Plot balalaika: Simple chart designs for long-tail distributed data

Mark M. Shovman, Ran Wolff

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Current approaches to summarising large arrays of data for presentation and communication mostly comprise reporting means with, e.g., Bar-charts. These methods are well-suited for unimodal, ideally normally-or near-normally distributed data, but are misleading for long-tail distributions that comprise most of the Big Data. We propose a succinct visualisation format, parallel in simplicity to bar-charts, that is suitable for communicating the gist of long-tail distributions, and show its efficiency empirically.

Original languageEnglish
Title of host publicationProceedings - Information Visualisation
Subtitle of host publicationComputer Graphics, Imaging and Visualisation, IV 2015
EditorsFatma Bouali, John Counsell, Sebastian Kernbach, Mark W. McK. Bannatyne, John Counsell, Chi Man Pun, Marjan Trutschl, Ebad Banissi, Weidong Huang, Gilles Venturini, Chun-Cheng Lin, Anna Ursyn, Remo Burkhard, Urska Cvek, Feng Lin, Theodor G. Wyeld, Jian J. Zhang, Martin J. Eppler, Georges Grinstein, Muhammad Sarfraz, Francis T. Marchese
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9781467375689
StatePublished - 18 Sep 2015
Externally publishedYes
Event19th International Conference on Information Visualisation, IV 2015 - Barcelona, Spain
Duration: 22 Jul 201524 Jul 2015

Publication series

NameProceedings of the International Conference on Information Visualisation
ISSN (Print)1093-9547


Conference19th International Conference on Information Visualisation, IV 2015

Bibliographical note

Publisher Copyright:
© 2015 IEEE.


  • Data visualization
  • Human computer interaction

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition


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