The sampling lens: Making sense of saturated visualisations

Geoffrey Ellis; Enrico Bertini; Alan Dix

doi:10.1145/1056808.1056914

The sampling lens: Making sense of saturated visualisations

Geoffrey Ellis^*, Enrico Bertini, Alan Dix

^*Corresponding author for this work

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

34 Citations (Scopus)

Abstract

Information visualisation systems frequently have to deal with large amounts of data and this often leads to saturated areas in the display with considerable overplotting. This paper introduces the Sampling Lens, a novel tool that utilizes random sampling to reduce the clutter within a moveable region, thus allowing the user to uncover any potentially interesting patterns and trends in the data while still being able to view the sample in context. We demonstrate the versatility of the tool by adding sampling lenses to scatter and parallel co-ordinate visualisations. We also consider some implementation issues and present initial user evaluation results.

Original language	English
Title of host publication	CHI'05 Extended Abstracts on Human Factors in Computing Systems, CHI EA'05
Pages	1351-1354
Number of pages	4
DOIs	https://doi.org/10.1145/1056808.1056914
Publication status	Published - 2 Apr 2005
Externally published	Yes
Event	Conference on Human Factors in Computing Systems, CHI EA 2005 - Portland, OR, United States Duration: 2 Apr 2005 → 7 Apr 2005

Conference

Conference	Conference on Human Factors in Computing Systems, CHI EA 2005
Country/Territory	United States
City	Portland, OR
Period	2/04/05 → 7/04/05

Keywords

Clutter
Density reduction
Information visualisation
Lens
Overplotting
Random sampling
Sampling

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10.1145/1056808.1056914

Cite this

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title = "The sampling lens: Making sense of saturated visualisations",

abstract = "Information visualisation systems frequently have to deal with large amounts of data and this often leads to saturated areas in the display with considerable overplotting. This paper introduces the Sampling Lens, a novel tool that utilizes random sampling to reduce the clutter within a moveable region, thus allowing the user to uncover any potentially interesting patterns and trends in the data while still being able to view the sample in context. We demonstrate the versatility of the tool by adding sampling lenses to scatter and parallel co-ordinate visualisations. We also consider some implementation issues and present initial user evaluation results.",

keywords = "Clutter, Density reduction, Information visualisation, Lens, Overplotting, Random sampling, Sampling",

author = "Geoffrey Ellis and Enrico Bertini and Alan Dix",

year = "2005",

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day = "2",

doi = "10.1145/1056808.1056914",

language = "English",

isbn = "1595930027",

pages = "1351--1354",

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note = "Conference on Human Factors in Computing Systems, CHI EA 2005 ; Conference date: 02-04-2005 Through 07-04-2005",

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AU - Ellis, Geoffrey

AU - Bertini, Enrico

AU - Dix, Alan

PY - 2005/4/2

Y1 - 2005/4/2

N2 - Information visualisation systems frequently have to deal with large amounts of data and this often leads to saturated areas in the display with considerable overplotting. This paper introduces the Sampling Lens, a novel tool that utilizes random sampling to reduce the clutter within a moveable region, thus allowing the user to uncover any potentially interesting patterns and trends in the data while still being able to view the sample in context. We demonstrate the versatility of the tool by adding sampling lenses to scatter and parallel co-ordinate visualisations. We also consider some implementation issues and present initial user evaluation results.

AB - Information visualisation systems frequently have to deal with large amounts of data and this often leads to saturated areas in the display with considerable overplotting. This paper introduces the Sampling Lens, a novel tool that utilizes random sampling to reduce the clutter within a moveable region, thus allowing the user to uncover any potentially interesting patterns and trends in the data while still being able to view the sample in context. We demonstrate the versatility of the tool by adding sampling lenses to scatter and parallel co-ordinate visualisations. We also consider some implementation issues and present initial user evaluation results.

KW - Clutter

KW - Density reduction

KW - Information visualisation

KW - Lens

KW - Overplotting

KW - Random sampling

KW - Sampling

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U2 - 10.1145/1056808.1056914

DO - 10.1145/1056808.1056914

M3 - Conference contribution

AN - SCOPUS:84869135852

SN - 1595930027

SN - 9781595930026

SP - 1351

EP - 1354

BT - CHI'05 Extended Abstracts on Human Factors in Computing Systems, CHI EA'05

Y2 - 2 April 2005 through 7 April 2005

ER -

The sampling lens: Making sense of saturated visualisations

Abstract

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Keywords

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