Making data visualization more efficient and effective: a survey


Data visualization is crucial in today’s data-driven business world, which has been widely used for helping decision making that is closely related to major revenues of many industrial companies. However, due to the high demand of data processing w.r.t. the volume, velocity, and veracity of data, there is an emerging need for database experts to help for efficient and effective data visualization. In response to this demand, this article surveys techniques that make data visualization more efficient and effective. (1) Visualization specifications define how the users can specify their requirements for generating visualizations. (2) Efficient approaches for data visualization process the data and a given visualization specification, which then produce visualizations with the primary target to be efficient and scalable at an interactive speed. (3) Data visualization recommendation is to auto-complete an incomplete specification, or to discover more interesting visualizations based on a reference visualization.

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    Note that, our pipeline and terminologies used in this paper are slightly different than those used in the visualization community. Please refer to for more details.

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Funding was provided by 973 Program of China (Grant No. 2015CB358700) and National Natural Science Foundation of China (Grant Nos. 61632016, 61521002, 61661166012).

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Qin, X., Luo, Y., Tang, N. et al. Making data visualization more efficient and effective: a survey. The VLDB Journal 29, 93–117 (2020).

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  • Data visualization
  • Visualization languages
  • Efficient data visualization
  • Data visualization recommendation