Paper
28 February 2000 Improving visualization by capturing domain knowledge
Jonathan Meddes, Eric McKenzie
Author Affiliations +
Proceedings Volume 3960, Visual Data Exploration and Analysis VII; (2000) https://doi.org/10.1117/12.378895
Event: Electronic Imaging, 2000, San Jose, CA, United States
Abstract
An effective visualization system depends on a user's ability to interpret a visual representation and made valid inferences. This paper first summarizes the role of domain knowledge when interpreting a visualization. Once the visual perception system has interpreted the visual representation, the user transforms the data into information by the introduction of domain knowledge; these are the rules or items of knowledge that are relevant tot this visual representation allowing the user to make meaningful inferences. In the remainder of the paper we concentrate on a visualization architecture that encapsulates domain knowledge to improve user interpretation of a visual representation. We use an agent-based paradigm to provide a distributed model of computation which moves away from a heavyweight constrained based algorithm towards a lightweight distributed system that empower individual data items. Finally, we present DIME, an implementation based on this approach. DIME is an ongoing research project that tightly integrates data storage, knowledge capture, and information visualization in a 'visual environment'.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jonathan Meddes and Eric McKenzie "Improving visualization by capturing domain knowledge", Proc. SPIE 3960, Visual Data Exploration and Analysis VII, (28 February 2000); https://doi.org/10.1117/12.378895
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KEYWORDS
Visualization

Data storage

Information visualization

Data modeling

Transform theory

Human-machine interfaces

Bismuth

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