Distributed Objects and Applications, International Symposium on (2000)
Sept. 21, 2000 to Sept. 23, 2000
Bastiaan Schönhage , Vrije Universiteit and ASZ Research & Development
Anton Eliëns , Vrije Universiteit and CWI
Decoupling the components of a distributed application through an intermediate shared data model is a powerful concept. Components can work independently, but at the same time-share, intermediate results and collaborate on a shared data structure. This paper describes a particular realization of the shared data model, the Shared Concept Space (SCS), which is an essential element of the DIVA visualization architecture. The Shared Concept Space decouples the information provider and visualizer and allows for hierarchical and derived data. We demonstrate the functionality of the SCS by discussing an example that shows how simulation data may be presented effectively to support decision-making in a business context. Visualization is the use of computer-supported, interactive, visual representations of data to amplify cognition . When multiple machines are deployed to transform the raw data into visual representations we speak of distributed visualization. One of the purposes of distributed visualization is to support collaborative visualization in which multiple users can work together using multiple perspectives on the information . The Distributed Visualization Architecture DIVA [9, 10] is our approach to supporting multiple users in corroboratively visualizing and understanding information. The architecture distinguishes between two types of data sources: static and dynamic. A typical static information source is a database. Examples of dynamic sources include simulations and measuring devices that produce new data on a timely basis. The data is transferred from its source location to the visualization components by means of the Shared Concept Space (SCS), the topic of this paper. Structure Section 1 describes the concept of communication mechanisms in distributed applications and gives two communication paradigms. Section 2 introduces the general idea and motivation of the Shared Concept Space. Section 3 shows that the Shared Concept Space has its foundations in a couple of design patterns, which are described in this section. After that, Section 4 discusses the software architecture underlying the Shared Concept Space. Section 5 zooms in two important distribution aspects: performance and scalability. Next, Section 6 illustrates the practical application of the Concept Space. Finally, Section 7 summarizes and concludes this paper.
B. Schönhage and A. Eliëns, "Information Exchange in a Distributed Visualization Architecture: The Shared Concept Space," Distributed Objects and Applications, International Symposium on(DOA), Antwerp, Belgium, 2000, pp. 335.