Visualization of temporal and spatial tensor data is a challenging task due to the large amount of multi-dimensional data. In most of the visualization, scientists are interested in finding certain defects, anomalies, or correlations while exploring data. Hence, visualization requires efficient exploration and representation techniques. In order to use the nematic liquid crystal (NLC) as a biosensor, scientists need to study and explore simulations for understanding the relationship between topological defects and the biological specimen.

To solve the above problem, we merge scientific and information visualization techniques to create a controlled exploration environment. System enables a user to filter and explore NLC data sets for orientation defects. We introduce a three level visualization approach for exploring tensor data sets using timeline, parallel coordinate, and glyph based visualization. Visualization helps in reducing unnecessary data at each stage and focus on the relevant ones. This abstract discusses the goal, approach and various research issues found in the design of the NLC data visualization system.