VISUALIZING LARGE, LOOSELY-STRUCTURED, HIERARCHICAL INFORMATION SPACES
Abstract
The magnitude of loosely, structured data available at users' fingertips from
local and distributed sources is experiencing unprecedented growth. Even
modern hierarchical visualization systems are overwhelmed by scalability
problems due to the explosive increase in data magnitude.
This thesis surveys the current state of the art in information visualization
to determine essential visualization characteristics, leading to a set of
guidelines for hierarchical visualization evaluation and design.
The guidelines become the basis for a new hierarchicial visualization
strategy, illustrated and implemented by the FLEX VIEW system.
FLEX VIEW incorporates three main features of this strategy. First, the
sophisticated use of emphasis and exclusion filters is applied to node
attributes and an importance value to refine content quality. Second, the
tight coupling of gestalt and detail views provides navigational capability
and presents global trends and anomalies. Third, concepts are extended to
abstracted hierarchies through automatic filter interface tuning. FLEX VIEW
also introduces a \fIschlider\fR control for the compact selection of multiple,
emphasized sub-ranges across a continuum.
Description
Keywords
Computer Science