SlideShare uma empresa Scribd logo
1 de 65
Baixar para ler offline
A Survey of Temporal Extensions of DLs
Research school: Foundations and Challenges of Change in Ontologies and
Databases 2014
Free University of Bozen-Bolzano, Italy

Group 6:
Daniele Dell’Aglio
DEIB – Politecnico di Milano

daniele.dellaglio@polimi.it

Fariz Darari
`
KRDB – Universita di Bolzano

fadirra@gmail.com

Davide Lanti
`
KRDB – Universita di Bolzano

davide.lanti.sersante@gmail.com

Mentor:
Michael Zakharyaschev
Birkbeck College

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

1 – 39
What we will see

The paper:
Alessandro Artale and Enrico Franconi. A survey of temporal extensions of
description logics. Annals of Mathematics and Artificial Intelligence,
30(1-4):171-210, 2000.
Outline:
Overview
Running Example
A Survey on Existing Solutions
Current Hot Topics, Future Directions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

2 – 39
Outline

Overview
Running Example
A Survey on Existing Solutions
State-change based DLs
Temporal DLs with internal approach
Point-based temporal DLs
Interval-based temporal DLs
Current Hot Topics, Future Directions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

3 – 39
Temporal extensions of DLs
How can time be modelled?

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

4 – 39
Temporal extensions of DLs
How can time be modelled?
Point-based notion of time

Interval-based notion of time

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

4 – 39
Temporal extensions of DLs
How can time be modelled?
Point-based notion of time

Interval-based notion of time

How can the temporal dimension be handled?

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

4 – 39
Temporal extensions of DLs
How can time be modelled?
Point-based notion of time

Interval-based notion of time

How can the temporal dimension be handled?
Implicit notion of time: sequences of events through state-change
representations
Explicit notion of time: definition of temporal operators and new formulae

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

4 – 39
Temporal extensions of DLs
How can time be modelled?
Point-based notion of time

Interval-based notion of time

How can the temporal dimension be handled?
Implicit notion of time: sequences of events through state-change
representations
Explicit notion of time: definition of temporal operators and new formulae
Internal point of view: different states of an individual are modelled as
different individual components
External point of view: an individual has different states in different
moments
Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

4 – 39
Classification of the DL temporal extensions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

5 – 39
Classification of the DL temporal extensions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

5 – 39
Classification of the DL temporal extensions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

5 – 39
Classification of the DL temporal extensions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

5 – 39
Classification of the DL temporal extensions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

5 – 39
Outline

Overview
Running Example
A Survey on Existing Solutions
State-change based DLs
Temporal DLs with internal approach
Point-based temporal DLs
Interval-based temporal DLs
Current Hot Topics, Future Directions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

6 – 39
Running example
How to become a doctor:
Be a PhD student for some years (3-4)
Defend a thesis
Become a doctor

Let’s try to model it with different temporal logics!

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

7 – 39
Outline

Overview
Running Example
A Survey on Existing Solutions
State-change based DLs
Temporal DLs with internal approach
Point-based temporal DLs
Interval-based temporal DLs
Current Hot Topics, Future Directions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

8 – 39
C LASP [DL96]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

9 – 39
C LASP [DL96]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

9 – 39
C LASP [DL96]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

9 – 39
C LASP [DL96]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

9 – 39
C LASP [DL96]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

9 – 39
C LASP [DL96]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

9 – 39
C LASP [DL96]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

9 – 39
C LASP

A system to reason about plans, proposed by Devambu and Litman (first half of
90s)

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

10 – 39
C LASP

A system to reason about plans, proposed by Devambu and Litman (first half of
90s)
Two formalisms
The C LASSIC DL to define states, actions, plans and relation among them
A set of operators to specify the plan expressions
SEQUENCE, LOOP, TEST, OR, . . .
The plan expression is converted in a finite automata

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

10 – 39
C LASP

A system to reason about plans, proposed by Devambu and Litman (first half of
90s)
Two formalisms
The C LASSIC DL to define states, actions, plans and relation among them
A set of operators to specify the plan expressions
SEQUENCE, LOOP, TEST, OR, . . .
The plan expression is converted in a finite automata
C LASP performs
Plan subsumption
Plan recognition: determines if a scenario belong to a given plan

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

10 – 39
C LASP considerations

Actions are instantaneous
The temporal expressivity of Clasp is implicit in the language
Alternatives can be expressed through disjunctions (OR)

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

11 – 39
C LASP considerations

Actions are instantaneous
The temporal expressivity of Clasp is implicit in the language
Alternatives can be expressed through disjunctions (OR)
Explicit temporal constraints are not expressible
The terminological representation of states:
is not as expressive as the predicate calculus representation used in STRIPS
avoids doing general theorem proving when computing state subsumption

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

11 – 39
Outline

Overview
Running Example
A Survey on Existing Solutions
State-change based DLs
Temporal DLs with internal approach
Point-based temporal DLs
Interval-based temporal DLs
Current Hot Topics, Future Directions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

12 – 39
T-R EX [WL92]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

13 – 39
T-R EX [WL92]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

13 – 39
T-R EX [WL92]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

13 – 39
T-R EX [WL92]

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

13 – 39
T-R EX
A system to represent and reason about plans developed by Weida and Litman
(90s)

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

14 – 39
T-R EX
A system to represent and reason about plans developed by Weida and Litman
(90s)
Like C LASP, two different formalisms are used
The K-R EP or the C LASSIC DLs to describe the actions
A temporal constraint network to represent the plans
Constraints defined through the Allen’s relationships
before, meets, after, finishes, . . .

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

14 – 39
T-R EX
A system to represent and reason about plans developed by Weida and Litman
(90s)
Like C LASP, two different formalisms are used
The K-R EP or the C LASSIC DLs to describe the actions
A temporal constraint network to represent the plans
Constraints defined through the Allen’s relationships
before, meets, after, finishes, . . .
T-R EX performs the following reasoning tasks:
subsumption
plan recognition: the system determines if a set of observations are
compatible with (i.e., could instantiate) the plan set
plans are classified in possible, necessary and impossible

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

14 – 39
T-R EX considerations

T-Rex conceptual model captures the actions
States are not represented

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

15 – 39
T-R EX considerations

T-Rex conceptual model captures the actions
States are not represented
T-Rex is an example of external notion of time with an internal approach
It uses the Allen’s relationships to specify the constraints (explicit notion of
time)
Plans capture the time notion (internal approach)

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

15 – 39
T-R EX considerations

T-Rex conceptual model captures the actions
States are not represented
T-Rex is an example of external notion of time with an internal approach
It uses the Allen’s relationships to specify the constraints (explicit notion of
time)
Plans capture the time notion (internal approach)
The plan subsumption is NP-Complete
The crux is to determine the mappings between plans

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

15 – 39
Time as Concrete Domain [BH91]

Idea:
Abstract individuals are related to values in a concrete domain
.. via features
Tuples of concrete values identified by features can be constrained to belong
to a predicate over the concrete domain

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

16 – 39
Example [AF00]
.
Poor-Manager = Manager

∀MONTHLY-BALANCE.∃(INCOME, EXPENSES). ≤

INCOME and EXPENSES are features from ∆I to the concrete domain R
≤ is a predicate defined over the concrete domain

∆I

R
IN

≤

EXP
M-B

M-B
IN

≤

EXP

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

17 – 39
ALC(D) [BH91]

ALC extended with concrete predicates
I
I
(∃(u1 , . . . , un ).P)I := {a ∈ ∆I | u1 (a), . . . , un (a) ∈ P D }

u1 , . . . , un are compositions of features
D is called concrete domain

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

18 – 39
Running Example
Postdoc

PHD-STATE : PhD-Student

DOC-STATE : (Doctor

¬PhD-Student)

∃(PHD-STATE ◦ HAS-TIME, DOC-STATE ◦ HAS-TIME).meets

∆I

Intervals
H-T

meets

P-S

D-S
H-T

Recall: “different states of an individual are modelled as different individuals”
Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

19 – 39
Considerations

ALC(D), ALCF (D)
concept satisfiability, subsumption, and ABox consistency
PSPACE-complete
.. under the assumption that satisfiability in the concrete domain is in PSPACE
ALCRP(D)
Undecidable
Decidability if avoiding the interaction of complex roles with existential
and universal restrictions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

20 – 39
Outline

Overview
Running Example
A Survey on Existing Solutions
State-change based DLs
Temporal DLs with internal approach
Point-based temporal DLs
Interval-based temporal DLs
Current Hot Topics, Future Directions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

21 – 39
Combining Description Logics and Tense Operators: ALCT [Sch93]

Combination of ALC with point-based modal temporal connectives
3P , 2P ,

cP , UP , UP

Time part of the semantic structure
AI ⊆ T × ∆I
R I ⊆ T × ∆I × ∆I
Recall: “an individual has different states at different moments”
Temporal connectives can be applied only to concepts
3CtI := {a ∈ ∆I | ∃t . t ≤ t ∧ a ∈ CtI }

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

22 – 39
Running Example

Every doctor has been a PhD student in the past
Doctor

3P PhD-Student

Every thesis defender is a PhD student that has been a PhD student in the past
Thesis-Defender

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

PhD-Student

3P PhD-Student

23 – 39
Running Example

Every doctor has been a PhD student in the past
Doctor

3P PhD-Student

Every thesis defender is a PhD student that has been a PhD student in the past
Thesis-Defender

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

PhD-Student

3P PhD-Student

23 – 39
Running Example
Every doctor has been a PhD student in the past
Doctor

3P PhD-Student

Every thesis defender is a PhD student that has been a PhD student in the past
Thesis-Defender

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

PhD-Student

3P PhD-Student

23 – 39
Considerations

ALCT
Empty Abox
Linear, unbounded and discrete time structure
PSPACE-complete for statisfiability checking
Branching, unbounded and discrete time structure
EXPTIME-hard
Interval-based time structure
Undecidable
Open questions (still open?)
Extending ALCT (N ) with past tense?
Real numbers?

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

24 – 39
Outline

Overview
Running Example
A Survey on Existing Solutions
State-change based DLs
Temporal DLs with internal approach
Point-based temporal DLs
Interval-based temporal DLs
Current Hot Topics, Future Directions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

25 – 39
Interval-based Temporal DLs

Schmiedel’s Formalism
Idea
Examples
The Undecidable Realm
Idea
Examples
Towards Decidable Logic
Idea
Examples

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

26 – 39
Interval-based Temporal DLs: Characteristics

Interval-based

Explicit, eg: alltime, 3TE
Follows the external approach, eg: C i, a for temporal concept assertions and
R i, a, b for temporal role assertions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

27 – 39
Schmiedel’s Formalism: Idea

The first of such an interval-based temporal DL (made in 1990)
Underlying DL = F LEN R− (no
on roles, and role conjunction)

, ⊥, ¬,

but with cardinality restrictions

Temporal operators = at, alltime, sometime
Subsumption is argued to be undecidable

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

28 – 39
Schmiedel’s Formalism: Examples
Concept: PhD students during 1993
(at 1993 PhDStudent)
Terminological Axiom: Doctors were PhD students
Doctor
(sometime(x)(metBy now x).(at x (PhDStudent)))

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

29 – 39
The Undecidable Realm: Idea

Developed by Bettini
Variable-free extension with existential and universal temporal quantification
Arbitrary relationships between more than two intervals can’t be represented
Satisfiability and subsumption are undecidable
Starting from the DL ALCN
Two concept constructors: 3TE.C and 2TE.C

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

30 – 39
The Undecidable Realm: Examples

Concept: Persons who become a doctor sometime
3after.Doctor ,
eg: 1990, michael belongs to this, if 1992, michael belongs to Doctor
Terminological Axiom: Doctors were PhD students
Doctor
3(metBy).PhDStudent

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

31 – 39
Towards Decidable Logics: Idea

Developed by Artale and Franconi
Decidable: Expressivity is reduced, universal quantification on
temporal variables has been eliminated
Underlying DL (most expressive): T L-ALCF
Temporal variables are introduced by the temporal existential quantifier 3,
excluding the predefined temporal var #

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

32 – 39
Towards Decidable Logics: Examples
Terminological Axiom: Doctors were PhD students
Doctor
3(x)(# metBy x).PhDStudent@x
Terminological Axiom: PhD thesis defenders finish their PhDs
PhDThesisDefender
3(x)(# finishes x).PhDStudent@x

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

33 – 39
Outline

Overview
Running Example
A Survey on Existing Solutions
State-change based DLs
Temporal DLs with internal approach
Point-based temporal DLs
Interval-based temporal DLs
Current Hot Topics, Future Directions

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

34 – 39
Hot Topics: Temporal DLs for OBDA

OBDA over temporal data with validity time
Ontologies capable of temporal conceptual modeling
Developed TQL extending OWL 2 QL, still preserving FO rewritability
Example:
A fact with its validity time: givesBirth(diana, michael, 1970)
A temporal axiom: 3p givesBirth

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

motherOf

35 – 39
Hot Topics: Stream Query Processing
Query language for RDF streams

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

36 – 39
A Survey of Temporal Extensions of DLs
Research school: Foundations and Challenges of Change in Ontologies and
Databases 2014
Free University of Bozen-Bolzano, Italy

Group 6:
Daniele Dell’Aglio
DEIB – Politecnico di Milano

daniele.dellaglio@polimi.it

Fariz Darari
`
KRDB – Universita di Bolzano

fadirra@gmail.com

Davide Lanti
`
KRDB – Universita di Bolzano

davide.lanti.sersante@gmail.com

Mentor:
Michael Zakharyaschev
Birkbeck College

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

37 – 39
[AF00] Alessandro Artale and Enrico Franconi.
A survey of temporal extensions of description logics.
Annals of Mathematics and Artificial Intelligence, 30(1-4):171–210, 2000.
[BH91] Franz Baader and Philipp Hanschke.
A scheme for integrating concrete domains into concept languages.
In Proceedings of the 12th International Joint Conference on Artificial
Intelligence - Volume 1, IJCAI’91, pages 452–457, San Francisco, CA, USA,
1991. Morgan Kaufmann Publishers Inc.
[DL96] Premkumar T. Devanbu and Diane J. Litman.
Taxonomic plan reasoning.
Artif. Intell., 84(1-2):1–35, 1996.
[Sch93] Klaus Schild.
Combining terminological logics with tense logic.
˜
In Miguel Filgueiras and LuAs Damas, editors, Progress in Artificial
Intelligence, volume 727 of Lecture Notes in Computer Science, pages
105–120. Springer Berlin Heidelberg, 1993.

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

38 – 39
[WL92] Robert A. Weida and Diane J. Litman.
Terminological reasoning with constraint networks and an application to
plan recognition.
In Bernhard Nebel, Charles Rich, and William R. Swartout, editors, KR,
pages 282–293. Morgan Kaufmann, 1992.

Daniele Dell’Aglio, Fariz Darari and Davide Lanti
A Survey of Temporal Extensions of DLs

39 – 39

Mais conteúdo relacionado

Semelhante a A Survey of Temporal Extensions of DLs

Delphi method ppt
Delphi method pptDelphi method ppt
Delphi method pptZAID703
 
The Delphi Method and its Contribution to Decision-Making
The Delphi Method and its Contribution to Decision-MakingThe Delphi Method and its Contribution to Decision-Making
The Delphi Method and its Contribution to Decision-MakingJingjing Lin
 
Neural Text Embeddings for Information Retrieval (WSDM 2017)
Neural Text Embeddings for Information Retrieval (WSDM 2017)Neural Text Embeddings for Information Retrieval (WSDM 2017)
Neural Text Embeddings for Information Retrieval (WSDM 2017)Bhaskar Mitra
 
Kdd 2014 tutorial bringing structure to text - chi
Kdd 2014 tutorial   bringing structure to text - chiKdd 2014 tutorial   bringing structure to text - chi
Kdd 2014 tutorial bringing structure to text - chiBarbara Starr
 
54-6 September 2002, Edinburgh, UK, Pages 5-11.Bos, Fost.docx
54-6 September 2002, Edinburgh, UK, Pages 5-11.Bos, Fost.docx54-6 September 2002, Edinburgh, UK, Pages 5-11.Bos, Fost.docx
54-6 September 2002, Edinburgh, UK, Pages 5-11.Bos, Fost.docxblondellchancy
 
Introduction to Ontology Concepts and Terminology
Introduction to Ontology Concepts and TerminologyIntroduction to Ontology Concepts and Terminology
Introduction to Ontology Concepts and TerminologySteven Miller
 
Latent Dirichlet Allocation
Latent Dirichlet AllocationLatent Dirichlet Allocation
Latent Dirichlet AllocationMarco Righini
 
RDA Work Groups Outputs and Adoption - Early WG Report back session
RDA Work Groups Outputs and Adoption - Early WG Report back sessionRDA Work Groups Outputs and Adoption - Early WG Report back session
RDA Work Groups Outputs and Adoption - Early WG Report back sessionResearch Data Alliance
 
AMW'11 dependencies-sem index-t-mappings
AMW'11 dependencies-sem index-t-mappingsAMW'11 dependencies-sem index-t-mappings
AMW'11 dependencies-sem index-t-mappingsMariano Rodriguez-Muro
 
Foundations of Delphi for Foresight and Group Communication
Foundations of Delphi for Foresight and Group CommunicationFoundations of Delphi for Foresight and Group Communication
Foundations of Delphi for Foresight and Group CommunicationTina Comes
 
Knowledge extraction in Web media: at the frontier of NLP, Machine Learning a...
Knowledge extraction in Web media: at the frontier of NLP, Machine Learning a...Knowledge extraction in Web media: at the frontier of NLP, Machine Learning a...
Knowledge extraction in Web media: at the frontier of NLP, Machine Learning a...Julien PLU
 
Slides
SlidesSlides
Slidesbutest
 

Semelhante a A Survey of Temporal Extensions of DLs (18)

Delphi method ppt
Delphi method pptDelphi method ppt
Delphi method ppt
 
The Delphi Method and its Contribution to Decision-Making
The Delphi Method and its Contribution to Decision-MakingThe Delphi Method and its Contribution to Decision-Making
The Delphi Method and its Contribution to Decision-Making
 
Neural Text Embeddings for Information Retrieval (WSDM 2017)
Neural Text Embeddings for Information Retrieval (WSDM 2017)Neural Text Embeddings for Information Retrieval (WSDM 2017)
Neural Text Embeddings for Information Retrieval (WSDM 2017)
 
RR 2013 - Montali - Verification and Synthesis in Description Logic Based Dyn...
RR 2013 - Montali - Verification and Synthesis in Description Logic Based Dyn...RR 2013 - Montali - Verification and Synthesis in Description Logic Based Dyn...
RR 2013 - Montali - Verification and Synthesis in Description Logic Based Dyn...
 
Delphi method
Delphi methodDelphi method
Delphi method
 
Kdd 2014 tutorial bringing structure to text - chi
Kdd 2014 tutorial   bringing structure to text - chiKdd 2014 tutorial   bringing structure to text - chi
Kdd 2014 tutorial bringing structure to text - chi
 
LDA on social bookmarking systems
LDA on social bookmarking systemsLDA on social bookmarking systems
LDA on social bookmarking systems
 
54-6 September 2002, Edinburgh, UK, Pages 5-11.Bos, Fost.docx
54-6 September 2002, Edinburgh, UK, Pages 5-11.Bos, Fost.docx54-6 September 2002, Edinburgh, UK, Pages 5-11.Bos, Fost.docx
54-6 September 2002, Edinburgh, UK, Pages 5-11.Bos, Fost.docx
 
Introduction to Ontology Concepts and Terminology
Introduction to Ontology Concepts and TerminologyIntroduction to Ontology Concepts and Terminology
Introduction to Ontology Concepts and Terminology
 
Latent Dirichlet Allocation
Latent Dirichlet AllocationLatent Dirichlet Allocation
Latent Dirichlet Allocation
 
RDA Work Groups Outputs and Adoption - Early WG Report back session
RDA Work Groups Outputs and Adoption - Early WG Report back sessionRDA Work Groups Outputs and Adoption - Early WG Report back session
RDA Work Groups Outputs and Adoption - Early WG Report back session
 
AMW'11 dependencies-sem index-t-mappings
AMW'11 dependencies-sem index-t-mappingsAMW'11 dependencies-sem index-t-mappings
AMW'11 dependencies-sem index-t-mappings
 
Some Information Retrieval Models and Our Experiments for TREC KBA
Some Information Retrieval Models and Our Experiments for TREC KBASome Information Retrieval Models and Our Experiments for TREC KBA
Some Information Retrieval Models and Our Experiments for TREC KBA
 
Foundations of Delphi for Foresight and Group Communication
Foundations of Delphi for Foresight and Group CommunicationFoundations of Delphi for Foresight and Group Communication
Foundations of Delphi for Foresight and Group Communication
 
Knowledge extraction in Web media: at the frontier of NLP, Machine Learning a...
Knowledge extraction in Web media: at the frontier of NLP, Machine Learning a...Knowledge extraction in Web media: at the frontier of NLP, Machine Learning a...
Knowledge extraction in Web media: at the frontier of NLP, Machine Learning a...
 
Slides
SlidesSlides
Slides
 
Zander summer pit
Zander   summer pitZander   summer pit
Zander summer pit
 
Unit 2(knowledge)
Unit 2(knowledge)Unit 2(knowledge)
Unit 2(knowledge)
 

Mais de Daniele Dell'Aglio

Distributed stream consistency checking
Distributed stream consistency checkingDistributed stream consistency checking
Distributed stream consistency checkingDaniele Dell'Aglio
 
Triplewave: a step towards RDF Stream Processing on the Web
Triplewave: a step towards RDF Stream Processing on the WebTriplewave: a step towards RDF Stream Processing on the Web
Triplewave: a step towards RDF Stream Processing on the WebDaniele Dell'Aglio
 
On unifying query languages for RDF streams
On unifying query languages for RDF streamsOn unifying query languages for RDF streams
On unifying query languages for RDF streamsDaniele Dell'Aglio
 
RSEP-QL: A Query Model to Capture Event Pattern Matching in RDF Stream Proces...
RSEP-QL: A Query Model to Capture Event Pattern Matching in RDF Stream Proces...RSEP-QL: A Query Model to Capture Event Pattern Matching in RDF Stream Proces...
RSEP-QL: A Query Model to Capture Event Pattern Matching in RDF Stream Proces...Daniele Dell'Aglio
 
Summary of the Stream Reasoning workshop at ISWC 2016
Summary of the Stream Reasoning workshop at ISWC 2016Summary of the Stream Reasoning workshop at ISWC 2016
Summary of the Stream Reasoning workshop at ISWC 2016Daniele Dell'Aglio
 
On Unified Stream Reasoning - The RDF Stream Processing realm
On Unified Stream Reasoning - The RDF Stream Processing realmOn Unified Stream Reasoning - The RDF Stream Processing realm
On Unified Stream Reasoning - The RDF Stream Processing realmDaniele Dell'Aglio
 
Querying the Web of Data with XSPARQL 1.1
Querying the Web of Data with XSPARQL 1.1Querying the Web of Data with XSPARQL 1.1
Querying the Web of Data with XSPARQL 1.1Daniele Dell'Aglio
 
Augmented Participation to Live Events through Social Network Content Enrichm...
Augmented Participation to Live Events through Social Network Content Enrichm...Augmented Participation to Live Events through Social Network Content Enrichm...
Augmented Participation to Live Events through Social Network Content Enrichm...Daniele Dell'Aglio
 
An experience on empirical research about rdf stream
An experience on empirical research about rdf streamAn experience on empirical research about rdf stream
An experience on empirical research about rdf streamDaniele Dell'Aglio
 
RDF Stream Processing Models (RSP2014)
RDF Stream Processing Models (RSP2014)RDF Stream Processing Models (RSP2014)
RDF Stream Processing Models (RSP2014)Daniele Dell'Aglio
 
IMaRS - Incremental Materialization for RDF Streams (SR4LD2013)
IMaRS - Incremental Materialization for RDF Streams (SR4LD2013)IMaRS - Incremental Materialization for RDF Streams (SR4LD2013)
IMaRS - Incremental Materialization for RDF Streams (SR4LD2013)Daniele Dell'Aglio
 
RDF Stream Processing Models (SR4LD2013)
RDF Stream Processing Models (SR4LD2013)RDF Stream Processing Models (SR4LD2013)
RDF Stream Processing Models (SR4LD2013)Daniele Dell'Aglio
 
Ontology based top-k query answering over massive, heterogeneous, and dynamic...
Ontology based top-k query answering over massive, heterogeneous, and dynamic...Ontology based top-k query answering over massive, heterogeneous, and dynamic...
Ontology based top-k query answering over massive, heterogeneous, and dynamic...Daniele Dell'Aglio
 
On correctness in RDF stream processor benchmarking
On correctness in RDF stream processor benchmarkingOn correctness in RDF stream processor benchmarking
On correctness in RDF stream processor benchmarkingDaniele Dell'Aglio
 
An Ontological Formulation and an OPM profile for Causality in Planning Appli...
An Ontological Formulation and an OPM profile for Causality in Planning Appli...An Ontological Formulation and an OPM profile for Causality in Planning Appli...
An Ontological Formulation and an OPM profile for Causality in Planning Appli...Daniele Dell'Aglio
 
P&MSP2012 - Version Control Systems
P&MSP2012 - Version Control SystemsP&MSP2012 - Version Control Systems
P&MSP2012 - Version Control SystemsDaniele Dell'Aglio
 

Mais de Daniele Dell'Aglio (20)

Distributed stream consistency checking
Distributed stream consistency checkingDistributed stream consistency checking
Distributed stream consistency checking
 
On web stream processing
On web stream processingOn web stream processing
On web stream processing
 
On a web of data streams
On a web of data streamsOn a web of data streams
On a web of data streams
 
Triplewave: a step towards RDF Stream Processing on the Web
Triplewave: a step towards RDF Stream Processing on the WebTriplewave: a step towards RDF Stream Processing on the Web
Triplewave: a step towards RDF Stream Processing on the Web
 
On unifying query languages for RDF streams
On unifying query languages for RDF streamsOn unifying query languages for RDF streams
On unifying query languages for RDF streams
 
RSEP-QL: A Query Model to Capture Event Pattern Matching in RDF Stream Proces...
RSEP-QL: A Query Model to Capture Event Pattern Matching in RDF Stream Proces...RSEP-QL: A Query Model to Capture Event Pattern Matching in RDF Stream Proces...
RSEP-QL: A Query Model to Capture Event Pattern Matching in RDF Stream Proces...
 
Summary of the Stream Reasoning workshop at ISWC 2016
Summary of the Stream Reasoning workshop at ISWC 2016Summary of the Stream Reasoning workshop at ISWC 2016
Summary of the Stream Reasoning workshop at ISWC 2016
 
On Unified Stream Reasoning - The RDF Stream Processing realm
On Unified Stream Reasoning - The RDF Stream Processing realmOn Unified Stream Reasoning - The RDF Stream Processing realm
On Unified Stream Reasoning - The RDF Stream Processing realm
 
Querying the Web of Data with XSPARQL 1.1
Querying the Web of Data with XSPARQL 1.1Querying the Web of Data with XSPARQL 1.1
Querying the Web of Data with XSPARQL 1.1
 
Augmented Participation to Live Events through Social Network Content Enrichm...
Augmented Participation to Live Events through Social Network Content Enrichm...Augmented Participation to Live Events through Social Network Content Enrichm...
Augmented Participation to Live Events through Social Network Content Enrichm...
 
An experience on empirical research about rdf stream
An experience on empirical research about rdf streamAn experience on empirical research about rdf stream
An experience on empirical research about rdf stream
 
RDF Stream Processing Models (RSP2014)
RDF Stream Processing Models (RSP2014)RDF Stream Processing Models (RSP2014)
RDF Stream Processing Models (RSP2014)
 
IMaRS - Incremental Materialization for RDF Streams (SR4LD2013)
IMaRS - Incremental Materialization for RDF Streams (SR4LD2013)IMaRS - Incremental Materialization for RDF Streams (SR4LD2013)
IMaRS - Incremental Materialization for RDF Streams (SR4LD2013)
 
RDF Stream Processing Models (SR4LD2013)
RDF Stream Processing Models (SR4LD2013)RDF Stream Processing Models (SR4LD2013)
RDF Stream Processing Models (SR4LD2013)
 
Ontology based top-k query answering over massive, heterogeneous, and dynamic...
Ontology based top-k query answering over massive, heterogeneous, and dynamic...Ontology based top-k query answering over massive, heterogeneous, and dynamic...
Ontology based top-k query answering over massive, heterogeneous, and dynamic...
 
On correctness in RDF stream processor benchmarking
On correctness in RDF stream processor benchmarkingOn correctness in RDF stream processor benchmarking
On correctness in RDF stream processor benchmarking
 
An Ontological Formulation and an OPM profile for Causality in Planning Appli...
An Ontological Formulation and an OPM profile for Causality in Planning Appli...An Ontological Formulation and an OPM profile for Causality in Planning Appli...
An Ontological Formulation and an OPM profile for Causality in Planning Appli...
 
P&MSP2012 - Maven
P&MSP2012 - MavenP&MSP2012 - Maven
P&MSP2012 - Maven
 
P&MSP2012 - Version Control Systems
P&MSP2012 - Version Control SystemsP&MSP2012 - Version Control Systems
P&MSP2012 - Version Control Systems
 
P&MSP2012 - Unit Testing
P&MSP2012 - Unit TestingP&MSP2012 - Unit Testing
P&MSP2012 - Unit Testing
 

Último

Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteDianaGray10
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek SchlawackFwdays
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
Training state-of-the-art general text embedding
Training state-of-the-art general text embeddingTraining state-of-the-art general text embedding
Training state-of-the-art general text embeddingZilliz
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfLoriGlavin3
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionDilum Bandara
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxLoriGlavin3
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 

Último (20)

Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test Suite
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
Training state-of-the-art general text embedding
Training state-of-the-art general text embeddingTraining state-of-the-art general text embedding
Training state-of-the-art general text embedding
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdf
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An Introduction
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptx
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 

A Survey of Temporal Extensions of DLs

  • 1. A Survey of Temporal Extensions of DLs Research school: Foundations and Challenges of Change in Ontologies and Databases 2014 Free University of Bozen-Bolzano, Italy Group 6: Daniele Dell’Aglio DEIB – Politecnico di Milano daniele.dellaglio@polimi.it Fariz Darari ` KRDB – Universita di Bolzano fadirra@gmail.com Davide Lanti ` KRDB – Universita di Bolzano davide.lanti.sersante@gmail.com Mentor: Michael Zakharyaschev Birkbeck College Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 1 – 39
  • 2. What we will see The paper: Alessandro Artale and Enrico Franconi. A survey of temporal extensions of description logics. Annals of Mathematics and Artificial Intelligence, 30(1-4):171-210, 2000. Outline: Overview Running Example A Survey on Existing Solutions Current Hot Topics, Future Directions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 2 – 39
  • 3. Outline Overview Running Example A Survey on Existing Solutions State-change based DLs Temporal DLs with internal approach Point-based temporal DLs Interval-based temporal DLs Current Hot Topics, Future Directions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 3 – 39
  • 4. Temporal extensions of DLs How can time be modelled? Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 4 – 39
  • 5. Temporal extensions of DLs How can time be modelled? Point-based notion of time Interval-based notion of time Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 4 – 39
  • 6. Temporal extensions of DLs How can time be modelled? Point-based notion of time Interval-based notion of time How can the temporal dimension be handled? Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 4 – 39
  • 7. Temporal extensions of DLs How can time be modelled? Point-based notion of time Interval-based notion of time How can the temporal dimension be handled? Implicit notion of time: sequences of events through state-change representations Explicit notion of time: definition of temporal operators and new formulae Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 4 – 39
  • 8. Temporal extensions of DLs How can time be modelled? Point-based notion of time Interval-based notion of time How can the temporal dimension be handled? Implicit notion of time: sequences of events through state-change representations Explicit notion of time: definition of temporal operators and new formulae Internal point of view: different states of an individual are modelled as different individual components External point of view: an individual has different states in different moments Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 4 – 39
  • 9. Classification of the DL temporal extensions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 5 – 39
  • 10. Classification of the DL temporal extensions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 5 – 39
  • 11. Classification of the DL temporal extensions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 5 – 39
  • 12. Classification of the DL temporal extensions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 5 – 39
  • 13. Classification of the DL temporal extensions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 5 – 39
  • 14. Outline Overview Running Example A Survey on Existing Solutions State-change based DLs Temporal DLs with internal approach Point-based temporal DLs Interval-based temporal DLs Current Hot Topics, Future Directions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 6 – 39
  • 15. Running example How to become a doctor: Be a PhD student for some years (3-4) Defend a thesis Become a doctor Let’s try to model it with different temporal logics! Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 7 – 39
  • 16. Outline Overview Running Example A Survey on Existing Solutions State-change based DLs Temporal DLs with internal approach Point-based temporal DLs Interval-based temporal DLs Current Hot Topics, Future Directions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 8 – 39
  • 17. C LASP [DL96] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 9 – 39
  • 18. C LASP [DL96] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 9 – 39
  • 19. C LASP [DL96] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 9 – 39
  • 20. C LASP [DL96] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 9 – 39
  • 21. C LASP [DL96] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 9 – 39
  • 22. C LASP [DL96] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 9 – 39
  • 23. C LASP [DL96] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 9 – 39
  • 24. C LASP A system to reason about plans, proposed by Devambu and Litman (first half of 90s) Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 10 – 39
  • 25. C LASP A system to reason about plans, proposed by Devambu and Litman (first half of 90s) Two formalisms The C LASSIC DL to define states, actions, plans and relation among them A set of operators to specify the plan expressions SEQUENCE, LOOP, TEST, OR, . . . The plan expression is converted in a finite automata Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 10 – 39
  • 26. C LASP A system to reason about plans, proposed by Devambu and Litman (first half of 90s) Two formalisms The C LASSIC DL to define states, actions, plans and relation among them A set of operators to specify the plan expressions SEQUENCE, LOOP, TEST, OR, . . . The plan expression is converted in a finite automata C LASP performs Plan subsumption Plan recognition: determines if a scenario belong to a given plan Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 10 – 39
  • 27. C LASP considerations Actions are instantaneous The temporal expressivity of Clasp is implicit in the language Alternatives can be expressed through disjunctions (OR) Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 11 – 39
  • 28. C LASP considerations Actions are instantaneous The temporal expressivity of Clasp is implicit in the language Alternatives can be expressed through disjunctions (OR) Explicit temporal constraints are not expressible The terminological representation of states: is not as expressive as the predicate calculus representation used in STRIPS avoids doing general theorem proving when computing state subsumption Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 11 – 39
  • 29. Outline Overview Running Example A Survey on Existing Solutions State-change based DLs Temporal DLs with internal approach Point-based temporal DLs Interval-based temporal DLs Current Hot Topics, Future Directions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 12 – 39
  • 30. T-R EX [WL92] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 13 – 39
  • 31. T-R EX [WL92] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 13 – 39
  • 32. T-R EX [WL92] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 13 – 39
  • 33. T-R EX [WL92] Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 13 – 39
  • 34. T-R EX A system to represent and reason about plans developed by Weida and Litman (90s) Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 14 – 39
  • 35. T-R EX A system to represent and reason about plans developed by Weida and Litman (90s) Like C LASP, two different formalisms are used The K-R EP or the C LASSIC DLs to describe the actions A temporal constraint network to represent the plans Constraints defined through the Allen’s relationships before, meets, after, finishes, . . . Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 14 – 39
  • 36. T-R EX A system to represent and reason about plans developed by Weida and Litman (90s) Like C LASP, two different formalisms are used The K-R EP or the C LASSIC DLs to describe the actions A temporal constraint network to represent the plans Constraints defined through the Allen’s relationships before, meets, after, finishes, . . . T-R EX performs the following reasoning tasks: subsumption plan recognition: the system determines if a set of observations are compatible with (i.e., could instantiate) the plan set plans are classified in possible, necessary and impossible Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 14 – 39
  • 37. T-R EX considerations T-Rex conceptual model captures the actions States are not represented Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 15 – 39
  • 38. T-R EX considerations T-Rex conceptual model captures the actions States are not represented T-Rex is an example of external notion of time with an internal approach It uses the Allen’s relationships to specify the constraints (explicit notion of time) Plans capture the time notion (internal approach) Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 15 – 39
  • 39. T-R EX considerations T-Rex conceptual model captures the actions States are not represented T-Rex is an example of external notion of time with an internal approach It uses the Allen’s relationships to specify the constraints (explicit notion of time) Plans capture the time notion (internal approach) The plan subsumption is NP-Complete The crux is to determine the mappings between plans Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 15 – 39
  • 40. Time as Concrete Domain [BH91] Idea: Abstract individuals are related to values in a concrete domain .. via features Tuples of concrete values identified by features can be constrained to belong to a predicate over the concrete domain Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 16 – 39
  • 41. Example [AF00] . Poor-Manager = Manager ∀MONTHLY-BALANCE.∃(INCOME, EXPENSES). ≤ INCOME and EXPENSES are features from ∆I to the concrete domain R ≤ is a predicate defined over the concrete domain ∆I R IN ≤ EXP M-B M-B IN ≤ EXP Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 17 – 39
  • 42. ALC(D) [BH91] ALC extended with concrete predicates I I (∃(u1 , . . . , un ).P)I := {a ∈ ∆I | u1 (a), . . . , un (a) ∈ P D } u1 , . . . , un are compositions of features D is called concrete domain Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 18 – 39
  • 43. Running Example Postdoc PHD-STATE : PhD-Student DOC-STATE : (Doctor ¬PhD-Student) ∃(PHD-STATE ◦ HAS-TIME, DOC-STATE ◦ HAS-TIME).meets ∆I Intervals H-T meets P-S D-S H-T Recall: “different states of an individual are modelled as different individuals” Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 19 – 39
  • 44. Considerations ALC(D), ALCF (D) concept satisfiability, subsumption, and ABox consistency PSPACE-complete .. under the assumption that satisfiability in the concrete domain is in PSPACE ALCRP(D) Undecidable Decidability if avoiding the interaction of complex roles with existential and universal restrictions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 20 – 39
  • 45. Outline Overview Running Example A Survey on Existing Solutions State-change based DLs Temporal DLs with internal approach Point-based temporal DLs Interval-based temporal DLs Current Hot Topics, Future Directions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 21 – 39
  • 46. Combining Description Logics and Tense Operators: ALCT [Sch93] Combination of ALC with point-based modal temporal connectives 3P , 2P , cP , UP , UP Time part of the semantic structure AI ⊆ T × ∆I R I ⊆ T × ∆I × ∆I Recall: “an individual has different states at different moments” Temporal connectives can be applied only to concepts 3CtI := {a ∈ ∆I | ∃t . t ≤ t ∧ a ∈ CtI } Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 22 – 39
  • 47. Running Example Every doctor has been a PhD student in the past Doctor 3P PhD-Student Every thesis defender is a PhD student that has been a PhD student in the past Thesis-Defender Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs PhD-Student 3P PhD-Student 23 – 39
  • 48. Running Example Every doctor has been a PhD student in the past Doctor 3P PhD-Student Every thesis defender is a PhD student that has been a PhD student in the past Thesis-Defender Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs PhD-Student 3P PhD-Student 23 – 39
  • 49. Running Example Every doctor has been a PhD student in the past Doctor 3P PhD-Student Every thesis defender is a PhD student that has been a PhD student in the past Thesis-Defender Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs PhD-Student 3P PhD-Student 23 – 39
  • 50. Considerations ALCT Empty Abox Linear, unbounded and discrete time structure PSPACE-complete for statisfiability checking Branching, unbounded and discrete time structure EXPTIME-hard Interval-based time structure Undecidable Open questions (still open?) Extending ALCT (N ) with past tense? Real numbers? Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 24 – 39
  • 51. Outline Overview Running Example A Survey on Existing Solutions State-change based DLs Temporal DLs with internal approach Point-based temporal DLs Interval-based temporal DLs Current Hot Topics, Future Directions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 25 – 39
  • 52. Interval-based Temporal DLs Schmiedel’s Formalism Idea Examples The Undecidable Realm Idea Examples Towards Decidable Logic Idea Examples Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 26 – 39
  • 53. Interval-based Temporal DLs: Characteristics Interval-based Explicit, eg: alltime, 3TE Follows the external approach, eg: C i, a for temporal concept assertions and R i, a, b for temporal role assertions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 27 – 39
  • 54. Schmiedel’s Formalism: Idea The first of such an interval-based temporal DL (made in 1990) Underlying DL = F LEN R− (no on roles, and role conjunction) , ⊥, ¬, but with cardinality restrictions Temporal operators = at, alltime, sometime Subsumption is argued to be undecidable Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 28 – 39
  • 55. Schmiedel’s Formalism: Examples Concept: PhD students during 1993 (at 1993 PhDStudent) Terminological Axiom: Doctors were PhD students Doctor (sometime(x)(metBy now x).(at x (PhDStudent))) Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 29 – 39
  • 56. The Undecidable Realm: Idea Developed by Bettini Variable-free extension with existential and universal temporal quantification Arbitrary relationships between more than two intervals can’t be represented Satisfiability and subsumption are undecidable Starting from the DL ALCN Two concept constructors: 3TE.C and 2TE.C Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 30 – 39
  • 57. The Undecidable Realm: Examples Concept: Persons who become a doctor sometime 3after.Doctor , eg: 1990, michael belongs to this, if 1992, michael belongs to Doctor Terminological Axiom: Doctors were PhD students Doctor 3(metBy).PhDStudent Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 31 – 39
  • 58. Towards Decidable Logics: Idea Developed by Artale and Franconi Decidable: Expressivity is reduced, universal quantification on temporal variables has been eliminated Underlying DL (most expressive): T L-ALCF Temporal variables are introduced by the temporal existential quantifier 3, excluding the predefined temporal var # Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 32 – 39
  • 59. Towards Decidable Logics: Examples Terminological Axiom: Doctors were PhD students Doctor 3(x)(# metBy x).PhDStudent@x Terminological Axiom: PhD thesis defenders finish their PhDs PhDThesisDefender 3(x)(# finishes x).PhDStudent@x Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 33 – 39
  • 60. Outline Overview Running Example A Survey on Existing Solutions State-change based DLs Temporal DLs with internal approach Point-based temporal DLs Interval-based temporal DLs Current Hot Topics, Future Directions Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 34 – 39
  • 61. Hot Topics: Temporal DLs for OBDA OBDA over temporal data with validity time Ontologies capable of temporal conceptual modeling Developed TQL extending OWL 2 QL, still preserving FO rewritability Example: A fact with its validity time: givesBirth(diana, michael, 1970) A temporal axiom: 3p givesBirth Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs motherOf 35 – 39
  • 62. Hot Topics: Stream Query Processing Query language for RDF streams Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 36 – 39
  • 63. A Survey of Temporal Extensions of DLs Research school: Foundations and Challenges of Change in Ontologies and Databases 2014 Free University of Bozen-Bolzano, Italy Group 6: Daniele Dell’Aglio DEIB – Politecnico di Milano daniele.dellaglio@polimi.it Fariz Darari ` KRDB – Universita di Bolzano fadirra@gmail.com Davide Lanti ` KRDB – Universita di Bolzano davide.lanti.sersante@gmail.com Mentor: Michael Zakharyaschev Birkbeck College Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 37 – 39
  • 64. [AF00] Alessandro Artale and Enrico Franconi. A survey of temporal extensions of description logics. Annals of Mathematics and Artificial Intelligence, 30(1-4):171–210, 2000. [BH91] Franz Baader and Philipp Hanschke. A scheme for integrating concrete domains into concept languages. In Proceedings of the 12th International Joint Conference on Artificial Intelligence - Volume 1, IJCAI’91, pages 452–457, San Francisco, CA, USA, 1991. Morgan Kaufmann Publishers Inc. [DL96] Premkumar T. Devanbu and Diane J. Litman. Taxonomic plan reasoning. Artif. Intell., 84(1-2):1–35, 1996. [Sch93] Klaus Schild. Combining terminological logics with tense logic. ˜ In Miguel Filgueiras and LuAs Damas, editors, Progress in Artificial Intelligence, volume 727 of Lecture Notes in Computer Science, pages 105–120. Springer Berlin Heidelberg, 1993. Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 38 – 39
  • 65. [WL92] Robert A. Weida and Diane J. Litman. Terminological reasoning with constraint networks and an application to plan recognition. In Bernhard Nebel, Charles Rich, and William R. Swartout, editors, KR, pages 282–293. Morgan Kaufmann, 1992. Daniele Dell’Aglio, Fariz Darari and Davide Lanti A Survey of Temporal Extensions of DLs 39 – 39