A Question-Oriented Visualization Recommendation Approach for Data Exploration

The increasingly rapid growth of data production and the consequent need to explore data to obtain answers to the most varied questions have promoted the development of tools to facilitate the manipulation and construction of data visualizations. However, building useful data visualizations is not a trivial task: it may involve a large number of subtle decisions from experienced designers. In this paper, we present an approach that uses a set of heuristics to recommend data visualizations associated with questions, in order to facilitate the understanding of the recommendations and assisting the visual exploration process. Our approach was implemented and evaluated through the VisMaker tool. We carried out two studies comparing VisMaker with Voyager 2 and analyzed some aspects of the recommendation approaches through the participants' feedbacks. As a result, we found some advantages of our approach and gathered comments to help improve the development of visualization recommender tools.