Dave Reynolds

Jena: implementing the semantic web recommendations

The new Semantic Web recommendations for RDF, RDFS and OWL have, at their heart, the RDF graph. Jena2, a second-generation RDF toolkit, is similarly centered on the RDF graph. RDFS and OWL reasoning are seen as graph-to-graph transforms, producing graphs of virtual triples. Rich APIs are provided. The Model API includes support for other aspects of the RDF recommendations, such as containers and reification. The Ontology API includes support for RDFS and OWL, including advanced OWL Full support. Jena includes the de facto reference RDF/XML parser, and provides RDF/XML output using the full range of the rich RDF/XML grammar. N3 I/O is supported. RDF graphs can be stored in-memory or in databases. Jenas query language, RDQL, and the Web API are both offered for the next round of standardization.

SPARQL basic graph pattern optimization using selectivity estimation

In this paper, we formalize the problem of Basic Graph Pattern (BGP) optimization for SPARQL queries and main memory graph implementations of RDF data. We define and analyze the characteristics of heuristics for selectivity-based static BGP optimization. The heuristics range from simple triple pattern variable counting to more sophisticated selectivity estimation techniques. Customized summary statistics for RDF data enable the selectivity estimation of joined triple patterns and the development of efficient heuristics. Using the Lehigh University Benchmark (LUBM), we evaluate the performance of the heuristics for the queries provided by the LUBM and discuss some of them in more details.

Semantic information portals

In this paper, we describe the notion of a semantic information portal. This is a community information portal that exploits the semantic web standards to improve structure, extensibility, customization and sustainability. We are in the process of developing a prototype directory of environmental organizations as a demonstration of the approach and outline the design challenges involved and the current status of the work.

User profiling with privacy: a framework for adaptive information agents

This paper presents a framework for personal agents that respect the privacy of the individual. We present some motivations and outline a framework for the use of personal agents and user profiling for information systems designed around web services. A key element of our approach in general is to consider the impact of user-profiling and autonomous agents on the user. One particular aspect, which we explore in this paper, is the need to respect users privacy. One often-cited benefit of using personal agents is for personalising interaction. However, personalisation and privacy have contradictory goals in disclosing personal information. We explore some elements of our framework that allow the user to control the trade-offs around disclosure of personal information. We conclude with some motivating examples of the use of our framework in information-based tasks.