RDF and RDF Schema are two W3C standards aimed at enriching the Web with machine-processable semantic data. We have developed Sesame, an architecture for efficient storage and expressive querying of large quantities of metadata in RDF and RDF Schema. Sesame's design and implementation are independent from any specific storage device. Thus, Sesame can be deployed on top of a variety of storage devices, such as relational databases, triple stores, or object-oriented databases, without having to change the query engine or other functional modules. Sesame offers support for concurrency control, independent export of RDF and RDFS information and a query engine for RQL, a query language for RDF that offers native support for RDF Schema semantics. We present an overview of Sesame as a generic architecture, as well as its implementation and our first experiences with this implementation.

No abstract

RDF and RDF Schema are two W3C standards aimed at enriching the Web with machine-processable semantic data. We have developed Sesame, an architecture for efficient storage and expressive querying of large quantities of metadata in RDF and RDF Schema. Sesame's design and implementation are independent from any specific storage device. Thus, Sesame can be deployed on top of a variety of storage devices, such as relational databases, triple stores, or object-oriented databases, without having to change the query engine or other functional modules. Sesame offers support for concurrency control, independent export of RDF and RDFS information and a query engine for RQL, a query language for RDF that offers native support for RDF Schema semantics. We present an overview of Sesame as a generic architecture, as well as its implementation and our first experiences with this implementation.

No abstract

No abstract

A technical infrastructure for storing, querying and managing RDF data is a key element in the current semantic web development. Systems like Jena, Sesame or the ICS-FORTH RDF Suite are widely used for building semantic web applications. Currently, none of these systems supports the integrated querying of distributed RDF repositories. We consider this a major shortcoming since the semantic web is distributed by nature. In this paper we present an architecture for querying distributed RDF repositories by extending the existing Sesame system. We discuss the implications of our architecture and propose an index structure as well as algorithms for query processing and optimization in such a distributed context. Categories and Subject Descriptors MOTIVATIONThe need for handling multiple sources of knowledge and information is quite obvious in the context of semantic web applications. First of all we have the duality of schema and information content where multiple information sources can adhere to the same schema. Further, the re-use, extension and combination of multiple schema files is considered to be common practice on the semantic web [7]. Despite the inherently distributed nature of the semantic web, most current RDF infrastructures (for example [4]) store information locally as a single knowledge repository, i.e., RDF models from remote sources are replicated locally and merged into a single model. Distribution is virtually retained through the use of namespaces to distinguish between different models. We argue that many interesting applications on the semantic web would benefit from or even require an RDF infrastructure that supports real distribution of information sources that can be accessed from a single point. BeyondCopyright is held by the author/owner(s). May 17-22, 2004, New York, New York, USA. WWW2004,ACM 1-58113-844-X/04/0005. the argument of conceptual adequacy, there are a number of technical reasons for real distribution in the spirit of distributed databases:The commonly used approach of using a local copy of a remote source suffers from the problem of changing information. Directly using the remote source frees us from the need of managing change as we are always working with the original. Flexibility:Keeping different sources separate from each other provides us with a greater flexibility concerning the addition and removal of sources. In the distributed setting, we only have to adjust the corresponding system parameters.In many cases, it will even be unavoidable to adopt a distributed architecture, for example in scenarios in which the data is not owned by the person querying it. In this case, it will often not be permitted to copy the data. More and more information providers, however, create interfaces that can be used to query the information. The same holds for cases where the information sources are too large to just create a single model containing all the information, but they still can be queried using a special interface (Musicbrainz is an example of this case). Further, we...

A technical infrastructure for storing, querying and managing RDF data is a key element in the current Semantic Web development. Systems like Jena, Sesame or the ICS-FORTH RDF Suite are widely used for building Semantic Web applications. Currently, none of these systems support the integrated querying of distributed RDF repositories. We consider this a major shortcoming since the Semantic Web is distributed by nature. In this paper we present an architecture for querying distributed RDF repositories by extending the existing Sesame system. We discuss the implications of our architecture and propose an index structure as well as algorithms for query processing and optimization in such a distributed context.

No abstract