Towards democratizing relational data visualization

Nan Tang, Eugene Wu, Guoliang Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The problem of data visualization is to transform data into a visual context such that people can easily understand the significance of data. Nowadays, data visualization becomes especially important, because it is the de facto standard for modern business intelligence and successful data science. This tutorial will cover three specific topics: visualization languages define how the users can interact with various visualization systems; efficient data visualization processes the data and produces visualizations based on well-specified user queries; smart data visualization recommends data visualizations based on underspecified user queries. In this tutorial, we will go logically through these prior art, paying particular attentions on problems that may attract the interest from the database community.

Original languageEnglish
Title of host publicationSIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data
PublisherAssociation for Computing Machinery
Pages2025-2030
Number of pages6
ISBN (Electronic)9781450356435
DOIs
Publication statusPublished - 25 Jun 2019
Event2019 International Conference on Management of Data, SIGMOD 2019 - Amsterdam, Netherlands
Duration: 30 Jun 20195 Jul 2019

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Conference

Conference2019 International Conference on Management of Data, SIGMOD 2019
CountryNetherlands
CityAmsterdam
Period30/6/195/7/19

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Keywords

  • Data visualization
  • Relational data

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Tang, N., Wu, E., & Li, G. (2019). Towards democratizing relational data visualization. In SIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data (pp. 2025-2030). (Proceedings of the ACM SIGMOD International Conference on Management of Data). Association for Computing Machinery. https://doi.org/10.1145/3299869.3314029