Using Cartograms to Visualize Population Normalized Big-Data Sets

Anthony Breitzman

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

Abstract

A map is often a useful way to visualize big-data sets that vary by region. For example, voting patterns by region, income levels by region, or tweet frequency by location are just some examples of data that benefit from being placed on a map. However, measuring any regional activity and placing it on a map is usually disappointing. Typically, whenever a bar chart or pie chart is placed on a map, it either covers something else up or visually disappoints in other ways. A heat-map overlaid on top of a map is better, but it tends to show areas of high activity but gives no way of highlighting areas between average levels and below average levels of activity. In this paper we show several examples of cartograms that solve this problem. A cartogram is a map in which a regional variable - such as population, Senate representation, income, patents issued, or tweet activity - is substituted for land area. The geometry or space of the map is distorted to convey the information of the regional variable in a much more realistic and visually persuasive manner.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018
EditorsYang Song, Bing Liu, Kisung Lee, Naoki Abe, Calton Pu, Mu Qiao, Nesreen Ahmed, Donald Kossmann, Jeffrey Saltz, Jiliang Tang, Jingrui He, Huan Liu, Xiaohua Hu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3575-3580
Number of pages6
ISBN (Electronic)9781538650356
DOIs
StatePublished - Jan 22 2019
Event2018 IEEE International Conference on Big Data, Big Data 2018 - Seattle, United States
Duration: Dec 10 2018Dec 13 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

Conference

Conference2018 IEEE International Conference on Big Data, Big Data 2018
CountryUnited States
CitySeattle
Period12/10/1812/13/18

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All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems

Cite this

Breitzman, A. (2019). Using Cartograms to Visualize Population Normalized Big-Data Sets. In Y. Song, B. Liu, K. Lee, N. Abe, C. Pu, M. Qiao, N. Ahmed, D. Kossmann, J. Saltz, J. Tang, J. He, H. Liu, & X. Hu (Eds.), Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 (pp. 3575-3580). [8622217] (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2018.8622217