Handling time in RDF Claudio Gutierrez (Joint work with C. Hurtado - - PowerPoint PPT Presentation

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Handling time in RDF Claudio Gutierrez (Joint work with C. Hurtado - - PowerPoint PPT Presentation

Handling time in RDF Claudio Gutierrez (Joint work with C. Hurtado and A. Vaisman) Department of Computer Science Universidad de Chile UPM, Madrid, January 2009 Time in RDF p. 1/15 Outline Introducing time into RDF Temporal RDF


slide-1
SLIDE 1

Handling time in RDF

Claudio Gutierrez (Joint work with C. Hurtado and A. Vaisman)

Department of Computer Science Universidad de Chile

UPM, Madrid, January 2009

Time in RDF – p. 1/15

slide-2
SLIDE 2

Outline

  • Introducing time into RDF
  • Temporal RDF Graphs
  • Semantics of Temporal RDF Graphs
  • Syntax for Temporal Graphs
  • Querying Time in RDF

Time in RDF – p. 2/15

slide-3
SLIDE 3

Introducing time into RDF

  • Student
  • Grad

subC

  • UnderGrad

subC

  • M.Sc

subC

  • John

type

  • Time in RDF – p. 3/15
slide-4
SLIDE 4

Introducing time into RDF

  • Student
  • Grad

subC

  • UnderGrad

subC

  • Ph.D

subC

  • M.Sc

subC

  • John

type

  • Time in RDF – p. 3/15
slide-5
SLIDE 5

Introducing time into RDF

  • Student
  • Grad

subC

  • UnderGrad

subC

  • Ph.D

subC

  • M.Sc

subC

  • John

type

  • Time in RDF – p. 3/15
slide-6
SLIDE 6

Temporal Graph

  • Student
  • Grad

[0,Now]

  • UnderGrad

[0,Now]

  • Ph.D

[3,Now]

  • M.Sc

[0,Now]

  • John

[0,3]

  • [3,4]
  • [4,Now]
  • Time in RDF – p. 4/15
slide-7
SLIDE 7

General Issues

  • Versioning versus Labeling

– Label elements subject to change – Maintain a snapshot of each state of the graph

Time in RDF – p. 5/15

slide-8
SLIDE 8

General Issues

  • Versioning versus Labeling

– Label elements subject to change – Maintain a snapshot of each state of the graph

  • Time Points versus Time Intervals.

[4, 31] = [4] ∪ [5] ∪ · · · ∪ [30] ∪ [31]

Time in RDF – p. 5/15

slide-9
SLIDE 9

General Issues

  • Versioning versus Labeling

– Label elements subject to change – Maintain a snapshot of each state of the graph

  • Time Points versus Time Intervals.

[4, 31] = [4] ∪ [5] ∪ · · · ∪ [30] ∪ [31]

  • Temporal Query Language

– Point based (variables refer to point times) – Interval based (variables refer to intervals)

Time in RDF – p. 5/15

slide-10
SLIDE 10

RDF Intrinsic Issues

  • Notion of temporal Entailment |

  • Ph.D

[2,7] sc

  • sc

[5,7]

  • Grad

[5,9] sc

  • Stud

Time in RDF – p. 6/15

slide-11
SLIDE 11

RDF Intrinsic Issues

  • Notion of temporal Entailment |

  • Ph.D

[2,7] sc

  • sc

[5,7]

  • Grad

[5,9] sc

  • Stud
  • Treatment of temporal Blank Nodes:
  • Student
  • John

[2,3]

  • Mary

[3,5]

  • ?

| =τ

  • Student

X

[2,5]

  • Time in RDF – p. 6/15
slide-12
SLIDE 12

RDF Intrinsic Issues

  • Notion of temporal Entailment |

  • Ph.D

[2,7] sc

  • sc

[5,7]

  • Grad

[5,9] sc

  • Stud
  • Treatment of temporal Blank Nodes:
  • Student
  • John

[2,3]

  • Mary

[3,5]

  • ?

| =τ

  • Student

X

[2,5]

  • Vocabulary for temporal labeling

Time in RDF – p. 6/15

slide-13
SLIDE 13

Definitions

Temporal Triple: an RDF triple with a temporal label, e.g. (a, b, c)[t] Temporal Graph: set of temporal triples Snapshot of graph G at time t:

G(t) = {(a, b, c) : (a, b, c)[t] ∈ G}

Notion of temporal entailment G1 |

=τ G2

Time in RDF – p. 7/15

slide-14
SLIDE 14

Semantics

Ground Case:

G1 | =τ G2 if for each t, G1(t) | = G2(t)

Time in RDF – p. 8/15

slide-15
SLIDE 15

Semantics

Ground Case:

G1 | =τ G2 if for each t, G1(t) | = G2(t)

Non Ground Case:

G1 | =τ G2 if there are ground instances µ1(G1) and µ2(G2) such that for each t: µ1(G1)(t) | =τ µ2(G2)(t)

Time in RDF – p. 8/15

slide-16
SLIDE 16

Semantics

Ground Case:

G1 | =τ G2 if for each t, G1(t) | = G2(t)

Non Ground Case:

G1 | =τ G2 if there are ground instances µ1(G1) and µ2(G2) such that for each t: µ1(G1)(t) | =τ µ2(G2)(t)

  • Proposition. For ground graphs, G1 |

=τ G2 implies G1(t) | = G2(t) for all times t.

Time in RDF – p. 8/15

slide-17
SLIDE 17

Semantics (cont.)

The temporal closure tcl(G) is a maximal set of temporal triples G′ such that: – G′ contains G – G is equivalent to G′ Proposition.

G1 | =τ G2 iff tcl(G1) | =τ G2

  • Proposition. Deciding if G′ is the closure of G is

DP-complete.

Time in RDF – p. 9/15

slide-18
SLIDE 18

Syntax for (a, b, c)[4, 5]

  • Point version

a

  • Y1

Instant

4 c X

tsubj

  • tpred
  • tobj
  • temporal
  • temporal
  • Y2

Instant

5 c

Time in RDF – p. 10/15

slide-19
SLIDE 19

Syntax for (a, b, c)[4, 5]

  • Point version

a

  • Y1

Instant

4 c X

tsubj

  • tpred
  • tobj
  • temporal
  • temporal
  • Y2

Instant

5 c

  • Interval version

a

  • 4

c X

tsubj

  • tpred
  • tobj
  • temporal

Y

Interval

Z

initial

  • final
  • c

5

Time in RDF – p. 10/15

slide-20
SLIDE 20

Syntax (cont.): rules

Rule 1-2: Equivalence betwen point and interval versions Rule 3: Normalization of point-version:

a

  • Y

Instant

4 c X

tsubj

  • tpred
  • tobj
  • temporal
  • temporal

Z

Instant

5 c

Time in RDF – p. 11/15

slide-21
SLIDE 21

Syntax (cont.): rules

Rule 1-2: Equivalence betwen point and interval versions Rule 3: Normalization of point-version:

a

  • 4

c X

tsubj

  • tpred
  • tobj
  • temporal

V

Instant

  • Instant
  • 5

c

Time in RDF – p. 11/15

slide-22
SLIDE 22

Syntax works well

(a, b, c)[m, n] . ( )∗

  • a
  • .

( )∗

  • m

c X

  • temp

Y

Int

Z

init

  • fin
  • c

n

Time in RDF – p. 12/15

slide-23
SLIDE 23

Syntax works well (cont.)

Theorem.

  • 1. G1 |

=τ G2 implies (G1)∗ | = (G2)∗

  • 2. G2 |

= G2 implies (G1)∗ | =τ (G2)∗

  • 3. (G∗)∗ = G and G |

= (G∗)∗

  • Theorem. Let ⊢ be the deductive system formed by RDFS

rules plus Temporal rules. Then:

G1 | =τ G2 iff (G1)∗ ⊢ (G2)∗

Time in RDF – p. 13/15

slide-24
SLIDE 24

Querying Temporal RDF

Proposal: Conjunctive fragment with – interval and point variables – aggregate functions – constructor of graphs for answers

Time in RDF – p. 14/15

slide-25
SLIDE 25

Querying Temporal RDF

Proposal: Conjunctive fragment with – interval and point variables – aggregate functions – constructor of graphs for answers

  • Students who have taken a Master course between year

2000

  • Students taking Ph.D courses together and the time

when this occurred

  • Time intervals when the IT Master program was offered
  • Students applying for jobs at time t after finishing their

Ph.D program in no more than 4 years

Time in RDF – p. 14/15

slide-26
SLIDE 26

What we have:

  • 1. Semantics for Temporal RDF graphs
  • 2. Syntax to incorporate the framework into standard RDF
  • 3. Sound and complete inference rules for temporal graphs
  • 4. Complexity bounds showing temporal RDF preserves

complexity of RDF

  • 5. Sketch of Temporal RDF query language

Time in RDF – p. 15/15