Sesame A generic architecture for storing and querying RDF and RDFs

1. SesameA generic architecture for storing and querying RDF and RDFs 2008. 12. 08 Written by Jeen Broekstra, Arjohn Kampman Summarized by Gihyun Gong

2. About Sesame project • Developed by IST On-To-Knowledge project that ran from 1999 to 2002 • Focused on Knowledge and Contents Technology, Software Technology • Now, it is further developed and maintained by Aduna in cooperation with NLnet Foundation, developers from Ontotext

3. What is Sesame? • Sesame is an open source Java framework for storing, querying and reasoning with RDF and RDF Schema • It can be used as: • Standalone Server: A database for RDF and RDF Schema • Java Library: For applications that need to work with RDF internally • Sesame is similar to Jena • Supports triple storage • Supports reasoning • Supports Web services

4. Sesame’s Architecture Clients Clients HTTP SOAP HTTP Protocol Handler SOAP Protocol Handler Sesame Admin Module Query Module Export Module Repository Abstraction Layer (RAL) Repository

5. The Repository • DBMSs • Currently, Sesame is able to use • PostgreSQL • MySQL • Oracle (9i or newer) • Existing RDF stores • RDF files • RDF network services • Using multiple sesame server to retrieve results for queries • This opens up the possibility of a highly distributed architecture for RDF storing and querying

6. Repository Abstraction Layer (RAL) • RAL offers stable, high-level interface for talking to repositories • It is defined by an API that offers these functionalities: • Add data • Retrieve data • Delete data • Data is returned in streams (Scalability) • Only small amount of data is kept in memory • Suitable for use in highly constrained environments such as portable devices • Caching data (Performance) • E.g. caching RDF schema data which is needed very frequently

7. Admin Module • Allows inserting or deleting RDF data in repository • Retrieves its information from an RDF(S) source, and parses it using an RDF parser • Checks each (S, P, O) statement for consistency and infers implied information if necessary for instance: • If P equals type, it infers that O must be a class. • If P equals subClassOf, it infers that S and O must be classes. • If P equals subPropertyOf, then it infers that both S and O must be properties. • If P equals domain or range, then it infers that S must be a property and O must be a class

8. Query Module • Evaluates RQL queries posed by the user • It is independent of the underlying repository • Can not use optimizations and query evaluations offered by specific DBMSs • RQL queries are translated into a set of calls to the RAL • e.g. when a query contains a join operation over two subqueries, each of the subqueries is evaluated, and the join operation is then executed by the query engine on the results

9. RDF Export Module • This module allows for the extraction of the complete schema and/or data from a model in RDF format • It supplies the basis for using Sesame with other RDF tools

10. SeRQL (Sesame RDF Query Language) • Extension of RQL • Some of the built-in predicates: • {X} serql:directSubClassOf {Y} • {X} serql:directSubPropertyOf {Y} • Some of the built-in functions • isLiteral() • isResource()

11. Important Features of Sesame • Portability • It is written completely in Java • Repository independence • Provides RAL • Extensibility • Other functional modules can be created and be plugged in it • Flexible communication by using protocol handlers • The architecture separates the communication details from the actual functionality through the use of protocol handlers

12. Using PostgreSQL as Repository • PostgreSQL is an open-source object-relational DBMS • It supports subtable relations between its tables • Subtable relations are also transitive • These relations can be used to model the subsumption reasoning of RDF schema.

13. Example RDF Schema & Data domain range Writer hasWritten Book subClassOf FamousWriter Schema Data type type hasWritten …/twain/mark …/ISBN00023423442

14. Storing Schema (PostgreSQL) Class SubClassOf SubPropertyOf Property Domain Range

15. Storing Data (PostgreSQL) Resource Book Writer FamousWriter hasWritten

16. Using MySQL

17. Scalability Issues • An experiment using Sesame: • Uploading and querying a collection of nouns from Wordnet(http://www.semanticweb.org/library) • Consisting of about 400,000 RDF statements. • Using a workstation (Sun UltraSPARC 5, 256MB RAM) • Uploading the Wordnet nouns took 94 minutes. • Querying was quite slow (in MySQL) • Because data is distributed over multiple tables, and retrieving data needs doing many joins on tables

18. Future Work • Transaction Rollback Support • Aims an ACID compliant storage system • Versioning support • Adding and extending functional modules • Support ‘Update’ operation • DAML+OIL support

19. Comparison with others • Database Compatibility • API Compatibility

20. Comparison with others • Tool Support • Query Language Support

21. Comparison with others • Reasoning level and Scalability

22. References • Sesame : A Generic architecture for storing and querying RDF and RDFs, http://sesame.aidministrator.nl/ • Create Scalable Semantic Applications with Database-Backed RDF Stores, www.devx.com • OpenRDF - Sesame Benchmark, http://bklab.snu.ac.kr/blog/kwangsub/53