Context Mediation on Wall Street

This paper reports on a practical implementation of a context mediator for the fixed income securities industry. We describe industry circumstances and the data and calculation services (DCS) mediator developed and deployed in the early 1990s. The mediator was designed as an interpretive engine controlled by a static declarative knowledge structure and client preference data. In addition to heterogeneous, autonomous data sources, the mediator integrated autonomously developed local and remote procedural components. Client access to both data and computational resources were provided through an active conceptual model. Structural and semantic context conversions were used to integrate disparate components and to support varying client needs. Lessons learned from the implementation and usage of this mediator provide insight into the requirements for a successful context mediator.