How can semantic conflicts in data exchange be resolved? This paper introduces the Context Interchange strategy, a novel approach to mediated data access in heterogeneous systems. This framework avoids identifying semantic conflicts a priori, instead detecting and reconciling them dynamically using a context mediator by comparing context axioms associated with each system. The research addresses a critical challenge in data management when systems using disparate semantics must share and integrate data. This article demonstrates how queries formulated on shared views, export schemas, and shared ontologies can be mediated within the Context Interchange framework. The proposed framework is validated through a prototype implementation providing mediated data access to both traditional and web-based information sources. This system employs a logic-based, object-oriented formalism for representing and reasoning about data semantics across different systems, enhancing flexibility and interoperability. The findings enable more seamless data exchange among disparate systems, reducing the need for extensive pre-configuration and manual conflict resolution. This approach has potential applications in various domains, including enterprise information integration, data warehousing, and semantic web technologies. Further research could explore adaptive context mediators capable of learning and evolving context axioms to improve mediation accuracy and efficiency over time.
This paper on context interchange is highly relevant to ACM Transactions on Information Systems, which publishes research on the design, development, and evaluation of information systems. The paper addresses the core challenge of achieving interoperability between disparate systems. By introducing a novel strategy for mediating data access, the paper aligns with the journal's scope of advancing the theory and practice of information systems.