2019
Nardini, Pascal; Chen, Min; Samsel, Francesca; Bujack, Roxana; Bottinger, Michael; Scheuermann, Gerik
The making of continuous colormaps Journal Article
In: IEEE transactions on visualization and computer graphics, vol. 27, no. 6, pp. 3048–3063, 2019.
Abstract | Links | BibTeX | Tags: ccc-tool, color perception, colormaps
@article{nardini2019making,
title = {The making of continuous colormaps},
author = {Pascal Nardini and Min Chen and Francesca Samsel and Roxana Bujack and Michael Bottinger and Gerik Scheuermann},
url = {http://www.informatik.uni-leipzig.de/~bujack/2020ccc.pdf},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
journal = {IEEE transactions on visualization and computer graphics},
volume = {27},
number = {6},
pages = {3048--3063},
publisher = {IEEE},
abstract = {Continuous colormaps are integral parts of many visualization techniques, such as heat-maps, surface plots, and flow visualization. Despite that the critiques of rainbow colormaps have been around and well-acknowledged for three decades, rainbow colormaps are still widely used today. One reason behind the resilience of rainbow colormaps is the lack of tools for users to create a continuous colormap that encodes semantics specific to the application concerned. In this paper, we present a web-based software system, CCC-Tool (short for Charting Continuous Colormaps) under the URL https://ccctool.com, for creating, editing, and analyzing such application-specific colormaps. We introduce the notion of “colormap specification (CMS)” that maintains the essential semantics required for defining a color mapping scheme. We provide users with a set of advanced utilities for constructing CMS’s with various levels of complexity, examining their quality attributes using different plots, and exporting them to external application software. We present two case studies, demonstrating that the CCC-Tool can help domain scientists as well as visualization experts in designing semantically-rich colormaps.},
keywords = {ccc-tool, color perception, colormaps},
pubstate = {published},
tppubtype = {article}
}
Continuous colormaps are integral parts of many visualization techniques, such as heat-maps, surface plots, and flow visualization. Despite that the critiques of rainbow colormaps have been around and well-acknowledged for three decades, rainbow colormaps are still widely used today. One reason behind the resilience of rainbow colormaps is the lack of tools for users to create a continuous colormap that encodes semantics specific to the application concerned. In this paper, we present a web-based software system, CCC-Tool (short for Charting Continuous Colormaps) under the URL https://ccctool.com, for creating, editing, and analyzing such application-specific colormaps. We introduce the notion of “colormap specification (CMS)” that maintains the essential semantics required for defining a color mapping scheme. We provide users with a set of advanced utilities for constructing CMS’s with various levels of complexity, examining their quality attributes using different plots, and exporting them to external application software. We present two case studies, demonstrating that the CCC-Tool can help domain scientists as well as visualization experts in designing semantically-rich colormaps.
2017
Samsel, Francesca; Patchett, John; Rogers, David; Tsai, Karen
Employing Color Theory to Visualize Volume-rendered Multivariate Ensembles of Asteroid Impact Simulations Inproceedings
In: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 1126-1134, ACM, 2017, ISBN: 978-1-4503-4656-6, (LA-UR-17-20419).
Abstract | Links | BibTeX | Tags: colormaps, ensemble visualization, scientific visualization, visualization design, volume rendering
@inproceedings{LAPR-2017-027464,
title = {Employing Color Theory to Visualize Volume-rendered Multivariate Ensembles of Asteroid Impact Simulations},
author = {Francesca Samsel and John Patchett and David Rogers and Karen Tsai},
url = {http://doi.acm.org/10.1145/3027063.3053337},
doi = {10.1145/3027063.3053337},
isbn = {978-1-4503-4656-6},
year = {2017},
date = {2017-05-06},
booktitle = {Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems},
pages = {1126-1134},
publisher = {ACM},
series = {CHI EA '17},
abstract = {We describe explorations and innovations developed to help scientists understand an ensemble of large scale simulations of asteroid impacts in the ocean. The simulations were run to help scientists determine the characteristics of asteroids that NASA should track, so that communities at risk from impact can be given advanced notice. Of relevance to the CHI community are 1) hands-on workflow issues specific to exploring ensembles of large scientific data, 2) innovations in exploring such data ensembles with color, and 3) examples of multidisciplinary collaboration.},
note = {LA-UR-17-20419},
keywords = {colormaps, ensemble visualization, scientific visualization, visualization design, volume rendering},
pubstate = {published},
tppubtype = {inproceedings}
}
We describe explorations and innovations developed to help scientists understand an ensemble of large scale simulations of asteroid impacts in the ocean. The simulations were run to help scientists determine the characteristics of asteroids that NASA should track, so that communities at risk from impact can be given advanced notice. Of relevance to the CHI community are 1) hands-on workflow issues specific to exploring ensembles of large scientific data, 2) innovations in exploring such data ensembles with color, and 3) examples of multidisciplinary collaboration.
Samsel, Francesca; Turton, Terece; Wolfram, Phillip; Bujack, Roxana
Intuitive Colormaps for Environmental Visualization Inproceedings
In: Rink, Karsten; Middel, Ariane; Zeckzer, Dirk; Bujack, Roxana (Ed.): Workshop on Visualisation in Environmental Sciences (EnvirVis), The Eurographics Association, 2017, ISBN: 978-3-03868-040-6, (LA-UR-17-22224).
Abstract | Links | BibTeX | Tags: colormaps, environmental sciences
@inproceedings{info:lanl-repo/lareport/LA-UR-17-22224,
title = {Intuitive Colormaps for Environmental Visualization},
author = {Francesca Samsel and Terece Turton and Phillip Wolfram and Roxana Bujack},
editor = {Karsten Rink and Ariane Middel and Dirk Zeckzer and Roxana Bujack},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/IntuitiveColormapsforEnvironmentalVisualization.pdf},
doi = {10.2312/envirvis.20171105},
isbn = {978-3-03868-040-6},
year = {2017},
date = {2017-03-16},
booktitle = {Workshop on Visualisation in Environmental Sciences (EnvirVis)},
publisher = {The Eurographics Association},
abstract = {Visualizations benefit from the use of intuitive colors, enabling an observer to make use of more automatic, subconscious channels. In this paper, we apply the concept of intuitive color to the generation of thematic colormaps for the environmental sciences. In particular, we provide custom sets of colormaps for water, atmosphere, land, and vegetation. These have been integrated into the online tool: ColorMoves: The Environment to enable the environmental scientist to tailor them precisely to the data and tasks in a simple drag-and-drop workflow.},
howpublished = {EnvirVis ; 2017-06-12 - 2017-06-13 ; Barcelona, Spain},
note = {LA-UR-17-22224},
keywords = {colormaps, environmental sciences},
pubstate = {published},
tppubtype = {inproceedings}
}
Visualizations benefit from the use of intuitive colors, enabling an observer to make use of more automatic, subconscious channels. In this paper, we apply the concept of intuitive color to the generation of thematic colormaps for the environmental sciences. In particular, we provide custom sets of colormaps for water, atmosphere, land, and vegetation. These have been integrated into the online tool: ColorMoves: The Environment to enable the environmental scientist to tailor them precisely to the data and tasks in a simple drag-and-drop workflow.
Ware, Colin; Turton, Terece; Samsel, Francesca; Bujack, Roxana; Rogers, David
Evaluating the Perceptual Uniformity of Color Sequences for Feature Discrimination Inproceedings
In: Lawonn, Kai; Smit, Noeska; Cunningham, Douglas (Ed.): EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3), The Eurographics Association, 2017, ISBN: 978-3-03868-041-3, (LA-UR-17-24206).
Abstract | Links | BibTeX | Tags: colormaps, visualization
@inproceedings{eurorv3.20171107,
title = {Evaluating the Perceptual Uniformity of Color Sequences for Feature Discrimination},
author = {Colin Ware and Terece Turton and Francesca Samsel and Roxana Bujack and David Rogers},
editor = {Kai Lawonn and Noeska Smit and Douglas Cunningham},
url = {https://diglib.eg.org/handle/10.2312/eurorv320171107},
isbn = {978-3-03868-041-3},
year = {2017},
date = {2017-01-01},
booktitle = {EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3)},
publisher = {The Eurographics Association},
abstract = {Probably the most common method for visualizing univariate data maps is through pseudocoloring and one of the most commonly cited requirements of a good colormap is that it be perceptually uniform. This means that differences between adjacent colors in the sequence be equally distinct. The practical value of uniformity is for features in the data to be equally distinctive no matter where they lie in the colormap, but there are reasons for thinking that uniformity in terms of feature detection may not be achieved by current methods which are based on the use of uniform color spaces. In this paper we provide a new method for directly evaluating colormaps in terms of their capacity for feature resolution. We apply the method in a study using Amazon Mechanical Turk to evaluate seven colormaps. Among other findings the results show that two new double ended sequences have the highest discriminative power and good uniformity. Ways in which the technique can be applied include the design of colormaps for uniformity, and a method for evaluating colormaps through feature discrimination curves for differently sized features.},
note = {LA-UR-17-24206},
keywords = {colormaps, visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Probably the most common method for visualizing univariate data maps is through pseudocoloring and one of the most commonly cited requirements of a good colormap is that it be perceptually uniform. This means that differences between adjacent colors in the sequence be equally distinct. The practical value of uniformity is for features in the data to be equally distinctive no matter where they lie in the colormap, but there are reasons for thinking that uniformity in terms of feature detection may not be achieved by current methods which are based on the use of uniform color spaces. In this paper we provide a new method for directly evaluating colormaps in terms of their capacity for feature resolution. We apply the method in a study using Amazon Mechanical Turk to evaluate seven colormaps. Among other findings the results show that two new double ended sequences have the highest discriminative power and good uniformity. Ways in which the technique can be applied include the design of colormaps for uniformity, and a method for evaluating colormaps through feature discrimination curves for differently sized features.
Bujack, Roxana; Turton, Terece; Samsel, Francesca; Ware, Colin; Rogers, David; Ahrens, James
The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps Inproceedings
In: IEEE Visualization, 2017.
Abstract | Links | BibTeX | Tags: color theory, colormaps, linearity
@inproceedings{bujack2017good,
title = {The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps},
author = {Roxana Bujack and Terece Turton and Francesca Samsel and Colin Ware and David Rogers and James Ahrens},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/10/TheGoodtheBadandtheUgly.pdf},
year = {2017},
date = {2017-01-01},
booktitle = {IEEE Visualization},
abstract = {A myriad of design rules for what constitutes a “good” colormap can be found in the literature. Some common rules include order, uniformity, and high discriminative power. However, the meaning of many of these terms is often ambiguous or open to interpretation. At times, different authors may use the same term to describe different concepts or the same rule is described by varying nomenclature. These ambiguities stand in the way of collaborative work, the design of experiments to assess the characteristics of colormaps, and automated colormap generation.
In this paper, we review current and historical guidelines for colormap design. We propose a specified taxonomy and provide unambiguous mathematical definitions for the most common design rules.},
keywords = {color theory, colormaps, linearity},
pubstate = {published},
tppubtype = {inproceedings}
}
A myriad of design rules for what constitutes a “good” colormap can be found in the literature. Some common rules include order, uniformity, and high discriminative power. However, the meaning of many of these terms is often ambiguous or open to interpretation. At times, different authors may use the same term to describe different concepts or the same rule is described by varying nomenclature. These ambiguities stand in the way of collaborative work, the design of experiments to assess the characteristics of colormaps, and automated colormap generation.
In this paper, we review current and historical guidelines for colormap design. We propose a specified taxonomy and provide unambiguous mathematical definitions for the most common design rules.
In this paper, we review current and historical guidelines for colormap design. We propose a specified taxonomy and provide unambiguous mathematical definitions for the most common design rules.
2016
Samsel, Francesca; Klassen, Sebastian; Petersen, Mark; Turton, Terece; Abram, Greg; Rogers, David; Ahrens, James
Interactive Colormapping: Enabling Multiple Data Ranges, Detailed Views of Ocean Salinity Inproceedings
In: Proceedings of the 34rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, ACM, San Jose, California, 2016, (LA-UR-15-20105).
Abstract | Links | BibTeX | Tags: climate science, color perception, color theory, colormaps, high-resolution datasets, scientific visualization
@inproceedings{Samsel:2016:CIP:2702613.2702975,
title = {Interactive Colormapping: Enabling Multiple Data Ranges, Detailed Views of Ocean Salinity},
author = {Francesca Samsel and Sebastian Klassen and Mark Petersen and Terece Turton and Greg Abram and David Rogers and James Ahrens},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/InteractiveColormapping.pdf},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of the 34rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems},
publisher = {ACM},
address = {San Jose, California},
series = {CHI EA '16},
abstract = {Ocean salinity is a critical component to understanding climate change. Salinity concentrations and temperature drive large ocean currents which in turn drive global weather patterns. Melting ice caps lower salinity at the poles while river deltas bring fresh water into the ocean worldwide. These processes slow ocean currents, changing weather patterns and producing extreme climate events which disproportionally affect those living in poverty. Analysis of salinity presents a unique visualization challenge. Important data are found in narrow data ranges, varying with global location. Changing values of salinity are important in understanding ocean currents, but are difficult to map to colors using traditional tools. Commonly used colormaps may not provide sufficient detail for this data. Current editing tools do not easily enable a scientist to explore the subtleties of salinity. We present a workflow, enabled by an interactive colormap tool that allows a scientist to interactively apply sophisticated colormaps to scalar data. The intuitive and immediate interaction of the scientist with the data is a critical contribution of this work.},
note = {LA-UR-15-20105},
keywords = {climate science, color perception, color theory, colormaps, high-resolution datasets, scientific visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Ocean salinity is a critical component to understanding climate change. Salinity concentrations and temperature drive large ocean currents which in turn drive global weather patterns. Melting ice caps lower salinity at the poles while river deltas bring fresh water into the ocean worldwide. These processes slow ocean currents, changing weather patterns and producing extreme climate events which disproportionally affect those living in poverty. Analysis of salinity presents a unique visualization challenge. Important data are found in narrow data ranges, varying with global location. Changing values of salinity are important in understanding ocean currents, but are difficult to map to colors using traditional tools. Commonly used colormaps may not provide sufficient detail for this data. Current editing tools do not easily enable a scientist to explore the subtleties of salinity. We present a workflow, enabled by an interactive colormap tool that allows a scientist to interactively apply sophisticated colormaps to scalar data. The intuitive and immediate interaction of the scientist with the data is a critical contribution of this work.
2015
Samsel, Francesca
Understanding via Color Presentation
27.10.2015, (IEEE Vis 2015 Color Mapping Panel).
Abstract | Links | BibTeX | Tags: colormaps
@misc{Samsel1027,
title = {Understanding via Color},
author = {Francesca Samsel},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/UnderstandingViaColor.pptx
http://ieeevis.org/year/2015/info/overview-amp-topics/panels},
year = {2015},
date = {2015-10-27},
abstract = {In this panel, we highlight optimal solutions for designing and building color maps in visualization applications and presentations. Our panelists represent artists, software engineers, cartographers, color scientists, perceptual psychologists, and visualization researchers who have contributed effective solutions to applying color to data visualization. Each panelist will highlight their perspective as well as tips and tricks for color map solutions. Drawing on perspectives from many disciplines, the panel will identify gaps in our understanding about the use of color in visualization and will identify future research directions.},
note = {IEEE Vis 2015 Color Mapping Panel},
keywords = {colormaps},
pubstate = {published},
tppubtype = {presentation}
}
In this panel, we highlight optimal solutions for designing and building color maps in visualization applications and presentations. Our panelists represent artists, software engineers, cartographers, color scientists, perceptual psychologists, and visualization researchers who have contributed effective solutions to applying color to data visualization. Each panelist will highlight their perspective as well as tips and tricks for color map solutions. Drawing on perspectives from many disciplines, the panel will identify gaps in our understanding about the use of color in visualization and will identify future research directions.
Samsel, Francesca; Petersen, Mark; Geld, Terece; Abram, Greg; Wendelberger, Joanne; Ahrens, James
Colormaps That Improve Perception of High-Resolution Ocean Data Inproceedings
In: Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, pp. 703–710, ACM, Seoul, Republic of Korea, 2015, ISBN: 978-1-4503-3146-3, (LA-UR-15-20105).
Abstract | Links | BibTeX | Tags: climate science, color perception, color theory, colormaps, high-resolution datasets, scientific visualization
@inproceedings{Samsel:2015:CIP:2702613.2702975,
title = {Colormaps That Improve Perception of High-Resolution Ocean Data},
author = {Francesca Samsel and Mark Petersen and Terece Geld and Greg Abram and Joanne Wendelberger and James Ahrens},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/ColormapsThatImprovePerceptionOfHigh-ResolutionOceanData.pdf},
doi = {10.1145/2702613.2702975},
isbn = {978-1-4503-3146-3},
year = {2015},
date = {2015-01-01},
booktitle = {Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems},
pages = {703--710},
publisher = {ACM},
address = {Seoul, Republic of Korea},
series = {CHI EA '15},
abstract = {Scientists from the Climate, Ocean and Sea Ice Modeling Team (COSIM) at the Los Alamos National Laboratory (LANL) are interested in gaining a deeper understanding of three primary ocean currents: the Gulf Stream, the Kuroshio Current, and the Agulhas Current & Retroflection. To address these needs, visual artist Francesca Samsel teamed up with experts from the areas of computer science, climate science, statistics, and perceptual science. By engaging an artist specializing in color, we created colormaps that provide the ability to see greater detail in these high-resolution datasets. The new colormaps applied to the POP dataset enabled scientists to see areas of interest unclear using standard colormaps. Improvements in the perceptual range of color allowed scientists to highlight structures within specific ocean currents. Work with the COSIM team members drove development of nested colormaps which provide further detail to the scientists.},
note = {LA-UR-15-20105},
keywords = {climate science, color perception, color theory, colormaps, high-resolution datasets, scientific visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Scientists from the Climate, Ocean and Sea Ice Modeling Team (COSIM) at the Los Alamos National Laboratory (LANL) are interested in gaining a deeper understanding of three primary ocean currents: the Gulf Stream, the Kuroshio Current, and the Agulhas Current & Retroflection. To address these needs, visual artist Francesca Samsel teamed up with experts from the areas of computer science, climate science, statistics, and perceptual science. By engaging an artist specializing in color, we created colormaps that provide the ability to see greater detail in these high-resolution datasets. The new colormaps applied to the POP dataset enabled scientists to see areas of interest unclear using standard colormaps. Improvements in the perceptual range of color allowed scientists to highlight structures within specific ocean currents. Work with the COSIM team members drove development of nested colormaps which provide further detail to the scientists.
: . .
1.
Nardini, Pascal; Chen, Min; Samsel, Francesca; Bujack, Roxana; Bottinger, Michael; Scheuermann, Gerik
The making of continuous colormaps Journal Article
In: IEEE transactions on visualization and computer graphics, vol. 27, no. 6, pp. 3048–3063, 2019.
@article{nardini2019making,
title = {The making of continuous colormaps},
author = {Pascal Nardini and Min Chen and Francesca Samsel and Roxana Bujack and Michael Bottinger and Gerik Scheuermann},
url = {http://www.informatik.uni-leipzig.de/~bujack/2020ccc.pdf},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
journal = {IEEE transactions on visualization and computer graphics},
volume = {27},
number = {6},
pages = {3048--3063},
publisher = {IEEE},
abstract = {Continuous colormaps are integral parts of many visualization techniques, such as heat-maps, surface plots, and flow visualization. Despite that the critiques of rainbow colormaps have been around and well-acknowledged for three decades, rainbow colormaps are still widely used today. One reason behind the resilience of rainbow colormaps is the lack of tools for users to create a continuous colormap that encodes semantics specific to the application concerned. In this paper, we present a web-based software system, CCC-Tool (short for Charting Continuous Colormaps) under the URL https://ccctool.com, for creating, editing, and analyzing such application-specific colormaps. We introduce the notion of “colormap specification (CMS)” that maintains the essential semantics required for defining a color mapping scheme. We provide users with a set of advanced utilities for constructing CMS’s with various levels of complexity, examining their quality attributes using different plots, and exporting them to external application software. We present two case studies, demonstrating that the CCC-Tool can help domain scientists as well as visualization experts in designing semantically-rich colormaps.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Continuous colormaps are integral parts of many visualization techniques, such as heat-maps, surface plots, and flow visualization. Despite that the critiques of rainbow colormaps have been around and well-acknowledged for three decades, rainbow colormaps are still widely used today. One reason behind the resilience of rainbow colormaps is the lack of tools for users to create a continuous colormap that encodes semantics specific to the application concerned. In this paper, we present a web-based software system, CCC-Tool (short for Charting Continuous Colormaps) under the URL https://ccctool.com, for creating, editing, and analyzing such application-specific colormaps. We introduce the notion of “colormap specification (CMS)” that maintains the essential semantics required for defining a color mapping scheme. We provide users with a set of advanced utilities for constructing CMS’s with various levels of complexity, examining their quality attributes using different plots, and exporting them to external application software. We present two case studies, demonstrating that the CCC-Tool can help domain scientists as well as visualization experts in designing semantically-rich colormaps.
2.
Samsel, Francesca; Patchett, John; Rogers, David; Tsai, Karen
Employing Color Theory to Visualize Volume-rendered Multivariate Ensembles of Asteroid Impact Simulations Inproceedings
In: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 1126-1134, ACM, 2017, ISBN: 978-1-4503-4656-6, (LA-UR-17-20419).
@inproceedings{LAPR-2017-027464,
title = {Employing Color Theory to Visualize Volume-rendered Multivariate Ensembles of Asteroid Impact Simulations},
author = {Francesca Samsel and John Patchett and David Rogers and Karen Tsai},
url = {http://doi.acm.org/10.1145/3027063.3053337},
doi = {10.1145/3027063.3053337},
isbn = {978-1-4503-4656-6},
year = {2017},
date = {2017-05-06},
booktitle = {Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems},
pages = {1126-1134},
publisher = {ACM},
series = {CHI EA '17},
abstract = {We describe explorations and innovations developed to help scientists understand an ensemble of large scale simulations of asteroid impacts in the ocean. The simulations were run to help scientists determine the characteristics of asteroids that NASA should track, so that communities at risk from impact can be given advanced notice. Of relevance to the CHI community are 1) hands-on workflow issues specific to exploring ensembles of large scientific data, 2) innovations in exploring such data ensembles with color, and 3) examples of multidisciplinary collaboration.},
note = {LA-UR-17-20419},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We describe explorations and innovations developed to help scientists understand an ensemble of large scale simulations of asteroid impacts in the ocean. The simulations were run to help scientists determine the characteristics of asteroids that NASA should track, so that communities at risk from impact can be given advanced notice. Of relevance to the CHI community are 1) hands-on workflow issues specific to exploring ensembles of large scientific data, 2) innovations in exploring such data ensembles with color, and 3) examples of multidisciplinary collaboration.
3.
Samsel, Francesca; Turton, Terece; Wolfram, Phillip; Bujack, Roxana
Intuitive Colormaps for Environmental Visualization Inproceedings
In: Rink, Karsten; Middel, Ariane; Zeckzer, Dirk; Bujack, Roxana (Ed.): Workshop on Visualisation in Environmental Sciences (EnvirVis), The Eurographics Association, 2017, ISBN: 978-3-03868-040-6, (LA-UR-17-22224).
@inproceedings{info:lanl-repo/lareport/LA-UR-17-22224,
title = {Intuitive Colormaps for Environmental Visualization},
author = {Francesca Samsel and Terece Turton and Phillip Wolfram and Roxana Bujack},
editor = {Karsten Rink and Ariane Middel and Dirk Zeckzer and Roxana Bujack},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/IntuitiveColormapsforEnvironmentalVisualization.pdf},
doi = {10.2312/envirvis.20171105},
isbn = {978-3-03868-040-6},
year = {2017},
date = {2017-03-16},
booktitle = {Workshop on Visualisation in Environmental Sciences (EnvirVis)},
publisher = {The Eurographics Association},
abstract = {Visualizations benefit from the use of intuitive colors, enabling an observer to make use of more automatic, subconscious channels. In this paper, we apply the concept of intuitive color to the generation of thematic colormaps for the environmental sciences. In particular, we provide custom sets of colormaps for water, atmosphere, land, and vegetation. These have been integrated into the online tool: ColorMoves: The Environment to enable the environmental scientist to tailor them precisely to the data and tasks in a simple drag-and-drop workflow.},
howpublished = {EnvirVis ; 2017-06-12 - 2017-06-13 ; Barcelona, Spain},
note = {LA-UR-17-22224},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Visualizations benefit from the use of intuitive colors, enabling an observer to make use of more automatic, subconscious channels. In this paper, we apply the concept of intuitive color to the generation of thematic colormaps for the environmental sciences. In particular, we provide custom sets of colormaps for water, atmosphere, land, and vegetation. These have been integrated into the online tool: ColorMoves: The Environment to enable the environmental scientist to tailor them precisely to the data and tasks in a simple drag-and-drop workflow.
4.
Ware, Colin; Turton, Terece; Samsel, Francesca; Bujack, Roxana; Rogers, David
Evaluating the Perceptual Uniformity of Color Sequences for Feature Discrimination Inproceedings
In: Lawonn, Kai; Smit, Noeska; Cunningham, Douglas (Ed.): EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3), The Eurographics Association, 2017, ISBN: 978-3-03868-041-3, (LA-UR-17-24206).
@inproceedings{eurorv3.20171107,
title = {Evaluating the Perceptual Uniformity of Color Sequences for Feature Discrimination},
author = {Colin Ware and Terece Turton and Francesca Samsel and Roxana Bujack and David Rogers},
editor = {Kai Lawonn and Noeska Smit and Douglas Cunningham},
url = {https://diglib.eg.org/handle/10.2312/eurorv320171107},
isbn = {978-3-03868-041-3},
year = {2017},
date = {2017-01-01},
booktitle = {EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3)},
publisher = {The Eurographics Association},
abstract = {Probably the most common method for visualizing univariate data maps is through pseudocoloring and one of the most commonly cited requirements of a good colormap is that it be perceptually uniform. This means that differences between adjacent colors in the sequence be equally distinct. The practical value of uniformity is for features in the data to be equally distinctive no matter where they lie in the colormap, but there are reasons for thinking that uniformity in terms of feature detection may not be achieved by current methods which are based on the use of uniform color spaces. In this paper we provide a new method for directly evaluating colormaps in terms of their capacity for feature resolution. We apply the method in a study using Amazon Mechanical Turk to evaluate seven colormaps. Among other findings the results show that two new double ended sequences have the highest discriminative power and good uniformity. Ways in which the technique can be applied include the design of colormaps for uniformity, and a method for evaluating colormaps through feature discrimination curves for differently sized features.},
note = {LA-UR-17-24206},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Probably the most common method for visualizing univariate data maps is through pseudocoloring and one of the most commonly cited requirements of a good colormap is that it be perceptually uniform. This means that differences between adjacent colors in the sequence be equally distinct. The practical value of uniformity is for features in the data to be equally distinctive no matter where they lie in the colormap, but there are reasons for thinking that uniformity in terms of feature detection may not be achieved by current methods which are based on the use of uniform color spaces. In this paper we provide a new method for directly evaluating colormaps in terms of their capacity for feature resolution. We apply the method in a study using Amazon Mechanical Turk to evaluate seven colormaps. Among other findings the results show that two new double ended sequences have the highest discriminative power and good uniformity. Ways in which the technique can be applied include the design of colormaps for uniformity, and a method for evaluating colormaps through feature discrimination curves for differently sized features.
5.
Bujack, Roxana; Turton, Terece; Samsel, Francesca; Ware, Colin; Rogers, David; Ahrens, James
The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps Inproceedings
In: IEEE Visualization, 2017.
@inproceedings{bujack2017good,
title = {The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps},
author = {Roxana Bujack and Terece Turton and Francesca Samsel and Colin Ware and David Rogers and James Ahrens},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/10/TheGoodtheBadandtheUgly.pdf},
year = {2017},
date = {2017-01-01},
booktitle = {IEEE Visualization},
abstract = {A myriad of design rules for what constitutes a “good” colormap can be found in the literature. Some common rules include order, uniformity, and high discriminative power. However, the meaning of many of these terms is often ambiguous or open to interpretation. At times, different authors may use the same term to describe different concepts or the same rule is described by varying nomenclature. These ambiguities stand in the way of collaborative work, the design of experiments to assess the characteristics of colormaps, and automated colormap generation.
In this paper, we review current and historical guidelines for colormap design. We propose a specified taxonomy and provide unambiguous mathematical definitions for the most common design rules.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
A myriad of design rules for what constitutes a “good” colormap can be found in the literature. Some common rules include order, uniformity, and high discriminative power. However, the meaning of many of these terms is often ambiguous or open to interpretation. At times, different authors may use the same term to describe different concepts or the same rule is described by varying nomenclature. These ambiguities stand in the way of collaborative work, the design of experiments to assess the characteristics of colormaps, and automated colormap generation.
In this paper, we review current and historical guidelines for colormap design. We propose a specified taxonomy and provide unambiguous mathematical definitions for the most common design rules.
In this paper, we review current and historical guidelines for colormap design. We propose a specified taxonomy and provide unambiguous mathematical definitions for the most common design rules.
6.
Samsel, Francesca; Klassen, Sebastian; Petersen, Mark; Turton, Terece; Abram, Greg; Rogers, David; Ahrens, James
Interactive Colormapping: Enabling Multiple Data Ranges, Detailed Views of Ocean Salinity Inproceedings
In: Proceedings of the 34rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, ACM, San Jose, California, 2016, (LA-UR-15-20105).
@inproceedings{Samsel:2016:CIP:2702613.2702975,
title = {Interactive Colormapping: Enabling Multiple Data Ranges, Detailed Views of Ocean Salinity},
author = {Francesca Samsel and Sebastian Klassen and Mark Petersen and Terece Turton and Greg Abram and David Rogers and James Ahrens},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/InteractiveColormapping.pdf},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of the 34rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems},
publisher = {ACM},
address = {San Jose, California},
series = {CHI EA '16},
abstract = {Ocean salinity is a critical component to understanding climate change. Salinity concentrations and temperature drive large ocean currents which in turn drive global weather patterns. Melting ice caps lower salinity at the poles while river deltas bring fresh water into the ocean worldwide. These processes slow ocean currents, changing weather patterns and producing extreme climate events which disproportionally affect those living in poverty. Analysis of salinity presents a unique visualization challenge. Important data are found in narrow data ranges, varying with global location. Changing values of salinity are important in understanding ocean currents, but are difficult to map to colors using traditional tools. Commonly used colormaps may not provide sufficient detail for this data. Current editing tools do not easily enable a scientist to explore the subtleties of salinity. We present a workflow, enabled by an interactive colormap tool that allows a scientist to interactively apply sophisticated colormaps to scalar data. The intuitive and immediate interaction of the scientist with the data is a critical contribution of this work.},
note = {LA-UR-15-20105},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Ocean salinity is a critical component to understanding climate change. Salinity concentrations and temperature drive large ocean currents which in turn drive global weather patterns. Melting ice caps lower salinity at the poles while river deltas bring fresh water into the ocean worldwide. These processes slow ocean currents, changing weather patterns and producing extreme climate events which disproportionally affect those living in poverty. Analysis of salinity presents a unique visualization challenge. Important data are found in narrow data ranges, varying with global location. Changing values of salinity are important in understanding ocean currents, but are difficult to map to colors using traditional tools. Commonly used colormaps may not provide sufficient detail for this data. Current editing tools do not easily enable a scientist to explore the subtleties of salinity. We present a workflow, enabled by an interactive colormap tool that allows a scientist to interactively apply sophisticated colormaps to scalar data. The intuitive and immediate interaction of the scientist with the data is a critical contribution of this work.
7.
Samsel, Francesca
Understanding via Color Presentation
27.10.2015, (IEEE Vis 2015 Color Mapping Panel).
@misc{Samsel1027,
title = {Understanding via Color},
author = {Francesca Samsel},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/UnderstandingViaColor.pptx
http://ieeevis.org/year/2015/info/overview-amp-topics/panels},
year = {2015},
date = {2015-10-27},
abstract = {In this panel, we highlight optimal solutions for designing and building color maps in visualization applications and presentations. Our panelists represent artists, software engineers, cartographers, color scientists, perceptual psychologists, and visualization researchers who have contributed effective solutions to applying color to data visualization. Each panelist will highlight their perspective as well as tips and tricks for color map solutions. Drawing on perspectives from many disciplines, the panel will identify gaps in our understanding about the use of color in visualization and will identify future research directions.},
note = {IEEE Vis 2015 Color Mapping Panel},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
In this panel, we highlight optimal solutions for designing and building color maps in visualization applications and presentations. Our panelists represent artists, software engineers, cartographers, color scientists, perceptual psychologists, and visualization researchers who have contributed effective solutions to applying color to data visualization. Each panelist will highlight their perspective as well as tips and tricks for color map solutions. Drawing on perspectives from many disciplines, the panel will identify gaps in our understanding about the use of color in visualization and will identify future research directions.
8.
Samsel, Francesca; Petersen, Mark; Geld, Terece; Abram, Greg; Wendelberger, Joanne; Ahrens, James
Colormaps That Improve Perception of High-Resolution Ocean Data Inproceedings
In: Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, pp. 703–710, ACM, Seoul, Republic of Korea, 2015, ISBN: 978-1-4503-3146-3, (LA-UR-15-20105).
@inproceedings{Samsel:2015:CIP:2702613.2702975,
title = {Colormaps That Improve Perception of High-Resolution Ocean Data},
author = {Francesca Samsel and Mark Petersen and Terece Geld and Greg Abram and Joanne Wendelberger and James Ahrens},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/ColormapsThatImprovePerceptionOfHigh-ResolutionOceanData.pdf},
doi = {10.1145/2702613.2702975},
isbn = {978-1-4503-3146-3},
year = {2015},
date = {2015-01-01},
booktitle = {Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems},
pages = {703--710},
publisher = {ACM},
address = {Seoul, Republic of Korea},
series = {CHI EA '15},
abstract = {Scientists from the Climate, Ocean and Sea Ice Modeling Team (COSIM) at the Los Alamos National Laboratory (LANL) are interested in gaining a deeper understanding of three primary ocean currents: the Gulf Stream, the Kuroshio Current, and the Agulhas Current & Retroflection. To address these needs, visual artist Francesca Samsel teamed up with experts from the areas of computer science, climate science, statistics, and perceptual science. By engaging an artist specializing in color, we created colormaps that provide the ability to see greater detail in these high-resolution datasets. The new colormaps applied to the POP dataset enabled scientists to see areas of interest unclear using standard colormaps. Improvements in the perceptual range of color allowed scientists to highlight structures within specific ocean currents. Work with the COSIM team members drove development of nested colormaps which provide further detail to the scientists.},
note = {LA-UR-15-20105},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Scientists from the Climate, Ocean and Sea Ice Modeling Team (COSIM) at the Los Alamos National Laboratory (LANL) are interested in gaining a deeper understanding of three primary ocean currents: the Gulf Stream, the Kuroshio Current, and the Agulhas Current & Retroflection. To address these needs, visual artist Francesca Samsel teamed up with experts from the areas of computer science, climate science, statistics, and perceptual science. By engaging an artist specializing in color, we created colormaps that provide the ability to see greater detail in these high-resolution datasets. The new colormaps applied to the POP dataset enabled scientists to see areas of interest unclear using standard colormaps. Improvements in the perceptual range of color allowed scientists to highlight structures within specific ocean currents. Work with the COSIM team members drove development of nested colormaps which provide further detail to the scientists.