Ontologies are shared models of a domain that encode a view which is common to a set of different parties. Contexts are local models that encode a party's subjective view of a domain. In this paper we show how ontologies can be contextualized, thus acquiring certain useful properties that a pure shared approach cannot provide. We say that an ontology is contextualized or, also, that it is a contextual ontology, when its contents are kept local, and therefore not shared with other ontologies, and mapped with the contents of other ontologies via explicit (context) mappings. The result is Context OWL (C-OWL), a language whose syntax and semantics have been obtained by extending the OWL syntax and semantics to allow for the representation of contextual ontologies.

Context-awareness is one of the drivers of the ubiquitous computing paradigm, whereas a well designed model is a key accessor to the context in any context-aware system. This paper provides a survey of the the most relevant current approaches to modeling context for ubiquitous computing. Numerous approaches are reviewed, classified relative to their core elements and evaluated with respect to their appropriateness for ubiquitous computing. 1.

Multi-Agent Systems are increasingly complex, and the problem of their verification and validation is acquiring increasing importance. In this paper we show how a well known and effective verification technique, symbolic model checking, can be generalized to deal with Multi-Agent Systems. Our approach is fully amenable to the reuse of data structures used in symbolic model checking, Binary Decision Diagrams in particular, to deal with extremely large state spaces. A preliminary implementation of the approach in the NuMAS system shows promising results.

Abstract. The Semantic Web is a powerful vision that is getting to grips with the challenge of providing more human-oriented web services. Hence, reasoning with and across distributed, partially implicit assumptions (contextual knowledge), is a milestone. Ontologies are a primary means to deploy the Semantic Web vision, but few work has been done on them to manage the context-dependency of Web knowledge. In this paper we introduce an ontology for representing a variety of reified contexts and states of affairs, called D&S, currently implemented as a plug-in to the DOLCE foundational ontology, and its application to two cases: an ontology for communication situations and roles, and an ontology for peer-to-peer communication. The reified contexts represented in D&S have a rich structure, and are a middleware between full-fledged formal contexts and theories, and the often poor vocabularies implemented in Web ontologies... 1

Abstract. Semantic coordination, namely the problem of finding an agreement on the meaning of heterogeneous semantic models, is one of the key issues in the development of the Semantic Web. In this paper, we propose a new algorithm for discovering semantic mappings across hierarchical classifications based on a new approach to semantic coordination. This approach shifts the problem of semantic coordination from the problem of computing linguistic or structural similarities (what most other proposed approaches do) to the problem of deducing relations between sets of logical formulae that represent the meaning of concepts belonging to different models. We show how to apply the approach and the algorithm to an interesting family of semantic models, namely hierarchical classifications, and present the results of preliminary tests on two types of hierarchical classifications, web directories and catalogs. Finally, we argue why this is a significant improvement on previous approaches. 1

ist and Wiksell, Stockholm, 1965. [ Serafini and Ghidini, 1997 ] L. Serafini and C. Ghidini. Context Based Semantics for Federated Databases. In Proceedings of the 1st International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT-97), pages 33--45, Rio de Jeneiro, Brazil, 1997. Also IRSTTechnical Report 9609-02, IRST, Trento, Italy. [ Subrahmanian, 1994 ] V.S. Subrahmanian. Amalgamating Knowledge Bases. ACM Trans. Database Syst., 19(2):291--331, 1994. [ Wiederhold, 1992 ] G. Wiederhold. Mediators in the architecture of future information systems. IEEE Computer, 25(3):38--49, 1992. and complete calculus for DFOL based on ML systems. Finally we have compared our formalism with other formalisms for the representation and integration of distributed knowledge and reasoning systems. Acknowledgments. We thank all the people of the Mechanized Reasoning Group of IRST and DISA for useful discussions and feedb

Abstract. The paper addresses the problem of reasoning with multiple ontologies interrelated with semantic mappings. This problem is becoming more and more relevant due to the necessity of building a scalable ontological reasoning tools for the Semantic Web. In contrast to the so called global approach, in which reasoning with multiple semantically related ontologies is performed in a global knowledge base that encodes both ontologies and semantic mappings, we propose a distributed reasoning approach in which reasoning is the result of combination via semantic mappings of local reasonings chunks performed in single ontologies. The paper presents a tableau-based distributed reasoning procedure which is sound and complete w.r.t. Distributed Description Logics, the formal framework used to represent multiple semantically connected ontologies. The paper also describes the design and implementation principles of a distributed reasoning system, called DRAGO (Distributed Reasoning Architecture for a Galaxy of Ontology), that implements such distributed decision procedure. 1

A central theme of the semantic web is that programs should be able to easily aggregate data from di#erent sources. Unfortunately, even if two sites provide their data using the same data model and vocabulary, subtle differences in their use of terms and in the assumptions they make pose challenges for aggregation. Experiences with the TAP project reveal some of the phenomena that pose obstacles to a simplistic model of aggregation. Similar experiences have been reported by AI projects such as Cyc, which has lead to the development and use of various context mechanisms. In this paper we report on some of the problems with aggregating independently published data and propose a context mechanism to handle some of these problems. We briefly survey the context mechanisms developed in in AI and contrast them with the requirements of a context mechanism for the semantic web. Finally, we present a context mechanism for the semantic web that is adequate to handle the aggregation tasks, yet simple from both computational and model theoretic perspectives.

Independence { the study of what is relevant to a given problem of reasoning { has received an increasing attention from the AI community. In this paper, we consider two basic forms of independence, namely, a syntactic one and a semantic one. We show features and drawbacks of them. In particular, while the syntactic form of independence is computationally easy to check, there are cases in which things that intuitively are not relevant are not recognized as such. We also consider the problem of forgetting, i.e., distilling from a knowledge base only the part that is relevant to the set of queries constructed from a subset of the alphabet. While such process is computationally hard, it allows for a simpli - cation of subsequent reasoning, and can thus be viewed as a form of compilation: once the relevant part of a knowledge base has been extracted, all reasoning tasks to be performed can be simpli ed.

In this paper, we criticise the objectivistic approach that underlies most current systems for Knowledge Management. We show that such an approach is incompatible with the very nature of what is to be managed (i.e., knowledge), and we argue that this may partially explain why most knowledge management systems are deserted by users. We propose a different approach - called distributed knowledge management - in which subjective and social (in a word, contextual) aspects of knowledge are seriously taken into account. Finally, we present a general technological architecture in which these ideas are implemented by introducing the concept of knowledge node.