Abstract. Ontology matching is a crucial task to enable interoperation between Web applications using different but related ontologies. Today, most of the ontology matching techniques are targeted to find 1:1 mappings. However, block mappings are in fact more pervasive. In this paper, we discuss the block matching problem and suggest that both the mapping quality and the partitioning quality should be considered in block matching. We propose a novel partitioning-based approach to address the block matching issue. It considers both linguistic and structural characteristics of domain entities based on virtual documents, and uses a hierarchical bisection algorithm for partitioning. We set up two kinds of metrics to evaluate of the quality of block matching. The experimental results demonstrate that our approach is feasible. 1

Abstract. Ontology maturing as a conceptual process model is based on the assumption that ontology engineering is a continuous collaborative and informal learning process and always embedded in tasks that make use of the ontology to be developed. For supporting ontology maturing, we need lightweight and easy-to-use tools integrating usage and construction processes of ontologies. Within two applications – ImageNotion for semantic annotation of images and SOBOLEO for semantically enriched social bookmarking – we have shown that such ontology maturing support is feasible with the help of Web 2.0 technologies. In this paper, we want to present the conclusions from two evaluation sessions with end users and summarize requirements for further development. 1

Abstract: Ontology matching is commonly defined as a matter of dealing with

Abstract. An ontology is a formal representation of a domain modeling the entities in the domain and their relations. When a domain is represented by multiple ontologies, there is need for creating mappings among these ontologies in order to facilitate the integration of data annotated with and reasoning across these ontologies. The objective of this paper is to present our experience in aligning two large anatomical ontologies and to reflect on some of the issues and challenges encountered along the way. The anatomical ontologies under investigation are the Foundational Model of Anatomy (FMA) and GALEN. Our approach to aligning concepts is automatic, rule-based, and operates at the schema level, generating mostly point-to-point mappings. It uses a combination of domain-specific lexical techniques and structural and semantic techniques (to validate the mappings suggested lexically). It also takes advantage of domainspecific knowledge (lexical knowledge from external resources such as the Unified Medical Language System, as well as knowledge augmentation and inference techniques). Overall, the lexical alignment followed by structural validation identified 3,029 pairs of equivalent concepts in the FMA and GALEN, accounting for about 4 % of all FMA concepts and 32 % of all GALEN concepts. 1 Presentation of the system

Abstract. AUTOMS is a tool for the automatic alignment of domain ontologies. To ensure high precision and recall with the minimum human involvement, AUTOMS integrates several matching methods. This paper presents the tool and the results obtained for the ontologies within the framework of the OAEI 2006 contest. Particularly, the synthesis of lexical, semantic and structural matching methods, together with the exploitation of concept instances resulted in a rather high recall with space of improvement, and a quite high precision that shows the accuracy of the individual methods, as well as of their synthesis. 1 Presentation of the system 1.1 State, purpose, general statement In this paper we present the AUTOMS tool for the automatic alignment of ontologies. The proposed tool exploits the HCONE-merge [1] ontology mapping method, which is based on “uncovering ” the informal intended meaning of concepts by mapping them to WordNet senses. Furthermore, AUTOMS integrates the HCONE-merge

This paper proposes a method for the mapping of ontologies that, in a greater extent than other approaches, discovers and exploits sets of latent features for approximating the intended meaning of ontology elements. This is done by applying the reverse generative process of the Latent Dirichlet Allocation model. Similarity between element pairs is computed by means of the Kullback-Leibler divergence measure. Experimental results show the potential of the method. 1.

Abstract. The development of the Semantic Web has led to the proposal of several solutions concerning the retrieval of Semantic Web Documents (SWDs). However, current solutions presuppose that the query is given in a structured way- using a formal language- and provide no advanced means for the (semantic) alignment of the query to the contents of the Semantic Web Documents. As a consequence, many of the Web users can not take advantage of the semantic retrieval services provided, given their inability to express formal queries and/or their divergent conceptualizations of a domain. In this paper, we report on preliminary experiments towards an approach to SWDs retrieval that aims to support users to form semantic queries – requiring no knowledge and skills for expressing queries in a formal language- and to retrieve SWDs whose content is similar to the queries formed. 1

Abstract. The work 1 reported in this article aims towards computing web services ’ data semantics. The paper provides extensive experimental results towards the automatic semantic annotation of WSDL specifications. Specifically, this paper reports on combinations of state-of-the-art methods for automatically mapping the part elements of the WSDL input and output messages to ontology classes: These combinations result to a specific method for Uncovering web Services Data Semantics (USDS). We study the performance of USDS even in challenging cases where lexical items are rather scarce and misleading. Experimental results are being thoroughly discussed, showing the potential and limitations of USDS.

The integration of heterogeneous data sources with even heterogeneous semantic meanings poses a challenge for data and system integrators. Ontology Alignment (OA) tries to identify similarities between heterogeneous ontologies and to automatically create suitable mappings for transformation. However, the usage of standard OA approach for safety-critical domains needs further investigation. In this paper, we describe a semi-automated ontology alignment approach (SAMOA) well-suitable for integration scenarios of safety-critical applications. The major contribution of our approach is the modeling differentiation between individual system knowledge and generic domain-specific knowledge. We evaluate our approach by providing a typical use case example from the Air Traffic Management (ATM) domain. In addition we analyze to what extent the SAMOA approach can be supported by state-ofthe-art OA approaches. 1.

SUMMARY: Computer-Aided Design (CAD) and Geographical Information System (GIS) are being used in tandem to support a variety of decisions throughout the life cycle of civil infrastructure systems. Existing CAD and GIS platforms have been developed independently with different purposes resulting in significant differences in terms of data formats they support, terminology they utilize, semantics of concepts they represent, and reasoning techniques on which they are based. For this reason, existing CAD and GIS platforms are currently not interoperable, resulting in wasted time and money due to limitations associated with exchange of data and knowledge. Within the context of this paper, we highlight a set of interoperability challenges associated with CAD and GIS platforms and describe a web-service based approach that will enable semantic interoperability between these two platforms. The paper specifically discusses research challenges associated with different components of such a proposed semantic web-based approach; namely task decomposition, ontology identification, web service discovery and matching, and service composition. KEYWORDS: semantic web services, CAD-GIS, interoperability, web service composition, automated planning, web service discovery