These are the slides corresponding to the presentation done at ISWC 2013 in Sydney, for the paper with the same title. Remember to check the main URL: http://j.mp/benchmarkqueryrewriting
Generative Artificial Intelligence: How generative AI works.pdf
Towards a systematic benchmarking of ontology-based query rewriting systems
1. Introduction
State of the art
Analysis
Results
Conclusions
References
T OWARDS A SYSTEMATIC BENCHMARKING OF
ONTOLOGY- BASED QUERY REWRITING SYSTEMS
´
Jos´ Mora and Oscar Corcho
e
{jmora, ocorcho}@fi.upm.es
http://j.mp/benchmarkqueryrewriting
Sydney - October 25, 2013
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
1 / 21
2. Introduction
State of the art
Analysis
Results
Conclusions
References
WARNING
Before we start:
This is an evaluation paper
There are many acronyms, sorry for that...
Extensive state of the art, short slides
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
2 / 21
3. Introduction
State of the art
Analysis
Results
Conclusions
References
I NDEX
1
I NTRODUCTION
2
S TATE OF THE ART
3
A NALYSIS
4
R ESULTS
5
C ONCLUSIONS
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
3 / 21
4. Introduction
State of the art
Analysis
Results
Conclusions
References
OBDA I DEA
query
jmora@fi.upm.es
ontology
Evaluating OBDA query rewriting
data source
Sydney - October 25, 2013
4 / 21
5. Introduction
State of the art
Analysis
Results
Conclusions
References
A PPROACH
query
ontology
rewritten
query
jmora@fi.upm.es
REWRITING
data source
Evaluating OBDA query rewriting
Sydney - October 25, 2013
5 / 21
6. Introduction
State of the art
Analysis
Results
Conclusions
References
E XAMPLE
query
Q(x) <- Person(x)
REWRITING
rewritten
query
ontology
Student
Person
Q(x) <- Person(x)
Q(x) <- Student(x)
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
6 / 21
7. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONTEXT
ontology
REWRITING
rewritten
query
translated
results
jmora@fi.upm.es
Evaluating OBDA query rewriting
translated
query
data source
query
translation
query
execution
translation
results
Sydney - October 25, 2013
7 / 21
8. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONTEXT
ontology
REWRITING
rewritten
query
translated
results
jmora@fi.upm.es
Evaluating OBDA query rewriting
translated
query
data source
query
translation
query
execution
translation
results
Sydney - October 25, 2013
7 / 21
9. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONTEXT
ontology
REWRITING
rewritten
query
translated
results
jmora@fi.upm.es
Evaluating OBDA query rewriting
translated
query
data source
query
translation
query
execution
translation
results
Sydney - October 25, 2013
7 / 21
10. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONTEXT
rewritten
query
translation
translated
query
EBox
data source
query
execution
translated
results
jmora@fi.upm.es
REWRITING
query
ontology
translation
results
Evaluating OBDA query rewriting
Sydney - October 25, 2013
7 / 21
11. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONTEXT
rewritten
query
translation
translated
query
Mappings
data source
query
execution
translated
results
jmora@fi.upm.es
REWRITING
query
ontology
ontology
ontology
ontology
translation
results
Evaluating OBDA query rewriting
Sydney - October 25, 2013
7 / 21
12. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONTEXT
ontology
REWRITING
rewritten
query
to analyse
jmora@fi.upm.es
translated
results
Evaluating OBDA query rewriting
translated
query
data source
query
translation
query
execution
translation
results
Sydney - October 25, 2013
7 / 21
13. Introduction
State of the art
Analysis
Results
Conclusions
References
F OCUSING
query
REWRITING
ontology
rewritten
query
to analyse
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
8 / 21
14. Introduction
State of the art
Analysis
Results
Conclusions
References
Horn
-S H I
g ±2
Data
lo
IO ¬
E LH
Rapi
d’s
iteR
DL-L
iteF
DL-L
axiom1
B1 B2 , B1 ¬B2 3
≥ 2R1 ⊥
R1 R2 , R1 ¬R2
B1 ∃R1 , ∃R1 B1
B1 ∃R1 .B2
∃R1 .B1 B2
B1 B2 B3
{a} B, B {a}, B(a)
n-ary predicates
trans(R1 )
B1 ∀R1 .B2 , B1 ≤ 1R1 .B2
DL-L
logic
iteco
r
e
Q
L OGICS
1 here
Bi represents a basic concept and Rj a role that may be basic or inverted.
implemented in Nyaya
3 note that some systems implementing negation assume a consistent ABox
2 as
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
9 / 21
15. Introduction
State of the art
Analysis
Results
Conclusions
References
S YSTEMS
System
Quonto
REQUIEM
Presto
Rapid
Nyaya
Venetis’
Prexto
Clipper
kyrie
4 Close
Input
DL-LiteR
ELHIO¬
DL-LiteR
DL-LiteR 4
Datalog±
DL-LiteR
DL-LiteR and EBox
Horn-SHIQ
ELHIO¬
to OWL2 QL, B1
jmora@fi.upm.es
Output
UCQ
Datalog or UCQ
Datalog
Datalog or UCQ
UCQ
UCQ
Datalog or UCQ
Datalog
Datalog or UCQ
Reference
Calvanese et al. (2007)
P´ rez-Urbina et al. (2009)
e
Rosati and Almatelli (2010)
Chortaras et al. (2011)
Gottlob et al. (2011)
Venetis et al. (2011)
Rosati (2012)
Eiter et al. (2012)
Mora and Corcho (2013)
∃R.B2 axioms are supported
Evaluating OBDA query rewriting
Sydney - October 25, 2013
10 / 21
16. Introduction
State of the art
Analysis
Results
Conclusions
References
G OALS
We analyse this context and available assets to
1. obtain a set of dimensions
2. describe current evaluations, systems and user needs
3. facilitate the construction and expansion of benchmarks
4. choose the system that addresses best one or several given use cases
5. detect the most relevant limitations in the state of the art and
6. address these limitations
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
11 / 21
17. Introduction
State of the art
Analysis
Results
Conclusions
References
G OALS
We analyse this context and available assets to
1. obtain a set of dimensions
2. describe current evaluations, systems and user needs
3. facilitate the construction and expansion of benchmarks
4. choose the system that addresses best one or several given use cases
5. detect the most relevant limitations in the state of the art and
6. address these limitations
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
11 / 21
18. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
19. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
20. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
21. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
22. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
23. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
24. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
25. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
26. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
27. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
28. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
29. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
30. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
31. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
32. Introduction
State of the art
Analysis
Results
Conclusions
References
D IMENSIONS
Expressiveness in tests: traditionally DL-LiteR
Most expressive logic in the intersection of all systems
Systems that handle more expressive logics cannot show their full potential
Expressiveness lost in translation to Datalog
How expressive are the ontologies for OBDA?
Consequences of not covered expressiveness on precision and completeness
Output complexity: apples, oranges and pears
How to compare UCQs and Datalog programs?
Characteristics of the system that is going to execute them
Input complexity: treat with care
What kind of queries can be processed?
What kind of queries do we want to process?
Additional inputs: to each one its own
EBox, cache of previous queries, etc.
Comparison among systems and comparison with RealityTM
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
12 / 21
33. Introduction
State of the art
Analysis
Results
Conclusions
References
A SSETS
Several assets used for evaluation5
Usual ontologies (A, AX, P1, P5, P5X, S, U, UX, V)
Not so usual ontologies (core, galen-lite)
New ontologies (AXE, AXEb, P5XE, UXE)
Usually with 5 queries, but up to 9 in some cases
5 available
here: http://j.mp/benchmarkqueryrewriting
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
13 / 21
34. Introduction
State of the art
Analysis
Results
Conclusions
References
A SSETS
Several assets used for evaluation5
Usual ontologies (A, AX, P1, P5, P5X, S, U, UX, V)
Not so usual ontologies (core, galen-lite)
New ontologies (AXE, AXEb, P5XE, UXE)
Usually with 5 queries, but up to 9 in some cases
5 available
here: http://j.mp/benchmarkqueryrewriting
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
13 / 21
35. Introduction
State of the art
Analysis
Results
Conclusions
References
A SSETS
Several assets used for evaluation5
Usual ontologies (A, AX, P1, P5, P5X, S, U, UX, V)
Not so usual ontologies (core, galen-lite)
New ontologies (AXE, AXEb, P5XE, UXE)
Usually with 5 queries, but up to 9 in some cases
5 available
here: http://j.mp/benchmarkqueryrewriting
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
13 / 21
36. Introduction
State of the art
Analysis
Results
Conclusions
References
A SSETS
Several assets used for evaluation5
Usual ontologies (A, AX, P1, P5, P5X, S, U, UX, V)
Not so usual ontologies (core, galen-lite)
New ontologies (AXE, AXEb, P5XE, UXE)
Usually with 5 queries, but up to 9 in some cases
5 available
here: http://j.mp/benchmarkqueryrewriting
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
13 / 21
37. Introduction
State of the art
Analysis
Results
Conclusions
References
A SSETS
Several assets used for evaluation5
Usual ontologies (A, AX, P1, P5, P5X, S, U, UX, V)
Not so usual ontologies (core, galen-lite)
New ontologies (AXE, AXEb, P5XE, UXE)
Usually with 5 queries, but up to 9 in some cases
5 available
here: http://j.mp/benchmarkqueryrewriting
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
13 / 21
38. Introduction
State of the art
Analysis
Results
Conclusions
References
E XPERIMENTAL SETUP
Intel Core2 6300@1.86GHz, 2GB of RAM
Running queries 5 times, results averaged
Cold runs of the systems
Measuring the time for the rewriting
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
14 / 21
43. Introduction
State of the art
Analysis
Results
Conclusions
References
R E - FOCUSING
query
REWRITING
ontology
rewritten
query
to analyse
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
17 / 21
44. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
45. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
46. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
47. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
48. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
49. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
50. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
51. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
52. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
53. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
54. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
55. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
56. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS I
A benchmark should consider how the input represents reality wrt:
queries
syntax (=, COUNT, MAX, ...)
expressiveness (CQ, UCQ, comparisons, arithmetic operations, ...)
shape (star shaped, linear, cyclic, ...)
size (number of atoms, number of clauses, triples...)
ontologies
expressiveness (from DL-LiteR to...)
shape (flat, hierarchical, cyclic ...)
size (number of concepts, properties, individuals, ...)
Additional information
mappings
ABox dependencies / EBox
caching for several queries
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
18 / 21
57. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS II
A benchmark should consider what the output means wrt:
Shape of rewritten queries
expressiveness
types of clauses
syntax with special characteristics
Size of rewritten queries
number of clauses
number of atoms (and distinct atoms)
number of joins
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
19 / 21
58. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS II
A benchmark should consider what the output means wrt:
Shape of rewritten queries
expressiveness
types of clauses
syntax with special characteristics
Size of rewritten queries
number of clauses
number of atoms (and distinct atoms)
number of joins
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
19 / 21
59. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS II
A benchmark should consider what the output means wrt:
Shape of rewritten queries
expressiveness
types of clauses
syntax with special characteristics
Size of rewritten queries
number of clauses
number of atoms (and distinct atoms)
number of joins
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
19 / 21
60. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS II
A benchmark should consider what the output means wrt:
Shape of rewritten queries
expressiveness
types of clauses
syntax with special characteristics
Size of rewritten queries
number of clauses
number of atoms (and distinct atoms)
number of joins
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
19 / 21
61. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS II
A benchmark should consider what the output means wrt:
Shape of rewritten queries
expressiveness
types of clauses
syntax with special characteristics
Size of rewritten queries
number of clauses
number of atoms (and distinct atoms)
number of joins
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
19 / 21
62. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS II
A benchmark should consider what the output means wrt:
Shape of rewritten queries
expressiveness
types of clauses
syntax with special characteristics
Size of rewritten queries
number of clauses
number of atoms (and distinct atoms)
number of joins
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
19 / 21
63. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS II
A benchmark should consider what the output means wrt:
Shape of rewritten queries
expressiveness
types of clauses
syntax with special characteristics
Size of rewritten queries
number of clauses
number of atoms (and distinct atoms)
number of joins
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
19 / 21
64. Introduction
State of the art
Analysis
Results
Conclusions
References
C ONCLUSIONS II
A benchmark should consider what the output means wrt:
Shape of rewritten queries
expressiveness
types of clauses
syntax with special characteristics
Size of rewritten queries
number of clauses
number of atoms (and distinct atoms)
number of joins
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
19 / 21
65. Introduction
State of the art
Analysis
Results
Conclusions
References
R EFERENCES I
Diego Calvanese, Giuseppe De Giacomo, Domenico Lembo, Maurizio Lenzerini, and Riccardo Rosati. Tractable reasoning and efficient query answering in
description logics: The DL-Lite family. Journal of Automated Reasoning, 39(3):385–429, October 2007. doi: 10.1007/s10817- 007- 9078- x. URL
http://dx.doi.org/10.1007/s10817- 007- 9078- x.
Alexandros Chortaras, Despoina Trivela, and Giorgos Stamou. Optimized query rewriting for OWL 2 QL. In Nikolaj Bjørner and Viorica
Sofronie-Stokkermans, editors, Automated Deduction – CADE-23, volume 6803, pages 192–206. Springer Berlin Heidelberg, Berlin, Heidelberg, 2011.
ISBN 978-3-642-22437-9. URL http://www.springerlink.com/content/g8153m783k638210/.
Thomas Eiter, Magdalena Ortiz, Mantas vSimkus, Trung-Kien Tran, and Guohui Xiao. Query rewriting for horn-SHIQ plus rules. In Proc. of the 26th AAAI
Conference on Artificial Intelligence, AAAI, 2012. URL
http://www.aaai.org/ocs/index.php/AAAI/AAAI12/paper/viewPDFInterstitial/4931/5263.
Georg Gottlob, Giorgio Orsi, and Andreas Pieris. Ontological queries: Rewriting and optimization (extended version). arXiv:1112.0343, December 2011.
URL http://arxiv.org/abs/1112.0343.
Jose Mora and Oscar Corcho. Engineering optimisations in query rewriting for OBDA. In Proceedings of the 9th International Conference on Semantic Systems,
ICPS, pages 41–48, Graz, Austria, September 2013. ACM.
H´ ctor P´ rez-Urbina, Ian Horrocks, and Boris Motik. Efficient query answering for OWL 2. In The Semantic Web - ISWC 2009, volume 5823 of Lecture Notes in
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Computer Science, pages 489–504. Springer, 2009. URL http://dx.doi.org/10.1007/978- 3- 642- 04930- 9_31.
Riccardo Rosati. Prexto: Query rewriting under extensional constraints in DL-Lite. In Elena Simperl, Philipp Cimiano, Axel Polleres, Oscar Corcho, and
Valentina Presutti, editors, The Semantic Web: Research and Applications, volume 7295 of Lecture Notes in Computer Science, pages 360–374. Springer Berlin
/ Heidelberg, 2012. ISBN 978-3-642-30283-1. URL http://www.springerlink.com/content/1j61g52j78525175/abstract/.
Riccardo Rosati and Alessandro Almatelli. Improving query answering over DL-Lite ontologies. In Fangzhen Lin, Ulrike Sattler, and Miroslaw
Truszczynski, editors, Proceedings of the Twelfth International Conference on the Principles of Knowledge Representation and Reasoning. AAAI Press, 2010. URL
http://dblp.uni- trier.de/db/conf/kr/kr2010.html.
T. Venetis, G. Stoilos, and G. Stamou. Query rewriting under query extensions for OWL 2 QL ontologies. In The 7th International Workshop on Scalable
Semantic Web Knowledge Base Systems (SSWS 2011), page 59, 2011. URL
http://iswc2011.semanticweb.org/fileadmin/iswc/Papers/Workshops/SSWS/SSWS2011- Proceedings.pdf.
jmora@fi.upm.es
Evaluating OBDA query rewriting
Sydney - October 25, 2013
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66. Introduction
State of the art
Analysis
Results
Conclusions
References
T OWARDS A SYSTEMATIC BENCHMARKING OF
ONTOLOGY- BASED QUERY REWRITING SYSTEMS
´
Jos´ Mora and Oscar Corcho
e
{jmora, ocorcho}@fi.upm.es
http://j.mp/benchmarkqueryrewriting
Sydney - October 25, 2013
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