Making data visualization more efficient and effective: a survey

Xuedi Qin, Yuyu Luo, Nan Tang, Guoliang Li

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
JournalVLDB Journal
DOIs
Publication statusAccepted/In press - 1 Jan 2019

Fingerprint

Data visualization
Visualization
Specifications
Industry
Decision making

Keywords

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

ASJC Scopus subject areas

  • Information Systems
  • Hardware and Architecture

Cite this

Making data visualization more efficient and effective : a survey. / Qin, Xuedi; Luo, Yuyu; Tang, Nan; Li, Guoliang.

In: VLDB Journal, 01.01.2019.

Research output: Contribution to journalArticle

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