The State of the Art in Cartograms

Nusrat, Sabrina; Kobourov, Stephen G.

doi:10.1111/cgf.12932

Cited by 87 publications

(70 citation statements)

References 105 publications

(151 reference statements)

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“…They proposed different classes of metrics: statistical distortion, topology distortion, shape distortion and complexity to assess quality. Nusrat et al [NK16] surveyed three different types of quality metrics: topology accuracy, geography accuracy, and statistical accuracy of the geospatial data applied to Cartograms. They offered guides to mitigate inaccuracies:…”

Section: Summary Of Approachesmentioning

confidence: 99%

Quality Metrics for Information Visualization

Behrisch

Blumenschein

Kim

et al. 2018

Computer Graphics Forum

101

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The visualization community has developed to date many intuitions and understandings of how to judge the quality of views in visualizing data. The computation of a visualization's quality and usefulness ranges from measuring clutter and overlap, up to the existence and perception of specific (visual) patterns. This survey attempts to report, categorize and unify the diverse understandings and aims to establish a common vocabulary that will enable a wide audience to understand their differences and subtleties. For this purpose, we present a commonly applicable quality metric formalization that should detail and relate all constituting parts of a quality metric. We organize our corpus of reviewed research papers along the data types established in the information visualization community: multi-and high-dimensional, relational, sequential, geospatial and text data. For each data type, we select the visualization subdomains in which quality metrics are an active research field and report their findings, reason on the underlying concepts, describe goals and outline the constraints and requirements. One central goal of this survey is to provide guidance on future research opportunities for the field and outline how different visualization communities could benefit from each other by applying or transferring knowledge to their respective subdomain. Additionally, we aim to motivate the visualization community to compare computed measures to the perception of humans.

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Section: Summary Of Approachesmentioning

confidence: 99%

Quality Metrics for Information Visualization

Behrisch

Blumenschein

Kim

et al. 2018

Computer Graphics Forum

101

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“…Nusrat et al follow‐up their previous survey with an extended version [NK16b]. They start by presenting a history of cartographic visualization, beginning with their origins in 1870.…”

Section: Survey Papersmentioning

confidence: 99%

Survey of Surveys (SoS) ‐ Mapping The Landscape of Survey Papers in Information Visualization

McNabb

Laramee

2017

Computer Graphics Forum

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Information visualization as a field is growing rapidly in popularity since the first information visualization conference in 1995. However, as a consequence of its growth, it is increasingly difficult to follow the growing body of literature within the field. Survey papers and literature reviews are valuable tools for managing the great volume of previously published research papers, and the quantity of survey papers in visualization has reached a critical mass. To this end, this survey paper takes a quantum step forward by surveying and classifying literature survey papers in order to help researchers understand the current landscape of Information Visualization. It is, to our knowledge, the first survey of survey papers (SoS) in Information Visualization. This paper classifies survey papers into natural topic clusters which enables readers to find relevant literature and develops the first classification of classifications. The paper also enables researchers to identify both mature and less developed research directions as well as identify future directions. It is a valuable resource for both newcomers and experienced researchers in and outside the field of Information Visualization and Visual Analytics.

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“…Cartograms are not new: their history is described by Dorling (1996); a more recent review is provided by Nusrat and Kobourov (2016). Over the 20-year gap between those publications, what was once an esoteric method of cartographic visualisation has become much more common as the range of software available to produce cartograms has expanded.…”

Section: Choropleth Maps Cartograms and The Problems Of Representationmentioning

confidence: 99%

Mapping the changing residential geography of White British secondary school children in England using visually balanced cartograms and hexograms

2018

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Harris, R., Charlton, M., & Brunsdon, C. (2018). Mapping the changing residential geography of White British secondary school children in England using visually balanced cartograms and hexograms. Journal of Maps, 14(1), 65-72. https University of Bristol -Explore Bristol Research General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms In the context of debates about segregation within the UK, this paper maps the residential geography of two groups of White British school children, one of which was in secondary school in 2011 and the other in 2017. To present that geography, hexograms are introduced as a complement to visually balanced cartograms, both of which seek to address the problems of invisibility and distortion encountered with more conventional choropleth and cartogram maps. The nature of these problems is introduced, our solutions discussed, and the methods applied to the case study, which allow changes in the geography to be seen. ARTICLE HISTORY

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The State of the Art in Cartograms

Cited by 87 publications

References 105 publications

Quality Metrics for Information Visualization

Quality Metrics for Information Visualization

Survey of Surveys (SoS) ‐ Mapping The Landscape of Survey Papers in Information Visualization

Mapping the changing residential geography of White British secondary school children in England using visually balanced cartograms and hexograms

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