Damyan Ognyanov

OWLIM – a pragmatic semantic repository for OWL

OWLIM is a high-performance Storage and Inference Layer (SAIL) for Sesame, which performs OWL DLP reasoning, based on forward-chaining of entilement rules. The reasoning and query evaluation are performed in-memory, while in the same time OWLIM provides a reliable persistence, based on N-Triples files. This paper presents OWLIM, together with an evaluation of its scalability over synthetic, but realistic, dataset encoded with respect to PROTON ontology. The experiment demonstrates that OWLIM can scale to millions of statements even on commodity desktop hardware. On an almost-entry-level server, OWLIM can manage a knowledge base of 10 million explicit statements, which are extended to about 19 millions after forward chaining. The upload and storage speed is about 3,000 statement/sec. at the maximal size of the repository, but it starts at more than 18,000 (for a small repository) and slows down smoothly. As it can be expected for such an inference strategy, delete operations are expensive, taking as much as few minutes. In the same time, a variety of queries can be evaluated within milliseconds. The experiment shows that such reasoners can be efficient for very big knowledge bases, in scenarios when delete operations should not be handled in real-time.

Ontology Versioning and Change Detection on the Web

To effectively use ontologies on the Web, it is essential that changes in ontologies are managed well. This paper analyzes the topic of ontology versioning in the context of the Web by looking at the characteristics of the version relation between ontologies and at the identification of online ontologies. Then, it describes the design of a web-based system that helps users to manage changes in ontologies. The system helps to keep different versions of web-based ontologies interoperable, by maintaining not only the transformations between ontologies, but also the conceptual relation between concepts in different versions. The system allows ontology engineers to compare versions of ontology and to specify these conceptual relations. For the visualization of differences, it uses an adaptable rule-based mechanism that finds and classifies changes in RDF-based ontologies.

Tracking Changes in RDF(S) Repositories

The real-world knowledge management applications require features such as versioning and fine-grained access control. Each of them raises the issue of tracking the changes in a knowledge base. Important part of the research presented is the definition of a formal model for tracking changes in graph-based data models. It was used in the ontology middleware module developed under the On-To-Knowledge project as an extension of the Sesame RDF(S) repository. This paper is further development of the results reported in [5].