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The vision of semantic business processes is to enable the integration and inter-operability of business processes across organizational boundaries. Since different organizations model their processes differently, the discovery and retrieval of similar semantic business processes is necessary in order to foster inter-organizational collaborations. This paper presents our approach of using iSPARQL - our imprecise query engine based on iSPARQL - to query the OWL MIT Process Handbook - a large collection of over 5000 semantic business processes. We particularly show how easy it is to use iSPARQL to perform the presented process retrieval task. Furthermore, since choosing the best performing similarity strategy is a non-trivial, data-, and context-dependent task, we evaluate the performance of three simple and two human-engineered similarity strategies. In addition, we conduct machine learning experiments to learn similarity measures showing that complementary information contained in the different notions of similarity strategies provide a very high retrieval accuracy. Our preliminary results indicate that iSPARQL is indeed useful for extending the reach of queries and that it, therefore, is an enabler for inter- and intra-organizational collaborations. [ABSTRACT FROM AUTHOR]

Ontologies are increasingly used to represent the intended real-world semantics of data and services in information systems. Unfortunately, different databases often do not relate to the same ontologies when describing their semantics. Consequently, it is desirable to have information about the similarity between ontology concepts for ontology alignment and integration. This paper presents the SOQA-SimPack Toolkit (SST), an ontology language independent Java API that enables generic similarity detection and visualization in ontologies. We demonstrate SST's usefulness with the SOQA-SimPack Toolkit Browser, which allows users to graphically perform similarity calculations in ontologies. [ABSTRACT FROM AUTHOR]

The semantic web presents the vision of a distributed, dynamically growing knowledge base founded on formal logic. Common users, however, seem to have problems even with the simplest Boolean expressions. As queries from web search engines show, the great majority of users simply do not use Boolean expressions. So how can we help users to query a web of logic that they do not seem to understand? We address this problem by presenting a natural language interface to semantic web querying. The interface allows formulating queries in Attempto Controlled English (ACE), a subset of natural English. Each ACE query is translated into a discourse representation structure - a variant of the language of first-order logic - that is then translated into an N3-based semantic web querying language using an ontology-based rewriting framework. As the validation shows, our approach offers great potential for bridging the gap between the logic-based semantic web and its real-world users, since it allows users to query the semantic web without having to learn an unfamiliar formal language. Furthermore, we found that users liked our approach and designed good queries resulting in a very good retrieval performance (100% precision and 90% recall). [ABSTRACT FROM AUTHOR]