Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations

Collins, Christopher; Penn, Gerald; Carpendale, Sheelagh

doi:10.1109/tvcg.2009.122

Cited by 283 publications

(219 citation statements)

References 14 publications

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“…Areas of interest in a UML diagram can be highlighted using a deformed convex hull [22]. Isocontours-based bubblesets can be used to depict multiple relations defined on a set of items [25]. Automatic Euler diagrams, which show the grouping of subsets of items by drawing contiguous regions around them have also been considered [96].…”

Section: Alternative Representationsmentioning

confidence: 99%

Temporal Multivariate Networks

Archambault¹,

Abello²,

Kennedy³

et al. 2014

Lecture Notes in Computer Science

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Abstract. Networks that evolve over time, or dynamic graphs, have been of interest to the areas of information visualization and graph drawing for many years. Typically, its the structure of the dynamic graph that evolves as vertices and edges are added or removed from the graph. In a multivariate scenario, however, attributes play an important role and can also evolve over time. In this chapter, we characterize and survey methods for visualizing temporal multivariate networks. We also explore future applications and directions for this emerging area in the fields of information visualization and graph drawing.

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Section: Alternative Representationsmentioning

confidence: 99%

Temporal Multivariate Networks

Archambault¹,

Abello²,

Kennedy³

et al. 2014

Lecture Notes in Computer Science

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show abstract

“…Some hybrid layouts show the data in a primary layout and use a secondary visualization to add another data dimension. Bubble Sets by Collins et al [13] represents set relations among data entities on top of existing visualizations while keeping the primary layout intact and can be used with many primary visualizations, such as scatterplots, graphs, and maps. LineSets [1] create similar approach making use of curved lines to connect entities.…”

Section: Hybrid Visualizationmentioning

confidence: 99%

Exploring the Possibilities of Embedding Heterogeneous Data Attributes in Familiar Visualizations

Loorak

Périn

Collins³

et al. 2017

IEEE Trans. Visual. Comput. Graphics

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract-Heterogeneous multi-dimensional data are now sufficiently common that they can be referred to as ubiquitous. The most frequent approach to visualizing these data has been to propose new visualizations for representing these data. These new solutions are often inventive but tend to be unfamiliar. We take a different approach. We explore the possibility of extending well-known and familiar visualizations through including Heterogeneous Embedded Data Attributes (HEDA) in order to make familiar visualizations more powerful. We demonstrate how HEDA is a generic, interactive visualization component that can extend common visualization techniques while respecting the structure of the familiar layout. HEDA is a tabular visualization building block that enables individuals to visually observe, explore, and query their familiar visualizations through manipulation of embedded multivariate data. We describe the design space of HEDA by exploring its application to familiar visualizations in the D3 gallery. We characterize these familiar visualizations by the extent to which HEDA can facilitate data queries based on attribute reordering. Permanent repository link

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“…Reflecting the importance of understanding such data there have been a large number of techniques proposed for visualizing it such as [1,10,16,25,28,29,32,33,39]. Most of these techniques represent the sets using Euler diagrams.…”

Section: Introductionmentioning

confidence: 99%

The impact of topological and graphical choices on the perception of Euler diagrams

Blake

Rodgers

Howse

2016

Information Sciences

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This paper establishes the impact of topological and graphical properties on the comprehension of Euler diagrams. To-date, various studies have examined the impact of individual properties of Euler diagrams, such as curve shape and orientation. This has allowed us to establish guides for using these properties such as 'draw Euler diagrams with circles' and 'draw Euler diagrams without regard to orientation'. However, until the work described here, questions still remain, for example 'do these guides, when combined, make a significant difference to real-world Euler diagrams?', and if so, 'should they be used by those visualizing set data with Euler diagrams?' To answer these questions an empirical study was conducted to compare Euler diagrams that have been drawn by others for their real-world data, against versions that adhere to all of the guides in combination. The study establishes that both the accuracy and the speed with which information is derived from Euler diagrams is significantly improved when Euler diagrams adhere, where possible, to all the guides. The improvement is considerable when using the guided diagrams, with on average, the error rate being more than halved from 21.4% to 10.3%, and a 9 second improvement in the average time taken, from 34.2 seconds to 24.9 seconds. As Euler diagrams are regularly used to visualize information in a multitude of areas, ranging from crime control to social network analysis, our results indicate that applying the guides to these diagrams will improve the ability of users to accurately and quickly extract information.

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Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations

Cited by 283 publications

References 14 publications

Temporal Multivariate Networks

Temporal Multivariate Networks

Exploring the Possibilities of Embedding Heterogeneous Data Attributes in Familiar Visualizations

The impact of topological and graphical choices on the perception of Euler diagrams

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