A Review on Visualization Recommendation Strategies

Choosing the best visualization of a given dataset becomes more and more complex as not only the amount of data, but also the number of visualization types and the number of potential uses of visualizations grow tremendously. This challenge has spurred on the research into visualization recommendation systems. The ultimate aim of such a system is the suggestion of visualizations which provide interesting insights into the data. It should ideally consider data characteristics, domain knowledge and individual preferences to produce aesthetically appealing and easy to understand charts. Based on the mentioned factors, we have reviewed in this paper the state-of-the-art in visualization recommendation systems starting from the earliest attempt made on this subject. We identify challenges to visualization and visualization recommendation to guide future research directions.

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