Dependency based collaboration: Ontology based information management

Abstract

Central to any collaboration problem is the ability to model and understand how the effects of decisions made in one system propagate through the collective understanding, bringing to light insights and information. This raises the important research question of how information in different systems can be brought together in an understandable way but without the need to re-engineer either their interfaces or their data needs. The approach to "loose systems" coupling explored in this paper organizes information so that the dependency between information (people/groups, locations, resources and concepts) provided by disparate sources) can be identified, the consequences of the impacts on these dependencies analyzed and any consequences made explicit. This allows users to understand the explicit and implicit constraints, restraints and preferences that are imposed on their tasks ensuring any solutions they provide are compatible with ones being developed by other users. Understanding the "space of potential solutions" allows users to truly develop collaborate solutions in parallel without the need to employ a "stove piped" process in which users take turns in adding information to a solution in order to ensure consistency. Modeling the constraints, restraints and preferences of potential solutions also allows for more intelligent monitoring of information needs and hence more focusing information search. An example is provided showing how different planners and analysis tools can work collaboratively ensuring plans remains consistent.