaZulu-Natal, Durban, South Africa, 30-09-11

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Motivations

Investigation of the Computational Complexity of reasoningover Temporal Ontologies/Conceptual Models.

Languages considered: Family of Temporally ExtendedDL-Lite languages.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

ERVTThe Temporal Data Model

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

ERVT: The Proposed Temporal Conceptual Model

ERVT is the temporal extended Entity-Relationship model able tocapture Validity Time with the following temporal features:

Timestamping: to distinguish between temporal andatemporal modeling constructs.

Evolution and Transition constraints: to describe how objectscan change their class membership over time. Transitionconstraints presuppose that class migration happens in a fixedamount of time.

Lifespan cardinality constraints: temporal counterparts ofstandard cardinality constraints evaluated over the entireexistence of the object.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

ERVT: The Proposed Temporal Conceptual Model

ERVT is the temporal extended Entity-Relationship model able tocapture Validity Time with the following temporal features:

Timestamping: to distinguish between temporal andatemporal modeling constructs.

Evolution and Transition constraints: to describe how objectscan change their class membership over time. Transitionconstraints presuppose that class migration happens in a fixedamount of time.

Lifespan cardinality constraints: temporal counterparts ofstandard cardinality constraints evaluated over the entireexistence of the object.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

ERVT: The Proposed Temporal Conceptual Model

ERVT is the temporal extended Entity-Relationship model able tocapture Validity Time with the following temporal features:

Timestamping: to distinguish between temporal andatemporal modeling constructs.

Evolution and Transition constraints: to describe how objectscan change their class membership over time. Transitionconstraints presuppose that class migration happens in a fixedamount of time.

Lifespan cardinality constraints: temporal counterparts ofstandard cardinality constraints evaluated over the entireexistence of the object.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

ERVT: The Proposed Temporal Conceptual Model

ERVT is the temporal extended Entity-Relationship model able tocapture Validity Time with the following temporal features:

Timestamping: to distinguish between temporal andatemporal modeling constructs.

Evolution and Transition constraints: to describe how objectscan change their class membership over time. Transitionconstraints presuppose that class migration happens in a fixedamount of time.

Lifespan cardinality constraints: temporal counterparts ofstandard cardinality constraints evaluated over the entireexistence of the object.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

ERVT: A Company Example

Department S InterestGroup

OrganizationalUnit

d

Member S

(1,∞)

org

mbrEmployee S

Name(String)

S

PaySlipNumber(Integer)

S Salary(Integer)

T

Manager T

TopManagerAreaManager

dex−

dev

pex

WorksOn T

(3,∞)

act

emp

Project

ProjectCode(String)

SPropose gp

(0,1)

Ex-Project tex

Managesman

(1,1)

[0,5]

prj

(1,1)

1

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Known Complexity Results for Reasoning over ERVT

Undecidability.

Theorem. Reasoning on the ERVT fragment with bothtimestamping and evolution constraints isundecidable [ :AMAI-05].

Decidability.

Theorem. Reasoning on the ERVT fragment with bothtimestamping and evolution constraints restricted to classes isExpTime [ FWZ:02].Theorem. Reasoning on the ERVT fragment withtimestamping and lifespan cardinalities is 2ExpTime [ LT:07].

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Known Complexity Results for Reasoning over ERVT

Undecidability.

Theorem. Reasoning on the ERVT fragment with bothtimestamping and evolution constraints isundecidable [ :AMAI-05].

Decidability.

Theorem. Reasoning on the ERVT fragment with bothtimestamping and evolution constraints restricted to classes isExpTime [ FWZ:02].Theorem. Reasoning on the ERVT fragment withtimestamping and lifespan cardinalities is 2ExpTime [ LT:07].

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Temporal Conceptual Modelling – Known Results

temporal ERVT components temporalfeatures ERfull (ALCQI) modalities

trans, evo ExpTime [ FWZ:02] ©F/©P ,2F/2P

ts 2ExpTime [ LT:07] 2∗ ,Rts, evo Undec. [ :05] 2F/2P ,Rts, trans 2∗ ,R,©F/©Pts, lfc 2ExpTime [ LT:07] 2∗ ,Rtrans, lfc R,©F/©Pevo, lfc 2F/2P ,R

ts: Timestamping lfc: Lifespan Cardinalitiesevo: Evolution trans: Transition

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Aims of this Work

Our Aims: Conduct an exhaustive investigation on usefulfragments of ERVT weakening either the atemporal ortemporal component.

Our Results:

We give an exhaustive picture on the complexity of reasoningover temporal extensions of DL-Lite;Based on these results, we show encouraging complexityresults for reasoning over temporal ontologies where practicalreasoning is feasible!

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Aims of this Work

Our Aims: Conduct an exhaustive investigation on usefulfragments of ERVT weakening either the atemporal ortemporal component.

Our Results:

We give an exhaustive picture on the complexity of reasoningover temporal extensions of DL-Lite;Based on these results, we show encouraging complexityresults for reasoning over temporal ontologies where practicalreasoning is feasible!

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The DL-Lite Languages

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

DL-LiteNbool, DL-LiteNkrom and DL-LiteNcore

DL-LiteNbool. C1 v C2, with:

R −→ P | P−

B −→ A | ≥ n R | ⊥C −→ B | ¬C | C1 u C2

DL-LiteNkrom. B1 v B2, B1 u B2 v ⊥, ¬B1 v B2.

DL-LiteNcore. B1 v B2, B1 u B2 v ⊥.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The DL-Lite Languages - Complexity Results

Complexity Results [CDLLR:AAAI05, CKZ:JAIR09]:

Satisfiability: NP-complete/NLogSpace/NLogSpace;

Instance Checking (Data Complexity): AC0/AC0/AC0;

Query Answering (Data Complexity): coNP/coNP/AC0.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

DL-Lite – Conceptual Modelling Example

Manager v EmployeeAreaManager v ManagerTopManager v Manager

AreaManager u TopManager v ⊥Manager v AreaManager t TopManager∃WorksFor v Employee∃WorksFor− v Project

Project v ∃WorksFor−

≥ 2 Manages v ⊥≥ 2 Manages− v ⊥

...

Note: We use the shortcut ∃R instead of ≥ 1 R.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The Family of EER/UML Languages [ CKRZ:ER07]

ERrefDL-LiteNcore

ERboolDL-LiteNkrom

ERfullDL-LiteNbool

ConstructDL-Lite

RepresentationEntities Concept Name: E

+ + + Isa E1 v E2

+ + + Disjointness E1 v ¬E2

– + + Covering E ≡ E1 t E2

Attributes Role Name: A

+ + + Range ∃A− v D

+ + + Multiplicity E v≥ nAE v≤ mA

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The Family of EER/UML Languages [ CKRZ:ER07]

ERrefDL-LiteNcore

ERboolDL-LiteNkrom

ERfullDL-LiteNbool

ConstructDL-Lite

Representation

RelationshipsConcept Name CR

and n Roles Ui

+ + + TypingCR ≡ ∃Ui

≥ 2 Ui v ⊥∃U−i v Ei

+ + +Cardinality

(Refinement)E v≥ n U−iE v≤ m U−i

– – + Isa —

– – + Disjointness —

– – + Covering —

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The Temporal DL-LiteLanguages

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Seminal Papers

SCHILD, K., 1993. Combining terminological logics withtense logic. Proc. of the 6th Portuguese Conference on AI.

F. Baader and A. Laux., 1995. Terminological Logics withModal Operators, IJCAI-95.

Wolter, F. and Zakharyaschev, M., 1998, TemporalizingDescription Logics, FroCoS-98.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Complexity for Temporal ALC– Known Results

Temporal operators can be applied to:

Concepts, roles or axioms (they are temporalized);

Concepts, roles or axioms can have a time-invariantinterpretation (they are rigid).

The satisfiability problem has a different complexity dependingfrom the combination between LT L and ALC constructs:

concepts roles axiomsrigid temp rigid temp rigid temp

Undec. - yes yes - yes - [GKWZ:03]

2ExpTime∗ - yes - yes yes - [ LT:07]

2ExpTime yes - yes - yes yes [BGL:08]

ExpSpace - yes - - - yes [GKWZ:03]

ExpTime - yes - - yes - [S:93, FWZ:02]

(∗) Using the S5 modalities 2∗ and R.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The Temporal Language TFPXDL-LiteNbool

TFPXDL-LiteNbool has the following features:

The temporal operators are:

3F/3P (sometime in the future/past),2F/2P (always in the future/past), and©F/©P (next/previous time);

Concepts can be temporalized;

Roles can be rigid or flexible;

Axioms are rigid.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The TFPXDL-LiteNbool Temporal Languages

TFPXDL-LiteNbool. C1 v C2, with:

S ::= Pi | Gi , R ::= S | S−,

B ::= ⊥ | Ai | ≥ q R,

C ::= B | ¬C | C1 u C2 | 3FC | 3PC | 2FC | 2PC | ©FC | ©PC

Where Gi denotes rigid roles.

TFPXDL-LiteNcore. D1 v D2, D1 u D2 v ⊥;

TFPXDL-LiteNkrom. D1 v D2, D1 u D2 v ⊥, ¬D1 v D2;

with:D ::= B | 2FB | 2PB | ©FB | ©PB

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The TFPDL-LiteNbool Temporal Languages

TFPDL-LiteNbool. C1 v C2, with:

S ::= Pi | Gi , R ::= S | S−,

B ::= ⊥ | Ai | ≥ q R,

C ::= B | ¬C | C1 u C2 | 3FC | 3PC | 2FC | 2PC

Where Gi denotes rigid roles.

TFPDL-LiteNcore. D1 v D2, D1 u D2 v ⊥;

TFPDL-LiteNkrom. D1 v D2, D1 u D2 v ⊥, ¬D1 v D2;

with:D ::= B | 2FB | 2PB

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Semantics of TFPXDL-LiteNbool

A TFPXDL-LiteNbool interpretation I is a function over Z

I(n) =(∆I ,AI(n)0 , . . . ,P

I(n)0 , . . . ,G

I(n)0 , . . .

),

where:

Rigid roles are time-invariant:

GI(n1) = GI(n2), ∀n1, n2 ∈ Z

Temporal operators are interpreted over Z:

(3FC )I(n) =⋃

k>n CI(k), (3PC )I(n) =⋃

k<n CI(k),

(2FC )I(n) =⋂

k>n CI(k), (2PC )I(n) =⋂

k<n CI(k),

(©FC )I(n) = CI(n+1), (©PC )I(n) = CI(n−1).

TBox assertions are interpreted globally:

I |= C v D iff CI(n) ⊆ DI(n), for all n ∈ Z

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The Temporal Language TRUDL-LiteNbool

TRU DL-LiteNbool has the following features:

The temporal operators are:

3∗ (sometime), and2∗ (always);

Concepts can be temporalized;

Roles can be temporalized;

Axioms are rigid;

We have the following equivalences:

2∗ C = 2F2PC and 3∗ C = 3F3PC .

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The TRUDL-LiteNbool Temporal Language

TRU DL-LiteNbool language: Uses the universal modalities, 2∗ , 3∗ ,on both concepts and roles.

R ::=S | S− | 2∗ R | 3∗ R

C ::=B | ¬C | C1 u C2 | 2∗ C | 3∗ C

(2∗ C )I(n) =⋂k∈Z

CI(k) and (3∗ C )I(n) =⋃k∈Z

CI(k)

(2∗ R)I(n) =⋂k∈Z

RI(k) and (3∗ R)I(n) =⋃k∈Z

RI(k)

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

The TRXDL-LiteNbool Temporal Language

TRX DL-LiteNbool language: Uses the universal modalities, 2∗ , 3∗ ,just on roles, and the next/previous-time modalities, ©F , ©Pon concepts.

R ::=S | S− | 2∗ R | 3∗ R

C ::=B | ¬C | C1 u C2 | ©FC | ©PC

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Temporal DL-Lite LanguagesVs.

Temporal ConceptualModelling

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

TFPDL-LiteNbool/T

RUDL-Lite

Nbool – Timestamping

Department S InterestGroup

OrganizationalUnit

d

Member S

(1,∞)

org

mbrEmployee S

Name(String)

S

PaySlipNumber(Integer)

S Salary(Integer)

T

Manager T

TopManagerAreaManager

dex−

dev

pex

WorksOn T

(3,∞)

act

emp

Project

ProjectCode(String)

SPropose gp

(0,1)

Ex-Project tex

Managesman

(1,1)

[0,5]

prj

(1,1)

1

Manager v 3F3P¬Manager, Manager v 3∗ ¬ManagerEmployee v 2F2PEmployee, Employee v 2∗ Employee

Temporary Relations/Attributes: Reification

Global Relations/Attributes: Reification + Global Roles

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

TFPXDL-LiteNbool – Evolution and Transition Constraints

Department S InterestGroup

OrganizationalUnit

d

Member S

(1,∞)

org

mbrEmployee S

Name(String)

S

PaySlipNumber(Integer)

S Salary(Integer)

T

Manager T

TopManagerAreaManager

dex−

dev

pex

WorksOn T

(3,∞)

act

emp

Project

ProjectCode(String)

SPropose gp

(0,1)

Ex-Project tex

Managesman

(1,1)

[0,5]

prj

(1,1)

1

Manager v 3P¬EmployeeManager v 2FManager

AreaManager v 3FTopManager

Project v ©PEx-Project

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

TRUDL-LiteNbool – Lifespan Cardinality Constraints

Department S InterestGroup

OrganizationalUnit

d

Member S

(1,∞)

org

mbrEmployee S

Name(String)

S

PaySlipNumber(Integer)

S Salary(Integer)

T

Manager T

TopManagerAreaManager

dex−

dev

pex

WorksOn T

(3,∞)

act

emp

Project

ProjectCode(String)

SPropose gp

(0,1)

Ex-Project tex

Managesman

(1,1)

[0,5]

prj

(1,1)

1

A top-manager manages at most 5 different projects in her lifespanTopManager v ≤ 53∗ Manages (Lifespan Cardinalities)

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Temporal DL-Lite – Obtained Complexity Results

The following original complexity results have been used to showupper bounds for reasoning over Temporal Conceptual Models.

concepttemporaloperators

flexible & rigid roles onlytemporalized

roles (R)DL-LiteNbool DL-LiteNkrom/core DL-LiteNbool

2F/P ,©F/P(FPX)

PSpace NPin PTime

Undec.

2F/P(FP)

NP NPin PTime

?

2∗ ,©F/P(UX)

PSpace NPin PTime

Undec.(R X)

2∗(U)

NP NLogSpace NP(R U)

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Complexity: TFPXDL-LiteNbool and Fragments

1 We reduce satisfiability in TFPXDL-LiteNbool KBs tosatisfiability in QT L1, i.e., the one-variable fragment offirst-order temporal logic over (Z, <).

2 We then show how to remove existential quantifiers from suchQT L1 formulas, thus reducing to LT L formulas.

3 Complexity results for temporal extensions of DL-LiteNboolfollow from the corresponding LT L results.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Complexity: TFPXDL-LiteNkrom/core and Fragments

1 We reduce satisfiability in TFPXDL-LiteNkrom/core KBs tosatisfiability in QT L1, i.e., the one-variable fragment offirst-order temporal logic over (Z, <).

2 We then show how to remove existential quantifiers from suchQT L1 formulas, thus reducing to two fragments of LT L, i.e.,propositional temporal logic of binary clauses, i.e., LT Lkromand LT Lcore.

3 We show that:

LT Lkrom is NP-complete;LT Lcore is in PTime.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

LT Lkrom and LT Lcore

LT Lkrom

λ ::= p | ¬λ | ©Fλ | ©Pλ | 2Fλ | 2Pλ | 2∗ λ,

ϕ ::= (λ1 ∨ λ2) | 2∗ (λ1 ∨ λ2) | ϕ1 ∧ ϕ2.

LT Lcore

λ ::= p | ©Fλ | ©Pλ | 2Fλ | 2Pλ | 2∗ λ,

ϕ ::= (λ1 → λ2) | (¬λ1 ∨ ¬λ2) | 2∗ (λ1 → λ2) |2∗ (¬λ1 ∨ ¬λ2) | ϕ1 ∧ ϕ2.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Complexity: DL-Lite with Temporalized Roles

TRX DL-LiteNbool is Undecidable is proved by encoding the tilingproblem.

TRU DL-LiteNbool is NP-complete and the upper bound isshowed by construction of Quasimodels/Mosaics.

All the complexity results are shown in [ KRZ:xx]

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Complexity: DL-Lite with Temporalized Roles

TRX DL-LiteNbool is Undecidable is proved by encoding the tilingproblem.

TRU DL-LiteNbool is NP-complete and the upper bound isshowed by construction of Quasimodels/Mosaics.

All the complexity results are shown in [ KRZ:xx]

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Temporal Ontologies – Obtained Complexity Results

temporal EER componentfeatures ERfull ERbool ERref

ts 2ExpTime [ LT:IJCAI07] NP NLogSpace

trans ExpTime [ FWZ:JELIA02] PSpace in PTime

ts, trans Undec. PSpace in PTime

evo ExpTime [ FWZ:JELIA02] NP NP

ts, evo Undec. [ :AMAI05] NP NP

trans, evo ExpTime [ FWZ:JELIA02] PSpace NP

ts, trans, evo Undec. [ :AMAI05] PSpace NP

ts, lfc 2ExpTime [ LT:IJCAI07] NP† in NP†

trans, lfc Undec. Undec. ?

evo, lfc Undec. ? ?

(†) This result is proved only for binary relationships.

ts: Timestamping lfc: Lifespan Cardinalitiesevo: Evolution trans: Transition

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Conclusions

We showed that:

By dropping ISA between relations (ERbool/DL-LiteNbool) andcovering (ERref/DL-LiteNcore) we obtained bettercomputational behavior for reasoning over temporalschemas/DL-Lite ontologies.

Both ERbool and ERref have been extended with timestamping,evolution and transition constraints, lifespan cardinalities.

DL-LiteNbool, DL-LiteNkrom and DL-LiteNcore have been extendedwith past and future temporal operators, and with theuniversal modality (both over concepts and roles).

We presented a nearly complete picture for reasoning overtemporal CMs/Ontologies/DL-Lite KBs.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Future Work

Few cases involving lifespan cardinalities/universal modalityare still open.

Investigating the problem of temporal queries over temporalontologies/conceptual schemas.

Investigating the possibility to use standard and implementedtemporal reasoners for practical reasoning over temporalschemas.

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

Thanks to...

Enrico Franconi

Carsten Lutz

Christine Parent

Stefano Spaccapietra

David Toman

Frank Wolter

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

THANK YOU!

Alessandro Artale – KRDB Tailoring Temporal DLs for Reasoning over Temporal CMs

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