GAIA: making virtual space a reality

Data mining or knowledge discovery is a relatively new area of database research. Data mining is defined as the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. This is done by combining a variety of database, statistical and machine learning techniques. Different data mining algorithms have been developed to perform different types of analysis. Some algorithms search for repeating patterns or trends in a database. Others classify elements into groups based on their attribute values. For the data from GAIA, we are interested in data mining algorithms that perform classification and spatial location. These algorithms can be used to improve the efficiency of visualizing large, multidimensional datasets, which then can be presented in 3D virtual reality. Although GAIA will not launch before 2010 this work facilitates an insight into the data processing techniques required to create a useful tool for astrophysicists. The paper will present a data mining technique developed by RMIT University and ESA proposed for retrieving information from the GAIA database. This tool allows astrophysicists to simulate planet formation, stellar system collisions, and origins of our galaxy.