Computer graphics processing and selective visual display system – Computer graphics processing – Graph generating
Reexamination Certificate
1999-10-22
2002-10-15
Luu, Matthew (Department: 2672)
Computer graphics processing and selective visual display system
Computer graphics processing
Graph generating
C345S440100, C345S630000, C345S632000, C382S177000, C704S009000, C704SE21020
Reexamination Certificate
active
06466211
ABSTRACT:
TECHNICAL FIELD
The present invention relates to data visualization apparatuses, computer-readable mediums, computer data signals embodied in a transmission medium, data visualization methods, and digital computer data visualization methods.
BACKGROUND OF THE INVENTION
Some conventional information visualization systems provide visualization of documents or their attributes by representing documents or a group of documents with graphical symbols. Changes over a sequential variable such as time are often represented by showing a changing image which depicts data within pertinent time slots.
One graphical software application is available from Microsoft Corporation under the designation Excel™. Excel enables a user to generate a stacked line graph to visually represent a data set. The lines utilized to represent graphical information are stacked relative to one another and to corresponding x and y axes.
The stacked line graph includes a plurality of lines corresponding to respective entities being graphed. Although cumulative widths of the entities are depicted with reference to one of the axes, it is often difficult and tedious to determine the relative weights of entities with respect to one another at any given reference point.
Computer systems utilizing conventional data visualization technology are currently applied to numerous disciplines. For example, such is utilized for educational purposes, corporate presentations, etc. Accordingly, there is a need to provide visualization systems which provide clear and concise representations of desired data inasmuch as computers are being utilized at an ever increasing pace for data visualization.
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Gao Feng
Harris W. Michelle
Havre Susan L.
Hetzler Elizabeth G.
Martucci Louis M.
Battelle (Memorial Institute)
Luu Matthew
Sajous Wesner
Wells St. John P.S.
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