The Context Interchange strategy presents a novel perspective for mediated data access in which semantic conflicts among heterogeneous systems are not identified a priori, but are detected and reconciled by a context mediator through comparison of contexts axioms corresponding to the systems engaged in data exchange. In this article, we show that queries formulated on shared views, export schema, and shared “ontologies ” can be mediated in the same way using the Context Interchange framework. The proposed framework provides a logic-based object-oriented formalism for representing and reasoning about data semantics in disparate systems, and has been validated in a prototype implementation providing mediated data access to both traditional and web-based information sources. Categories and Subject Descriptors: H.2.4 [Database Management]: Systems—Query processing; H.2.5 [Database Management]: Heterogeneous Databases—Data translation

We introduce a new proof procedure for abductive logic programming and present two soundness results. Our procedure extends that of Fung and Kowalski by integrating abductive reasoning with constraint solving and by relaxing the restrictions on allowed inputs for which the procedure can operate correctly. An implementation of our proof procedure is available and has been applied successfully in the context of multiagent systems.

Mediation architectures like the Context Interchange research project, from which this work stems, integrate disparate information sources, hiding distribution and reconciling heterogeneity. As a result of transparent access, the notion of distinct sources often disappears from queries and results. However, there are situations where users or applications do need to know the sources from which a particular datum is drawn: for example, enforcement of intellectual property, evaluation of data quality or measurement of the timeliness of data. In this paper, we define attribution as the association of a value in the result of a query with the sources either from which the data was extracted or which contributed to the selection. Motivated by multisource querying, attribution has particular applicability in the context of the World Wide Web. After beginning with an example that both describes and motivates the need for attribution within the semi-structured environment of the Web, we offer...

. The emergence of the Internet as the de facto Global Information Infrastructure enables the construction of decision support systems that leverage on the panoply of on-line information sources. This highly dynamic environment presents a critical need for a flexible and scalable strategy for integrating the disparate information sources while respecting their independence. The Context Interchange strategy addresses above concerns with a special emphasis on resolving problems arising from semantic heterogeneity, i.e. inconsistencies arising from differences in the representation and interpretation of data. This is accomplished using three elements: a shared vocabulary for the underlying application domain (in the form of a domain model ), a formal object-relational data model (coin), and an object-deductive language (coinl). Semantic interoperation is accomplished by making use of declarative definitions corresponding to source and receiver contexts; i.e. constraints, choices, and pr...

Abstract The COntext INterchange (COIN) strategy is an approach to solving the problem of interoperability of semantically heterogeneous data sources through context mediation. COIN has used its own notation and syntax for representing ontologies. More recently, the OWL Web Ontology Language is becoming established as the W3C recommended ontology language. We propose the use of the COIN strategy to solve context disparity and ontology interoperability problems in the emerging Semantic Web – both at the ontology level and at the data level. In conjunction with this, we propose a version of the COIN ontology model that uses OWL and the emerging rules interchange language, RuleML.

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: In this paper, we describe results from a preliminary effort to better understand issues of attribution that arise from the application of knowledge-based systems to the blending of structured querying and document retrieval over disparate (heterogeneous, distributed) information sources. The term multimodal integration is introduced to refer to such a blending of structured querying and document retrieval. 1. Introduction While the World Wide Web offers a rich pool of resources, the mixture of media types, and diverse storage and access methods presents users with the challenge of divining useful information from the ether. One promising avenue for structuring the tangled Web calls for merging knowledge-based systems with traditional document retrieval in a multimodal paradigm using the Mediation reference architecture introduced in (Wiederhold, 92). In addition to the Context Interchange research project, from which this work stems, several projects (e.g. Arens & Knobloch, 92; Gar...

In this paper, we try and give a brief introduction to the Gestalt approach to the integration of disparate information sources and to the Context Interchange approach to the automatic identification and resolution of semantic conflicts. We also attempt present a survey of the modern solutions to the problems of query processing in Internet networked data sources, which both Gestalt and Context Interchange leverage and attempt to adapt and improve. 1 Introduction The growth of the Internet has not only greatly simplified the access to existing sources of information but also motivated the creation of numerous new sources. Paradoxally, this growth has made difficult the tasks of finding, extracting, and aggregating relevant information. Gateways, protocols like Object Database Connectivity (ODBC), and standards like eXtensible Markup Language (XML) are gaining popularity for they potentially solve the first issues of heterogeneity and connectivity. As a result, we can anticipate f...

project, from which this work stems, integrate disparate information sources, hiding distribution and reconciling heterogeneity. As a result of transparent access, the notion of distinct sources often disappears from queries and results. However, there are situations where users or applications do need to know the sources from which a particular datum is drawn: for example, enforcement ofintellectual property, evaluation of data quality or measurement of the timeliness of data. In this paper, we de ne attribution as the association of a value in the result of a query with the sources either from which the data was extracted or which contributed to the selection. Motivated by multisource querying, attribution has particular applicability in the context of the World Wide Web. After beginning with an example that both describes and motivates the need for attribution within the semi-structured environment ofthe Web, we o er a general attribution framework and algebra and discuss the implementation of a prototype. 1

Abstract. The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the Context Interchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web. 1