Geographic information is critical for building disaster planning, crisis management and early-warning systems. Decision making in Geographic Information Systems (GIS) increasingly relies on analyses of spatial data in map-based formats. Maps are complex structures composed of layers created from distributed heterogeneous data belonging to the separate organizations. This thesis presents a distributed service architecture for managing the production of knowledge from distributed collections of archived observations and simulation data through integrated data-views. Integrated views are defined by a federation service (“federator”) located on top of the standard service components. Common GIS standards enable the construction of this system. However, compliance requirements for interoperability, such as XML-encoded data and domain specific data characteristics, have costs and performance overhead. We investigate issues of combining standard compliance with performance. Although our framework is designed for GIS, we extend the principles and requirements to general science domains and discuss how these may be applied.