copyright © 2011 - ALL RIGHTS RESERVED CG Portfolio Papers Description This paper is about “Visualization Improvement by Reconfiguring the Vertical Axes in Parallel Coordinates”. ABSTRACT  Information visualization is a new science for observing the behavior of large-scale  data. There are several methods to represents data in visual format. One well-known  approach is Parallel Coordinates Plot (PCP) which maps multivariate data into 2D view.  Although PCP is a powerful method in data visualization, in some cases it is impossible  for the user to analyze the result due to the clutter effect in large datasets. It means with  huge number of data, there will be lots of intersected lines in PCP, making it hard to  track the corresponding row of each line. Hence, the pattern of data is less visible. This  paper presents a method based on the first-order derivative to change the order of  vertical axes in parallel coordinates in order to have fewer intersections between rows of  data. This method will reduce number of intersections up to 30% less than the random  order of the vertical axes resulting to a parallel coordinates with more meaningful  patterns. Keywords: Information, Data, Visualization, Parallel Coordinates Plot, Dataset.