Advances in networking and telecommunications have increased physical connectivity (the ability to exchange bits and bytes) amongst disparate datasources and receivers. Unfortunately, these new technologies do not provide logical connectivity (the ability to exchange data meaningfully). This is because data can be imprecise becuase it is only meaningful if understood with reference to an underlying context which embodies a numer of hidden assumptions. These assumptions can apply to any attribute of the data. For example, while a GPA of 4.0 is very impressive in Harvard's context, it is less so at MIT where the maximum GPA is 5.0.

As a result, any data integration effort must be capable of reconciling semantic conflicts among sources and receivers. This problem is generally referred to as the need for semantic interoperability among distributed datasources.

We address this problem by providing a Context Mediator which detects and reconciles semantic conflicts among distributed datasources and receivers. It does this through reasoning about the contexts associated with systems engaged in data exchange.