Presentation on theme: "Rajashree Deka Tetherless World Constellation Rensselaer Polytechnic Institute."— Presentation transcript:
Rajashree Deka Tetherless 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.
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.
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.
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.
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.
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.
D2RQ mapping language formally defined by http://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.
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".
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.
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.
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
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.
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.
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.
Prof. Peter Fox Patrick West Eric Rozell Ankesh Khandelwal Evan Patton