DLDB2: A Scalable MultiPerspective Semantic Web Repository

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DLDB2 A Scalable Multi-Perspective Semantic Web
Repository

• Zhengxiang Pan, Xingjian Zhang and Jeff Heflin

Presented on Web Intelligence (WI08) December
11th, 2008
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Overview

• We present a Semantic Web Knowledge Base System
  that scales both in terms of number of ontologies
  and quantity of data. It also supports reasoning
  from different view points.
• By delegating TBox reasoning to a DL reasoner, we
  focus on the design of the table schema, database
  views, and algorithms that achieve essential ABox
  reasoning over an RDBMS.
• We evaluate the performance using benchmarks and
  real world data from multiple sources.

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Ontology perspectives

• There may not be a universal model of all the
  data sources and ontologies on the web
• Extremely unlikely that one could exist (e.g.
  inconsistency)
• Instead, we should allow different viewpoints and
  contexts, which are supported by different
  ontologies
• Each perspective is based on an ontology
• An ontology provides a shared context
• Data sources that commit to the same ontology
  implicitly agreed to share a context
• When it makes sense, data that commit to
  different ontologies can be included to maximize
  integration

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Ontology perspectives -cont

• Theoretically, each perspective represents a
  certain view of the world, and could be
  considered a knowledge base.
• The answer to a semantic web query must be
  relative to a specific perspective
• A mapping ontology between a sequence of
  ontologies Oi ,..., On introduces no vocabulary
  of its own but extends Oi ,..., On and contains
  the axioms that map their vocabularies.

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Integration using perspectives
Car
Automobile
O1
O2
commits to
commits to
ce7334?O1Automobile
imports
ezz3290?O1Car
O1Car(x) ? O2Automobile(x)
Om12
O1Car(x) ? O2Automobile(x)
Om12
?ltO1 , car(x)gt ? ezz3290 ?ltO2 , automobile(x)gt
? ce7334 ?ltOm12 , car(x)gt ? ezz3290,
ce7334 ?ltOm12 , automobile(x)gt ? ezz3290,
ce7334
?ltOm12 , car(x)gt ? ezz3290 ?ltOm12 ,
automobile(x)gt ? ezz3290, ce7334
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DLDB2 System

• A knowledge base system
• extends relational databases with partial OWL
  reasoning capabilities
• Uses DL reasoner to precompute subsumptions
• Architecture

• The components are loosely coupled
• Any DIG compliant reasoner
• Any SQL compliant RDBMS with JDBC driver
• Reasoning services and databases can be
  distributed on different machines or clustered on
  multiple machines

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Table Design
schema-aware and decompositional
1Student
Ontologies_Index
SeqNum
URL
SeqNum
URL
1
http//www.lehigh.edu/zhp2/univ
-
bench.owl
1
http//www.lehigh.edu/zhp2/univ
-
bench.owl
Source_Index
SeqNum
URL
SeqNum
URL
1
http//www.lehigh.edu/zhp2/univ
-
bench.owl
1
http//www.lehigh.edu/zhp2/univ
-
bench.owl
2
http//www.lehigh.edu/ubdata/univ0_0.owl
2
http//www.lehigh.edu/ubdata/univ0_0.owl
1TakesCourse
URI_Index
ID
URI
ID
URI
1
http//www.Dept0.Univ0.edu/UndergraduateStudent121
1
http//www.Dept0.Univ0.edu/UndergraduateStudent121
2
http//www.Dept0.Univ0.edu/GraduateCourse9
2
http//www.Dept0.Univ0.edu/GraduateCourse9
3
http//www.Dept0.Univ0.edu/GraduateStudent123
3
http//www.Dept0.Univ0.edu/GraduateStudent123
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Inference
Load ontology
Load data
Data
Ontology
Student ? Person who takes a Course GraduateStud
ent ? Person who takes a GraduateCourse GraduateCo
urse ? Course
Find individual equivalence
DL Reasoner
Graduate Student ? Student
resolve individual equivalence
Inferred Hierarchy
Compute Transitive Closure
CREATE VIEW 1Student_1_view AS SELECT FROM
1Student where onto1 UNION SELECT FROM
1UndergraduateStudent_1_view UNION SELECT FROM
1GraduateStudent_1_view
table view creation
Store in database tables
Database operation
sequences numbers of the ontologies being both
ancestors of current ontology O and descendants
of the ontology that defines the term
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Query Answering
Query Interface application
http//swat.cse.lehigh.edu/ubmap.owl SELECT
?XWHERE ?X rdftype GraduateStudent. ?X
takesCourse lthttp//foo.edu/course0gt.
SPARQL query
Query API
SELECT 1GraduateStudent_2_view.ID FROM
1GraduateStudent_2_view, 1takesCourse_2_view
WHERE 1GraduateStudent_2_view.id
1takesCourse_2_view.subject AND
1takesCourse_2_view.object http//www.foo.edu/d
ept0/course0
Query Translation Algorithm
SQL Sentences
RDBMS
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Benchmark Load Time
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Benchmark Query Time
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Benchmark -Completeness
Completeness on UOBM Lite 5

• DLDB2 is complete on all LUBM queries
• DLDB2 on UOBM
• complete on 10 out of 13 queries
• 2 of the incomplete queries are due to universal
  restrictions. The rest is due to cardinalities
• DLDB2 is complete on a sizable subset of
  Description Horn Logic
• plus more DL inferences on TBox

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Multi-ontology Evaluation -Data
Loaded data sources
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Multi-ontology Evaluation -Load
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Multi-ontology Evaluation -Query

• In our evaluation, we first create the mappings
  between pairs of related ontologies, and then map
  them to popular ontologies like FOAFand Dublin
  Core.
• Totally, we created 16 mappings with 46 axioms.
  We also created 4 common perspectives such as
  academic and e-government each perspective
  extends (imports) some mappings of interest.
• Additionally, we created 169,023 owlsameAs
  statements to map URIs from different sources but
  refer to the same individual.

Query performance
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Future work

• Support efficient updates on documents
• Keep the data fresh
• Improve query performance
• Utilize query optimization techniques
• Prove the completeness of the system
• Formally define the language that the system is
  complete on

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Thank you

• Questions?