Computer Languages and Computing Science Department
University of Malaga
Spain
A Survey on Disk Oriented Querying and
Reasoning on the Semantic Web
María del Mar Roldán , José F. Aldana
Spanish junior researchers fight for employment rights
http://khaos.uma.es
We need (efficient and scalable) TOOLS for
storing and querying OWL ontologies
Databases
DL Systems
Integration not trivial
Study how different logical and physical
(persistent) storage models influence on the
querying and reasoning
mechanisms performance
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
2
Objectives
• Describing seven systems (SESAME, JENA, KAON,
KOWARI, DLDB, DLP-IM, IS) which uses database
technology to both represent knowledge persistently and
query this knowledge in the Semantic Web context.
• According to four features
• Ontology definition language
• Storage model
• Query language
• Reasoning mechanisms
• Obtaining conclusions and needs
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
3
Evaluation Framework (I)
1. Ontology Definition Language
1.1 Language used
(expressiveness for representing
knowledge)
2.1 Storage Technology
2. Storage Model
(Tbox and Abox Storage)
2.2 Specific physical representation
2.3 Access paths (idexes)
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
4
Evaluation Framework (II)
3.1 Type of queries allowed
(language expressiveness)
3. Query language
3.2 Scalability and efficiency in
massive storage
3.3 Distribution
4.1 Tbox reasoning mechanisms
4. Reasoning Mechanisms
4.2 Abox reasoning mechanisms
4.3 reasoning mechanisms
implementation
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
5
Ontology Definition Language
• From RDF to OWL
SESAME
JENA
KAON
KOWARI
DLDB
DLP-IM
IS
RDF
RDF
RDF +
extensions =
Part of OWL
expressiveness.
RDF
OWL
OWL subset
OWL
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
6
Storage Model
• Databases without specific physical
representation and access paths.
SESAME
JENA
KAON
KOWARI
DLDB
DLP-IM
IS
Object
Relational DB
+ Relational
DB
Relational
DB
Relational DB
Java database
+ AVL
indexes
Relational DB
Deductive
Database
Relational DB
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
7
Query language
• Usually translated to SQL or Datalog
• No distribution
SESAME
JENA
KAON
KOWARI
DLDB
DLP-IM
IS
RDQL  API
SeRQL  API
RDQL  API
KAONQL
 Datalog
iTQL
OWL  SQL
Datalog
OWL  SQL
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
8
Reasoning Mechanisms (Tbox)
• Concept subsumption
• No implementation homogeneity
SESAME
JENA
KAON
KOWARI
DLDB
DLP-IM
IS
Concept
Subsumption
Concept
Subsumption
Those that
can be
translated to
Datalog
Concept
Subsumption
Fact
mechanisms
Those that
can be
translated to
Datalog
NO
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
9
Reasoning Mechanisms (Abox)
• Instances Retrieval
• No implementation homogeneity
SESAME
JENA
KAON
KOWARI
DLDB
DLP-IM
IS
IR +
domain/range of
properties
IR
Generic rule
reasoner +
incomplete
owl lite
reasoner
(JENA2)
Transitive and
symmetric
properties
IR
IR
Those that
can be
implemented
by Datalog
rules
IR
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
10
Current tools
(Using database technology)
Databases as
instances warehouses
Our Proposal
Select the best logical
model
Simple logical
models
No physical
representation of the
knowledge
Select the best physical
storage structures and
indexes
Few reasoning
mechanisms
(subsumption) and
simple query
languages
Implement complex
reasoning mechanisms
and query language
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
11
Current tools (Using database technology)
Databases as
instances warehouses
Select the best logical
model
Simple logical models
No physical
representation of the
knowledge
Select the best physical
storage structures and
indexes
Few reasoning
mechanisms
(subsumption) and
simple query languages
Implement complex
reasoning mechanisms
and query language
In general (for all OWL ontologies)
Methodology
For some specific applications (biology)
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
12
How to proceed (Future tends)
• Defining complex reasoning mechanisms
• Defining our query language: complex concepts +
conjunctive queries
• Implementing the reasoning mechanisms and the
query language using several persistent storage
models (relational databases, logical databases,
XML databases…)
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
13
How to proceed (Future tends)
• Designing different physical storage for the
previous models
• Getting performance measures and doing analysis
• Obtaining conclusions and using them to define a
set of recommendations/methodology
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
14
Problems….
• Technical Problems:
•Complexity of the language (DL formalism)
•No good OWL parser
• BIG QUESTIONS TO DEAL WITH:
•Face OWA-CWA impedance mismatch in the query
language
•Analyze (New) Trade-offs between expressiveness and
efficiency (when reasoning in secondary memory)
01/07/2016
Semantic Web and Databases 2006
María del Mar Roldán-Garcia
15
Computer Languages and Computing Science Department
University of Malaga
Spain
A Survey on Disk Oriented Querying and
Reasoning on the Semantic Web
María del Mar Roldán , José F. Aldana
Spanish junior researchers fight for employment rights
http://khaos.uma.es