Abstract. (Semi-)automatic mapping — also called (semi-)automatic alignment — of ontologies is a core task to achieve interoperability when two agents or services use different ontologies. In the existing literature, the focus has so far been on improving the quality of mapping results. We here consider QOM, Quick Ontology Mapping, as a way to trade off between effectiveness (i.e. quality) and efficiency of the mapping generation algorithms. We show that QOM has lower run-time complexity than existing prominent approaches. Then, we show in experiments that this theoretical investigation translates into practical benefits. While QOM gives up some of the possibilities for producing high-quality results in favor of efficiency, our experiments show that this loss of quality is marginal. 1

Abstract. In this paper, we present an evaluation of four knowledge base systems (KBS) with respect to use in large OWL applications. To our knowledge, no experiment has been done with the scale of data used here. The smallest dataset used consists of 15 OWL files totaling 8MB, while the largest dataset consists of 999 files totaling 583MB. We evaluated two memory-based systems (OWLJessKB and memory-based Sesame) and two systems with persistent storage (database-based Sesame and DLDB-OWL). We describe how we have performed the evaluation and what factors we have considered in it. We show the results of the experiment and discuss the performance of each system. In particular, we have concluded that existing systems need to place a greater emphasis on scalability. 1

Abstract. We survey nearly 1300 OWL ontologies and RDFS schemas. The collection of statistical data allows us to perform analysis and report some trends. Though most of the documents are syntactically OWL Full, very few stay in OWL Full when they are syntactically patched by adding type triples. We also report the frequency of occurrences of OWL language constructs and the shape of class hierarchies in the ontologies. Finally, we note that of the largest ontologies surveyed here, most do not exceed the description logic expressivity of ALC. 1

In this paper we benchmark three popular database representations of RDF/S schemata and data: (a) a schema-aware (i.e., one table per RDF/S class or property) with explicit (ISA) or implicit (NOISA) storage of subsumption relationships, (b) a schema-oblivious (i.e., a single table with triples of the form #subject-predicate-object#), using (ID) or not (URI) identifiers to represent resources and (c) a hybrid of the schema-aware and schema-oblivious representations (i.e., one table per RDF/S meta-class by distinguishing also the range type of properties). Furthermore,

Semantic Portal is the next generation of web portals that are powered by Semantic Web technologies for improved information sharing and exchange for a community of users. Current methods of searching in Semantic Portals are limited to keyword-based search using information retrieval (IR) techniques, ontology-based formal query and reasoning, or a simple combination of the two. In this paper, we propose an enhanced model that tightly integrates IR with formal query and reasoning to fully utilize both textual and semantic information for searching in Semantic Portals. The model extends the search capabilities of existing methods and can answer more complex search requests. The ideas in a fuzzy description logic (DL) IR model and a formal DL query method are employed and combined in our model. Based on the model, a semantic search service is implemented and evaluated. The evaluation shows very large improvements over existing methods.

Abstract. OntoTrack is a new browsing and editing “in-one-view” ontology authoring tool that combines a hierarchical graphical layout and instant reasoning feedback for (the most rational fraction of) OWL Lite. OntoTrack provides an animated and zoomable view with context sensitive features like click-able miniature branches or selective detail views together with drag-and-drop editing. Each editing step is instantly synchronized with an external reasoner in order to provide appropriate graphical feedback about relevant modeling consequences. The most recent feature of OntoTrack is an on demand textual explanation for subsumption and equivalence between or unsatisfiability of classes. This paper describes the key features of the current implementation and discusses future work as well as some development issues. 1

Abstract. Ontology tools performance and scalability are critical to both the growth of the Semantic Web and the establishment of these tools in the industry. In this paper, we present briefly the benchmarking methodology used to improve the performance and the scalability of ontology development tools. We focus on the definition of the infrastructure for evaluating the performance of these tools ’ ontology management APIs in terms of its execution efficiency. We also present the results of applying the methodology for evaluating the API of the WebODE ontology engineering workbench. 1

Abstract 3. Reason–ability, i.e. usability for (ideally, non– trivial) inference by existing semantic web The relatively high level of standardisation of semantic reasoners. web ontology languages is in contrast to mostly ad hoc Unfortunately, many existing SWOs fail in one, if not designed content of ontologies themselves. An overview of all aspects. By consequence, the usefulness of semantic existing methods supporting ontology content creation is web is likely to be questioned: presented. Methods based on design patterns are then 1. Inaccurate ontologies will produce wrong results discussed in more detail as they seem most promising as soon as their implicit assumptions are violated. particularly for business environment. Examples of 2. Opaque ontologies (be they accurate) will either elementary problems typical for semantic web ontologies not be used outside their native application or will are shown, and their pattern–based solution is outlined. be mapped on an inadequate state of affairs. 1.

We survey nearly 1300 OWL ontologies and RDFS schemas. The collection of statistical data allows us to perform analysis and report some trends. Though most of the documents are syntactically OWL Full, very few stay in OWL Full when the syntactic errors are fixed. We also report the frequency of occurrences of OWL language constructs and the shape of class hierarchies in the ontologies. Finally, we note that of the largest ontologies surveyed here, most do not exceed the expressivity of ALC.

OntoTrack is an ontology authoring tool that combines a graph-based hierarchical layout and instant reasoning feedback within one single view. Currently OntoTrack can handle ontologies with an expressivity almost comparable to OWL Lite. The graphical representation provides an animated and zoomable subsumption graph with context sensitive features such as click-able miniature branches or selective detail views, together with drag-and-drop editing. Each editing step is instantly synchronised with an external reasoner in order to provide appropriate graphical feedback about relevant modelling consequences. A recent extention of OntoTrack provides an on-demand textual explanation for subsumption relationships between classes. This paper describes the key features of the current implementation and discusses future work, as well as some development issues. OntoTrack can be downloaded at