Data Visualization in Educational Datasets Using a Rule-Based Inference System

Dynamic data visualization can be a very useful analytical tool for discovering insights in complex real-world data sets with high dimensionality and large variety of data types. We leverage publicly available data sets from Washington State\´s Public Education System to demonstrate usefulness of data visualization as a tool for analysis and effective decision making. We created "querybuilder", a web-based interface which allows the user to generate ad-hoc queries. Our online inference system efficiently generates dynamic visualizations for user-specified queries. We then address the question of how to select an appropriate visualization type that would be best suited for the result of a specific query on the given data set. The main motivation for this work is developing a rule based inference system to automatically select the appropriate visualization type.