In recent years, query languages for the Semantic Web have gained increasing importance. Because the Semantic Web has grown very fast, the amount of data to be queried has increased massively. On the other hand, since many different communities around the globe are authoring Semantic Web content, the amount of overlapping data also constantly increases. Large knowledge bases, therefore, may contain many similar entities coming from different sources. One of the most challenging tasks in this area is to find imprecise matches (i.e., to find not only precise matches of queries but also similar ones). To achieve this goal, similarity measures are used determining the proximity of objects. Improving the recall of queries while still not losing too much precision is a sensitive task. The goal of this project is to extend traditional SPARQL with similarity operators to be able to query for similar entities in Semantic Web knowledge bases. SPARQL is an emerging standard query language for RDF.
There is an iSPARQL online demo available here. Please note the demo uses the OWL version of the MIT Process Handbook as example data set.
iSPARQL and OptARQ download (including a complete Eclipse project)
Note: iSPARQL and OptARQ are published under a GNU Lesser General Public License
- iSPARQL - An imprecise SPARQL demo
- SPARQL Query Language for RDF
- Jena – A Semantic Web Framework for Java
Furthermore, we have tested iSPARQL on the following datasets:
- Christoph Kiefer, Abraham Bernstein, and Markus Stocker. The Fundamentals of iSPARQL - A Virtual Triple Approach For Similarity-Based Semantic Web Tasks
- Christoph Kiefer, Abraham Bernstein, Jonas Tappolet. Analyzing Software with iSPARQL
- Christoph Kiefer, Abraham Bernstein, Hong Joo Lee, Mark Klein, Markus Stocker. Semantic Process Retrieval with iSPARQL
- Christoph Kiefer, Abraham Bernstein, Jonas Tappolet. Mining Software Repositories with iSPARQL and a Software Evolution Ontology
- Abraham Bernstein, Christoph Kiefer, Markus Stocker. OptARQ: A SPARQL Optimization Approach based on Triple Pattern Selectivity Estimation
- Markus Stocker. The Fundamentals of iSPARQL (diploma thesis University of Zurich)
- A. Bernstein, C. Kiefer, Imprecise RDQL: Towards Generic Retrieval in Ontologies Using Similarity Joins
- A. Bernstein, C. Kiefer, iRDQL - Imprecise Queries Using Similarity Joins for Retrieval in Ontologies
- A. Bernstein, C. Kiefer, iRDQL - Imprecise RDQL Queries Using Similarity Joins
All publications are available from our main publications site.