This project aims to integrate large-scale data sources from the Digging into Data repositories with other types of relevant data on the railroad system, already assembled by the project directors. Our project seeks to develop useful tools for spatio-temporal visualization of these data and the relationships among them. Our interdisciplinary team includes computer science, history, and geography researchers. Because the railroad "system" and its spatio-temporal configuration appeared differently from locality-to-locality and region-to-region, we need to adjust how we "locate" and "see" the system. By applying data mining and pattern recognition techniques, software systems can be created that dynamically redefine the way spatial data are represented. Utilizing processes common to analysis in Computer Science, we propose to develop a software framework that allows these embedded concepts to be visualized and further studied
