Dr. Martina Morris (PI) & Dr. Mark Handcock at the Center for Studies in Demography and Ecology of University of Washington are funding a SoNIA-related project contract to integrate dynamic network visualization techniques with the R statnet package developed by Morris, Handcock, et al at the CSDE. The funds come from the NIH grants supporting the Network Modeling Project at the University of Washington (grants R01 HD41877 and R01 DA12831)
The focus is on adapting and developing visualization techniques for dynamic network data. The specific emphasis will be on techniques relevant for understanding:
a) infectious disease transmission (change in state of elements due to a network diffusion process) and
b) the stationary dynamics (model-based addition and removal of nodes/edges) of longitudinal network data and simulation output.
The goal is to develop robust, rigorous and repeatable procedures for visually interpreting time-based network data. We will achieve this by linking existing software components and improving existing techniques to generate animations and export movies from R or other statistical packages into standard formats suitable for use in presentations or websites.
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