The Sloan Digital Sky Survey has created the most detailed three-dimensional maps of the Universe ever made, with deep multi-color images of one third of the sky, and spectra for more than three million astronomical objects.
Datasets which are identical over a number of statistical properties, yet produce dissimilar graphs, are frequently used to illustrate the importance of graphical representations when exploring data. This paper presents a novel method for generating such datasets, along with several examples. Our technique varies from previous approaches in that new datasets are iteratively generated from a seed dataset through random perturbations of individual data points, and can be directed towards a desired outcome through a simulated annealing optimization strategy.
C. Seitz, C. Legat, and J. Neidig. Workshops Proceedings of the 5th International Conference on Intelligent Environments, volume 4 of Ambient Intelligence and Smart Environments, page 51--57. Amsterdam, IOS Press, (2009)