Interactive visualization of enrollment data using parallel coordinates

Abstract

As one of the main tasks in colleges and universities, enrollment has a vital role in higher education. Visualization of enrollment data serves as an auxiliary to analyze and extract the potential and value of it. Due to the limitations of spatial imagination ability on multivariate data set, people can’t gain an intuitive sense of it. What is more, it’s difficult to display the variables and characteristics globally and simply using the common methods such as histogram, line chart and so on. It’s proposed that interactive visualization on multivariate enrollment data using parallel coordinates should be a simple and flexible approach. The comprehensive utilization of data modelling, data analysis and parallel coordinates aid to interpretation or mining on model, characteristics and rules hidden in the interior of enrollment data. Results of the application on the multivariate enrollment data set prove that, the method of parallel coordinates can implement visual analysis to multivariate Enrollment data flexibly and effectively.