Computing stable Demers cartograms

Soeren Nickel; Max Sondag; Wouter Meulemans; Markus Chimani; Stephen Kobourov; Jaakko Peltonen; Martin Nöllenburg

doi:10.1007/978-3-030-35802-0_4

Computing stable Demers cartograms

Soeren Nickel, Max Sondag, Wouter Meulemans, Markus Chimani, Stephen Kobourov, Jaakko Peltonen, Martin Nöllenburg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

203 Downloads (Pure)

Abstract

Cartograms are popular for visualizing numerical data for map regions. Maintaining correct adjacencies is a primary quality criterion for cartograms. When there are multiple data values per region (over time or different datasets) shown as animated or juxtaposed cartograms, preserving the viewer’s mental-map in terms of stability between cartograms is another important criterion. We present a method to compute stable Demers cartograms, where each region is shown as a square and similar data yield similar cartograms. We enforce orthogonal separation constraints with linear programming, and measure quality in terms of keeping adjacent regions close (cartogram quality) and using similar positions for a region between the different data values (stability). Our method guarantees ability to connect most lost adjacencies with minimal leaders. Experiments show our method yields good quality and stability.

Original language	English
Title of host publication	27th International Symposium Graph Drawing and Network Visualization (GD)
Editors	Daniel Archambault, Csaba D. Tóth
Place of Publication	Cham
Publisher	Springer
Pages	46-60
Number of pages	15
ISBN (Electronic)	978-3-030-35802-0
ISBN (Print)	978-3-030-35801-3
DOIs	https://doi.org/10.1007/978-3-030-35802-0_4
Publication status	Published - 2019
Event	27th International Symposium on Graph Drawing and Network Visualization, GD 2019 - Prague, Czech Republic Duration: 17 Sept 2019 → 20 Sept 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11904 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	27th International Symposium on Graph Drawing and Network Visualization, GD 2019
Country/Territory	Czech Republic
City	Prague
Period	17/09/19 → 20/09/19

Funding

This research was initiated at NII Shonan Meeting 127 ?Reimagining the Mental Map and Drawing Stability?. M. Sondag is supported by The Netherlands Organisation for Scientific Research (NWO) under project no. 639.023.20. S. Kobourov is supported by NSF grants CCF-1740858, CCF-1712119 and DMS-1839274. M. N?llenburg is supported by FWF grant P 31119.

Keywords

Cartograms
Mental-map preservation
Time-varying data

Access to Document

10.1007/978-3-030-35802-0_4

Author versionFinal author version , 796 KB

Cite this

Nickel, S., Sondag, M., Meulemans, W., Chimani, M., Kobourov, S., Peltonen, J., & Nöllenburg, M. (2019). Computing stable Demers cartograms. In D. Archambault, & C. D. Tóth (Eds.), 27th International Symposium Graph Drawing and Network Visualization (GD) (pp. 46-60). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11904 LNCS). Springer. https://doi.org/10.1007/978-3-030-35802-0_4

Nickel, Soeren ; Sondag, Max ; Meulemans, Wouter et al. / Computing stable Demers cartograms. 27th International Symposium Graph Drawing and Network Visualization (GD). editor / Daniel Archambault ; Csaba D. Tóth. Cham : Springer, 2019. pp. 46-60 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Computing stable Demers cartograms",

abstract = "Cartograms are popular for visualizing numerical data for map regions. Maintaining correct adjacencies is a primary quality criterion for cartograms. When there are multiple data values per region (over time or different datasets) shown as animated or juxtaposed cartograms, preserving the viewer{\textquoteright}s mental-map in terms of stability between cartograms is another important criterion. We present a method to compute stable Demers cartograms, where each region is shown as a square and similar data yield similar cartograms. We enforce orthogonal separation constraints with linear programming, and measure quality in terms of keeping adjacent regions close (cartogram quality) and using similar positions for a region between the different data values (stability). Our method guarantees ability to connect most lost adjacencies with minimal leaders. Experiments show our method yields good quality and stability.",

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Nickel, S, Sondag, M, Meulemans, W, Chimani, M, Kobourov, S, Peltonen, J & Nöllenburg, M 2019, Computing stable Demers cartograms. in D Archambault & CD Tóth (eds), 27th International Symposium Graph Drawing and Network Visualization (GD). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11904 LNCS, Springer, Cham, pp. 46-60, 27th International Symposium on Graph Drawing and Network Visualization, GD 2019, Prague, Czech Republic, 17/09/19. https://doi.org/10.1007/978-3-030-35802-0_4

Computing stable Demers cartograms. / Nickel, Soeren; Sondag, Max; Meulemans, Wouter et al.
27th International Symposium Graph Drawing and Network Visualization (GD). ed. / Daniel Archambault; Csaba D. Tóth. Cham: Springer, 2019. p. 46-60 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11904 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Nöllenburg, Martin

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Nickel S, Sondag M, Meulemans W, Chimani M, Kobourov S, Peltonen J et al. Computing stable Demers cartograms. In Archambault D, Tóth CD, editors, 27th International Symposium Graph Drawing and Network Visualization (GD). Cham: Springer. 2019. p. 46-60. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-35802-0_4

Computing stable Demers cartograms

Abstract

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Funding

Keywords

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