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Ontology materialization from relational database sources using D2RQ. Rajashree Deka Tetherless World Constellation Rensselaer Polytechnic Institute. RDBMS. The majority of data underpinning the Web are stored in Relational Databases (RDB). Advantages: Secure and scalable architecture. - PowerPoint PPT Presentation
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Ontology materialization from relational database
sources using D2RQ
Rajashree DekaTetherless World Constellation
Rensselaer Polytechnic Institute
The majority of data underpinning the Web are stored in Relational Databases (RDB).
Advantages: Secure and scalable architecture. Efficient storage. Reliability.
Disadvantages: Difficult to share data across large organizations
where different database schemata are used. Most importantly, there is no check on
semantics.
RDBMS
Semantic web getting more mature, growing need for RDF applications to access content of legacy databases.
Compared to RDB, RDF is: More expressive. More easily processed and interpreted. Easily reasoned over by software agents.
Need a way to make data in RDBMS available as RDF.
RDBMS to RDF
In order to generate Semantic Web content from a RDB, Tim Berners-Lee proposed a very direct mapping:
Each table in the RDB is a RDF class. Each field (column) name is a RDF property. Each record is a RDF node - an instance of the RDF
class and so can play the role of a subject or an object in a RDF statement.
Mapping data from RDBMS to RDF
Semi-automatic generation of ontology from RDB Read all records, export as RDF triples. Mappings are direct, complex mappings do not usually
appear. Need to convert to RDF regularly. Does not allow the population of an existing
ontology – a BIG limitation!
Map existing RDB to an existing ontology Customize mapping according to existing ontology. Complex mappings can be implemented.
Two Approaches
Provides an integrated environment for accessing the content of non-RDF, relational databases as virtual, read-only RDF graphs.
Using D2RQ we can: Query a non-RDF database using SPARQL queries. Access information in a non-RDF database using the
Jena API or the Sesame API. Access the content of the database as Linked Data
over the Web.
The D2RQ platform
D2RQ mapping language – describes the relation between ontology and RDB
D2RQ engine – uses mappings to rewrite Jena and Sesame API calls to SQL queries.
D2R server - provides a Linked Data view, a HTML view for debugging and a SPARQL Protocol endpoint over the database.
The D2RQ platform
D2R server
D2RQ mapping language formally defined byhttp://www4.wiwiss.fu-berlin.de/bizer/d2rq/0.1/ D2RQ namespace is defined by http://www.wiwiss.fu-berlin.de/suhl/bizer/D2RQ/0.1# Database compatibility:
Oracle MySQL PostgreSQL Microsoft SQL Server ODBC data sources (e.g. Microsoft Access) - mapping
generator and automatic detection of column types do not work.
More about D2RQ
Two command line tools (only on Windows and Unix systems ):
Mapping generator: Analyzes database schema. Generates a default mapping file. Resultant D2RQ map is an RDF document in N3 format. Mapping can be used as-is or can be customized.
Dump script: Writes the content of the RDB into a single RDF file. Supported syntaxes are "RDF/XML" (the default),
"RDF/XML-ABBREV", "N3", "N-TRIPLE".
Command line tools
Ontology is mapped to a database schema using:
d2rq:ClassMaps – Represents a class or a group of similar classes in the ontology. Specifies how instances of the class are identified.
d2rq:PropertyBridges – A ClassMap has a set of PropertyBridges which specify how the properties of an instance are created.
D2RQ mapping – how it works
BCODMO ontology materialization from MySQL database using D2RQ
BCODMO - D2RQ map
# Table dataset (default mapping) map:dataset a d2rq:ClassMap;
d2rq:dataStorage map:database;d2rq:uriPattern "dataset/@@dataset.dataset_id@@";d2rq:class vocab:dataset;d2rq:classDefinitionLabel "dataset";.
map:dataset__label a d2rq:PropertyBridge;d2rq:belongsToClassMap map:dataset;d2rq:property rdfs:label;d2rq:pattern "dataset #@@dataset.dataset_id@@";.
map:dataset_dataset_id a d2rq:PropertyBridge;d2rq:belongsToClassMap map:dataset;d2rq:property vocab:dataset_dataset_id;d2rq:propertyDefinitionLabel "dataset dataset_id";d2rq:column "dataset.dataset_id";d2rq:datatype xsd:int;
# Table dataset (customized mapping)map:dataset a d2rq:ClassMap;
d2rq:dataStorage map:database;d2rq:uriPattern "http://escience.rpi.edu/ontology/BCO-DMO/bcodmo/2/0/DeploymentDatasetCollection_@@dataset.dataset_id@@";d2rq:class bcodmo:DeploymentDatasetCollection;d2rq:classDefinitionLabel "DeploymentDatasetCollection";.
map:seeAlsoStatement a d2rq:PropertyBridge;d2rq:belongsToClassMap map:dataset;
d2rq:property rdfs:seeAlso;d2rq:uriPattern "http://osprey.bcodmo.org/dataset.cfm?id=@@dataset.dataset_id@@&flag=view";.
map:hasIdentifier a d2rq:PropertyBridge;d2rq:property bcodmo:hasIdentifier;d2rq:belongsToClassMap map:dataset;d2rq:column "dataset.dataset_id";d2rq:datatype xsd:int;.
map:dataset_dataset_id a d2rq:PropertyBridge; d2rq:belongsToClassMap map:dataset; d2rq:property bcodmo:hasParameter;
d2rq:refersToClassMap map:parameters; d2rq:propertyDefinitionLabel "dataset dataset_id"; d2rq:join "dataset.dataset_id =
dataset_parameters.dataset_id"; d2rq:join "dataset_parameters.parameters_id =
parameters.parameters_id";.
Excerpt of the mapping file
Customization is very direct in the case where a class in the ontology is represented by a table in the database.
Mapping is complicated or sometimes not possible when a class in the ontology is not a table in the database, but a record in a database table.
Customization of mapping
Define primary keys wherever possible and create indexes.
Indicate directions in d2rq:joins. Set d2rq:autoReloadMapping to false
whenever not needed. Use hint properties:
d2rq:valueMaxLength d2rq:valueRegex d2rq:valueContains
Optimizing D2R’sperformance
Performs reasonably well with basic triple patterns, performance deteriorates when SPARQL features such as OPTIONAL, FILTER and LIMIT are used.
Does not have reasoning capability. Reasoning can be added by using the D2RQ engine within Jena.
Integration of multiple databases or other data sources using D2RQ alone is not possible.
Read-only, cannot perform INSERT, DELETE or UPDATE operations.
Cannot handle complicated database structures like VIEWS.
Limitations
Virtuoso RDF View: Uses table to class and column to predicate
approach. RDB data are represented as virtual RDF
graphs. Customization of mapping possible.
Triplify: Maps HTTP-URI requests to relational database
queries expressed in SQL. No SPARQL support.
Other tools/applications for publishing databases on Semantic Web
R2O: XML based declarative mapping language.
DartGrid Semantic Web toolkit: Provides a visual tool to define mapping.
RDBToOnto User oriented tool that creates static mapping
(RDF dump).Asio Semantic Bridge for Relational Databases
(SBDR) and Automapper: Uses table to class approach.
Tools/Applications continued…
Prof. Peter Fox Patrick West Eric Rozell Ankesh Khandelwal Evan Patton
A note of thanks to…