For the past few weeks I have been working on the datacube browser for the lobi project.  These efforts have paralleled assignments for a class I am taking in visualization.  As a part of my final project for this class, I decided to improve my portion of the datacube browser, which is a parallel coordinates graph.  I devised a way for the system to automatically order the axes in a meaningful way.  I used a least squares algorithm to fit polynomials of degree one and two to pairs of dimensions to determine how well the data exhibited trends which are visibly appealing.  I also limited the appearance of randomness of k-means clustering, by assigning the colors based on attributes of cluster instead of randomly.  I plan to further improve these algorithms to show more interesting trends and appear less random and possibly not be random.  Any suggestions on what types of trends are visibly appealing in parallel coordinates would be welcomed.  If anyone wants a more detailed explanation of my algorithms, I have a pdf with a writeup of the project available.