Development of data mining and visualisation software for scientific analysis

Visualisation of data in particle physics currently involves event displays, histograms, line graphs and scatterplots. Since 1975 there has been an explosion of techniques for data visualisation driven by highly interactive computer systems and ideas from statistical graphics. This field has been driven by demands for data mining of large databases and genomics. Two key areas are direct manipulation of visual data and new methods for visualising high-dimensional data. The first area has seen the use of linked views, brushing and pruning. The second area has seen the introduction of methods such as parallel coordinates and the grand tour. In this project, these ideas are applied to particle physics data to evaluate their ability to reduce data analysis time and improve pattern recognition. Visualisation will also be combined with data mining techniques. The use of visualisation to aid the understanding of the effectiveness (or not) of various data mining methods will be evaluated. There are publicly available software tools that include many of the new statistical graphics techniques. However, no single tool includes all the most powerful new techniques and much work is required to integrate these ideas into data analysis tools for particle physics. Moreover, particle physics data sets are very large and cannot be handled by many of the available tools. This work will be done in collaboration with potential users in CMS and ATLAS. The improved software tools, especially their ability to handle very large datasets, will then find application to scientific areas other than particle physics.