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41.
Bujack, Roxana; Rogers, David; Ahrens, James
Reducing Occlusion in Cinema Databases through Feature-Centric Visualizations Proceedings Article
In: Leipzig Symposium on Visualization In Applications (LEVIA), 2018.
@inproceedings{bujack2018reducing,
title = {Reducing Occlusion in Cinema Databases through Feature-Centric Visualizations},
author = {Roxana Bujack and David Rogers and James Ahrens},
url = {https://datascience.dsscale.org/wp-content/uploads/2019/01/ReducingOcclusioninCinemaDatabasesthroughFeature-CentricVisualizations.pdf},
year = {2018},
date = {2018-01-01},
booktitle = {Leipzig Symposium on Visualization In Applications (LEVIA)},
abstract = {In modern supercomputer architectures, the I/O capabilities do not keep up with the computational speed. Image-based techniques are one very promising approach to a scalable output format for visual analysis, in which a reduced output that corresponds to the visible state of the simulation is rendered in-situ and stored to disk. These techniques can support interactive exploration of the data through image compositing and other methods, but automatic methods of highlighting data and reducing clutter can make these methods more effective. In this paper, we suggest a method of assisted exploration through the combination of feature-centric analysis with image space techniques and show how the reduction of the data to features of interest reduces occlusion in the output for a set of example applications.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In modern supercomputer architectures, the I/O capabilities do not keep up with the computational speed. Image-based techniques are one very promising approach to a scalable output format for visual analysis, in which a reduced output that corresponds to the visible state of the simulation is rendered in-situ and stored to disk. These techniques can support interactive exploration of the data through image compositing and other methods, but automatic methods of highlighting data and reducing clutter can make these methods more effective. In this paper, we suggest a method of assisted exploration through the combination of feature-centric analysis with image space techniques and show how the reduction of the data to features of interest reduces occlusion in the output for a set of example applications.
42.
Banesh, Divya; Wendelberger, Joanne; Petersen, Mark; Ahrens, James; Hamann, Bernd
Change Point Detection for Ocean Eddy Analysis Proceedings Article
In: Proceedings of the Workshop on Visualisation in Environmental Sciences, pp. 27–33, Eurographics Association, Brno, Czech Republic, 2018, ISBN: 978-3-03868-063-5.
@inproceedings{Banesh:2018:CPD:3310180.3310186,
title = {Change Point Detection for Ocean Eddy Analysis},
author = {Divya Banesh and Joanne Wendelberger and Mark Petersen and James Ahrens and Bernd Hamann},
url = {http://dl.acm.org/citation.cfm?id=3310180.3310186
https://dsscale.org/wp-content/uploads/2019/10/dbanesh_ChangeDetection_optimized.pdf},
isbn = {978-3-03868-063-5},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the Workshop on Visualisation in Environmental Sciences},
pages = {27--33},
publisher = {Eurographics Association},
address = {Brno, Czech Republic},
series = {EnvirVis '18},
abstract = {The detection and analysis of mesoscale ocean eddies is a complex task, made more difficult when simulated or observational ocean data are massive. We present the statistical approach of change point detection as a means to help scientists efficiently extract relevant scientific information. We demonstrate the value of change point detection for the characterization of eddy behavior in simulated ocean data. Our results show that change point detection helps with the identification of significant parameter values used in an algorithm or determination of time points that correspond to eddy activity of interest.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The detection and analysis of mesoscale ocean eddies is a complex task, made more difficult when simulated or observational ocean data are massive. We present the statistical approach of change point detection as a means to help scientists efficiently extract relevant scientific information. We demonstrate the value of change point detection for the characterization of eddy behavior in simulated ocean data. Our results show that change point detection helps with the identification of significant parameter values used in an algorithm or determination of time points that correspond to eddy activity of interest.
43.
Yang, Bo; Kostkova, Jitka; Flusser, Jan; Suk, Tomas; Bujack, Roxana
Rotation Invariants of Vector Fields from Orthogonal Moments Journal Article
In: Pattern Recognition, no. Supplement C, pp. 110 - 121, 2017, ISSN: 0031-3203, (LA-UR-17-26797, Under a Creative Comms license: http://creativecommons.org/licenses/by-nc-nd/4.0/).
@article{yang2017rotation,
title = {Rotation Invariants of Vector Fields from Orthogonal Moments},
author = {Bo Yang and Jitka Kostkova and Jan Flusser and Tomas Suk and Roxana Bujack},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/09/LA-UR-17-26797.pdf},
doi = {10.1016/j.patcog.2017.09.004},
issn = {0031-3203},
year = {2017},
date = {2017-09-11},
booktitle = {Pattern Recognition},
journal = {Pattern Recognition},
number = {Supplement C},
pages = {110 - 121},
abstract = {Abstract Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. To analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. In this paper, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but also on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian--Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.},
note = {LA-UR-17-26797, Under a Creative Comms license: http://creativecommons.org/licenses/by-nc-nd/4.0/},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. To analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. In this paper, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but also on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian--Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.
44.
Patchett, John; Nouanesengsy, Boonthanome; Ahrens, James; Lang, Michael; Rogers, David; Green, Jennifer; Samsel, Francesca; Cone, Giovanni; Hagen, Hans
Delivery of In Situ Capability to End Users Proceedings Article
In: 2017, (USDOE National Nuclear Security Administration (NNSA), LA-UR-17-26655).
@inproceedings{info:lanl-repo/lareport/LA-UR-17-26655,
title = {Delivery of In Situ Capability to End Users},
author = {John Patchett and Boonthanome Nouanesengsy and James Ahrens and Michael Lang and David Rogers and Jennifer Green and Francesca Samsel and Giovanni Cone and Hans Hagen},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/LA-UR-17-26655.pdf},
year = {2017},
date = {2017-08-01},
abstract = {Delivery of new technologies to deeply rooted end user workflows can be difficult. We describe a delivery process of a generalized in situ data analysis and visualization capability to both end users and simulation code developers. The process was driven and funded by management which helped ensure success. End users were chosen to exemplify the capability. Delivery is defined to include full integration into the simulation. This includes the simulation’s regular build and testing systems, in addition to institutional support in the supercomputing environments. This paper describes a robust and successful delivery of the in situ capability to our end users.},
note = {USDOE National Nuclear Security Administration (NNSA), LA-UR-17-26655},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Delivery of new technologies to deeply rooted end user workflows can be difficult. We describe a delivery process of a generalized in situ data analysis and visualization capability to both end users and simulation code developers. The process was driven and funded by management which helped ensure success. End users were chosen to exemplify the capability. Delivery is defined to include full integration into the simulation. This includes the simulation’s regular build and testing systems, in addition to institutional support in the supercomputing environments. This paper describes a robust and successful delivery of the in situ capability to our end users.
45.
Berres, Anne; Adhinarayanan, Vignesh; Turton, Terece; Feng, Wu; Rogers, David
A Pipeline for Large Data Processing Using Regular Sampling for Unstructured Grids Proceedings Article
In: 2017, (LA-UR-17-23903).
@inproceedings{info:lanl-repo/lareport/LA-UR-17-23903,
title = {A Pipeline for Large Data Processing Using Regular Sampling for Unstructured Grids},
author = {Anne Berres and Vignesh Adhinarayanan and Terece Turton and Wu Feng and David Rogers},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/LA-UR-17-23903.pdf},
year = {2017},
date = {2017-05-12},
abstract = {Large simulation data requires a lot of time and computational resources to compute, store, analyze, visualize, and run user studies. Today, the largest cost of a supercomputer is not hardware but maintenance, in particular energy consumption. Our goal is to balance energy consumption and cognitive value of visualizations of resulting data. This requires us to go through the entire processing pipeline, from simulation to user studies. To reduce the amount of resources, data can be sampled or compressed. While this adds more computation time, the computational overhead is negligible compared to the simulation time. We built a processing pipeline at the example of regular sampling. The reasons for this choice are two-fold: using a simple example reduces unnecessary complexity as we know what to expect from the results. Furthermore, it provides a good baseline for future, more elaborate sampling methods. We measured time and energy for each test we did, and we conducted user studies in Amazon Mechanical Turk (AMT) for a range of different results we produced through sampling.
},
note = {LA-UR-17-23903},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Large simulation data requires a lot of time and computational resources to compute, store, analyze, visualize, and run user studies. Today, the largest cost of a supercomputer is not hardware but maintenance, in particular energy consumption. Our goal is to balance energy consumption and cognitive value of visualizations of resulting data. This requires us to go through the entire processing pipeline, from simulation to user studies. To reduce the amount of resources, data can be sampled or compressed. While this adds more computation time, the computational overhead is negligible compared to the simulation time. We built a processing pipeline at the example of regular sampling. The reasons for this choice are two-fold: using a simple example reduces unnecessary complexity as we know what to expect from the results. Furthermore, it provides a good baseline for future, more elaborate sampling methods. We measured time and energy for each test we did, and we conducted user studies in Amazon Mechanical Turk (AMT) for a range of different results we produced through sampling.
46.
Samsel, Francesca; Patchett, John; Rogers, David; Tsai, Karen
Employing Color Theory to Visualize Volume-rendered Multivariate Ensembles of Asteroid Impact Simulations Proceedings Article
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.
47.
Patchett, John; Gisler, Galen
Deep Water Impact Ensemble Data Set Technical Report
2017, (LA-UR-17-21595).
@techreport{Patchett2017,
title = {Deep Water Impact Ensemble Data Set},
author = {John Patchett and Galen Gisler},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/DeepWaterImpactEnsembleDataSet_Revision1.pdf},
year = {2017},
date = {2017-05-02},
abstract = {This ensemble data set represents the study of asteroid impacts in deep ocean water. NASA’s Planetary Defense Coordination Office [1] is keenly interested to know the lower size limit of dangerous asteroids, so as to focus resources on finding all larger objects that potentially threaten the earth. Since most of the planet’s surface is water, that is where asteroids will most likely impact. This observation has generated a serious debate over the last two decades on just how dangerous impact-induced waves or tsunamis are to populated shorelines.},
note = {LA-UR-17-21595},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
This ensemble data set represents the study of asteroid impacts in deep ocean water. NASA’s Planetary Defense Coordination Office [1] is keenly interested to know the lower size limit of dangerous asteroids, so as to focus resources on finding all larger objects that potentially threaten the earth. Since most of the planet’s surface is water, that is where asteroids will most likely impact. This observation has generated a serious debate over the last two decades on just how dangerous impact-induced waves or tsunamis are to populated shorelines.
48.
Adhinarayanan, Vignesh; Feng, Wu-chun; Rogers, David; Ahrens, James; Pakin, Scott
Characterizing and Modeling Power and Energy for Extreme-Scale In-Situ Visualization Proceedings Article
In: 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 978-987, 2017, (LA-UR-16-22435).
@inproceedings{7967188,
title = {Characterizing and Modeling Power and Energy for Extreme-Scale In-Situ Visualization},
author = {Vignesh Adhinarayanan and Wu-chun Feng and David Rogers and James Ahrens and Scott Pakin},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/CharacterizingandModelingPowerandEnergyforExtreme-ScaleIn-SituVisualization.pdf},
doi = {10.1109/IPDPS.2017.113},
year = {2017},
date = {2017-05-01},
booktitle = {2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS)},
pages = {978-987},
abstract = {Plans for exascale computing have identified power and energy as looming problems for simulations running at that scale. In particular, writing to disk all the data generated by these simulations is becoming prohibitively expensive due to the energy consumption of the supercomputer while it idles waiting for data to be written to permanent storage. In addition, the power cost of data movement is also steadily increasing. A solution to this problem is to write only a small fraction of the data generated while still maintaining the cognitive fidelity of the visualization. With domain scientists increasingly amenable towards adopting an in-situ framework that can identify and extract valuable data from extremely large simulation results and write them to permanent storage as compact images, a large-scale simulation will commit to disk a reduced dataset of data extracts that will be much smaller than the raw results, resulting in a savings in both power and energy. The goal of this paper is two-fold: (i) to understand the role of in-situ techniques in combating power and energy issues of extreme-scale visualization and (ii) to create a model for performance, power, energy, and storage to facilitate what-if analysis. Our experiments on a specially instrumented, dedicated 150-node cluster show that while it is difficult to achieve power savings in practice using in-situ techniques, applications can achieve significant energy savings due to shorter write times for in-situ visualization. We present a characterization of power and energy for in-situ visualization; an application-aware, architecture-specific methodology for modeling and analysis of such in-situ workflows; and results that uncover indirect power savings in visualization workflows for high-performance computing (HPC).},
note = {LA-UR-16-22435},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Plans for exascale computing have identified power and energy as looming problems for simulations running at that scale. In particular, writing to disk all the data generated by these simulations is becoming prohibitively expensive due to the energy consumption of the supercomputer while it idles waiting for data to be written to permanent storage. In addition, the power cost of data movement is also steadily increasing. A solution to this problem is to write only a small fraction of the data generated while still maintaining the cognitive fidelity of the visualization. With domain scientists increasingly amenable towards adopting an in-situ framework that can identify and extract valuable data from extremely large simulation results and write them to permanent storage as compact images, a large-scale simulation will commit to disk a reduced dataset of data extracts that will be much smaller than the raw results, resulting in a savings in both power and energy. The goal of this paper is two-fold: (i) to understand the role of in-situ techniques in combating power and energy issues of extreme-scale visualization and (ii) to create a model for performance, power, energy, and storage to facilitate what-if analysis. Our experiments on a specially instrumented, dedicated 150-node cluster show that while it is difficult to achieve power savings in practice using in-situ techniques, applications can achieve significant energy savings due to shorter write times for in-situ visualization. We present a characterization of power and energy for in-situ visualization; an application-aware, architecture-specific methodology for modeling and analysis of such in-situ workflows; and results that uncover indirect power savings in visualization workflows for high-performance computing (HPC).
49.
Dutta, Soumya; Woodring, Jon; Shen, Han-Wei; Chen, Jen-Ping; Ahrens, James
Homogeneity guided probabilistic data summaries for analysis and visualization of large-scale data sets Proceedings Article
In: 2017 IEEE Pacific Visualization Symposium (PacificVis), pp. 111-120, 2017, ISSN: 2165-8773, (LA-UR-18-27370).
@inproceedings{8031585,
title = {Homogeneity guided probabilistic data summaries for analysis and visualization of large-scale data sets},
author = {Soumya Dutta and Jon Woodring and Han-Wei Shen and Jen-Ping Chen and James Ahrens},
url = {https://datascience.dsscale.org/wp-content/uploads/2018/08/la-ur_18-27370.pdf},
doi = {10.1109/PACIFICVIS.2017.8031585},
issn = {2165-8773},
year = {2017},
date = {2017-04-01},
booktitle = {2017 IEEE Pacific Visualization Symposium (PacificVis)},
pages = {111-120},
abstract = {High-resolution simulation data sets provide plethora of information, which needs to be explored by application scientists to gain enhanced understanding about various phenomena. Visual-analytics techniques using raw data sets are often expensive due to the data sets' extreme sizes. But, interactive analysis and visualization is crucial for big data analytics, because scientists can then focus on the important data and make critical decisions quickly. To assist efficient exploration and visualization, we propose a new region-based statistical data summarization scheme. Our method is superior in quality, as compared to the existing statistical summarization techniques, with a more compact representation, reducing the overall storage cost. The quantitative and visual efficacy of our proposed method is demonstrated using several data sets along with an in situ application study for an extreme-scale flow simulation.},
note = {LA-UR-18-27370},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
High-resolution simulation data sets provide plethora of information, which needs to be explored by application scientists to gain enhanced understanding about various phenomena. Visual-analytics techniques using raw data sets are often expensive due to the data sets' extreme sizes. But, interactive analysis and visualization is crucial for big data analytics, because scientists can then focus on the important data and make critical decisions quickly. To assist efficient exploration and visualization, we propose a new region-based statistical data summarization scheme. Our method is superior in quality, as compared to the existing statistical summarization techniques, with a more compact representation, reducing the overall storage cost. The quantitative and visual efficacy of our proposed method is demonstrated using several data sets along with an in situ application study for an extreme-scale flow simulation.
50.
Banesh, Divya; Schoonover, Joseph; Ahrens, James; Hamann, Bernd
Extracting, Visualizing and Tracking Mesoscale Ocean Eddies in Two-dimensional Image Sequences Using Contours and Moments Proceedings Article
In: 2017, (Workshop on Visualisation in Environmental Sciences (EnvirVis), LA-UR-17-21623).
@inproceedings{Authors2017,
title = {Extracting, Visualizing and Tracking Mesoscale Ocean Eddies in Two-dimensional Image Sequences Using Contours and Moments},
author = {Divya Banesh and Joseph Schoonover and James Ahrens and Bernd Hamann},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/ExtractingVisualizingandTrackingMesoscaleOceanEddiesinTwo-dimensionalImageSequencesUsingContoursandMoments.pdf},
year = {2017},
date = {2017-03-31},
abstract = {We introduce a system for the extraction and tracking of mesoscale eddies captured in massive global ocean simulations. The major strength and contribution of our system is its design, which is based on two-dimensional image data processing. The Cinema database [CD] makes possible the generation and storage of two-dimensional image data taken in-situ, i.e., the creation of images via a virtual camera generating images during the ongoing simulation. The problem of eddy extraction and tracking is simplified by our approach to the problem of finding, matching and tracking eddies in two-dimensional images, thus eliminating the task of processing the original massive three-dimensional data set. Our system can be used on a simple desktop computer and provides an intuitive interface allowing a scientist to perform an eddy analysis for global ocean data in real-time. We demonstrate the effectiveness of our implementation for a specific simulated data set.},
note = {Workshop on Visualisation in Environmental Sciences (EnvirVis), LA-UR-17-21623},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We introduce a system for the extraction and tracking of mesoscale eddies captured in massive global ocean simulations. The major strength and contribution of our system is its design, which is based on two-dimensional image data processing. The Cinema database [CD] makes possible the generation and storage of two-dimensional image data taken in-situ, i.e., the creation of images via a virtual camera generating images during the ongoing simulation. The problem of eddy extraction and tracking is simplified by our approach to the problem of finding, matching and tracking eddies in two-dimensional images, thus eliminating the task of processing the original massive three-dimensional data set. Our system can be used on a simple desktop computer and provides an intuitive interface allowing a scientist to perform an eddy analysis for global ocean data in real-time. We demonstrate the effectiveness of our implementation for a specific simulated data set.
51.
Samsel, Francesca; Turton, Terece; Wolfram, Phillip; Bujack, Roxana
Intuitive Colormaps for Environmental Visualization Proceedings Article
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.
52.
Patchett, John; Nouanesengsy, Boonthanome; Gisler, Galen; Ahrens, James; Hagen, Hans
In Situ and Post Processing Workflows for Asteroid Ablation Studies Proceedings Article
In: Kozlikova, Barbora; Schreck, Tobias; Wischgoll, Thomas (Ed.): EuroVis 2017 - Short Papers, The Eurographics Association, 2017, ISBN: 978-3-03868-043-7, (LA-UR-17-22699).
@inproceedings{eurovisshort.20171134,
title = {In Situ and Post Processing Workflows for Asteroid Ablation Studies},
author = {John Patchett and Boonthanome Nouanesengsy and Galen Gisler and James Ahrens and Hans Hagen},
editor = {Barbora Kozlikova and Tobias Schreck and Thomas Wischgoll},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/LA-UR-17-22699.pdf},
doi = {10.2312/eurovisshort.20171134},
isbn = {978-3-03868-043-7},
year = {2017},
date = {2017-01-01},
booktitle = {EuroVis 2017 - Short Papers},
publisher = {The Eurographics Association},
abstract = {Simulation scientists need to make decisions about what and how much output to produce. They must balance their ability to efficiently ingest the analysis with their ability to get more analysis. We study this balance as a tradeoff between flexibility of saved data products and accessibility of saved data products. One end of the spectrum is raw data that comes directly from the simulation, making it highly flexible, but inaccessible due to its size and format. The other end of the spectrum is highly processed and comparatively small data, often in the form of imagery or single scalar values. This data is typically highly accessible, needing no special equipment or software, but lacks flexibility for deeper analysis than what is presented. We lay out a user driven model that considers the scientists' output needs in regards to flexibility and accessibility. This model allows us to analyze a real-world example of a large simulation lasting months of wall clock time on thousands of processing cores. Though the ensemble of simulation's original intent was to study asteroid generated tsunamis, the simulations are now being used beyond that scope to study the asteroid ablation as it moves through the atmosphere. With increasingly large supercomputers, designing workflows that support an intentional and understood balance of flexibility and accessibility is necessary. In this paper, we present a new strategy developed from a user driven perspective to support the collaborative capability between simulation developers, designers, users and analysts to effectively support science by wisely using both computer and human time.},
note = {LA-UR-17-22699},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Simulation scientists need to make decisions about what and how much output to produce. They must balance their ability to efficiently ingest the analysis with their ability to get more analysis. We study this balance as a tradeoff between flexibility of saved data products and accessibility of saved data products. One end of the spectrum is raw data that comes directly from the simulation, making it highly flexible, but inaccessible due to its size and format. The other end of the spectrum is highly processed and comparatively small data, often in the form of imagery or single scalar values. This data is typically highly accessible, needing no special equipment or software, but lacks flexibility for deeper analysis than what is presented. We lay out a user driven model that considers the scientists' output needs in regards to flexibility and accessibility. This model allows us to analyze a real-world example of a large simulation lasting months of wall clock time on thousands of processing cores. Though the ensemble of simulation's original intent was to study asteroid generated tsunamis, the simulations are now being used beyond that scope to study the asteroid ablation as it moves through the atmosphere. With increasingly large supercomputers, designing workflows that support an intentional and understood balance of flexibility and accessibility is necessary. In this paper, we present a new strategy developed from a user driven perspective to support the collaborative capability between simulation developers, designers, users and analysts to effectively support science by wisely using both computer and human time.
53.
Hamilton, Stephen; Burns, Randal; Meneveau, Charles; Johnson, Perry; Lindstrom, Peter; Patchett, John; Szalay, Alexander S.
Extreme Event Analysis in Next Generation Simulation Architectures Proceedings Article
In: Kunkel, Julian M.; Yokota, Rio; Balaji, Pavan; Keyes, David (Ed.): High Performance Computing: 32nd International Conference, ISC High Performance 2017, Frankfurt, Germany, June 18--22, 2017, Proceedings, pp. 277–293, Springer, Cham Springer International Publishing}, 2017, ISBN: 978-3-319-58667-0.
@inproceedings{hamilton2017extreme,
title = {Extreme Event Analysis in Next Generation Simulation Architectures},
author = {Stephen Hamilton and Randal Burns and Charles Meneveau and Perry Johnson and Peter Lindstrom and John Patchett and Alexander S. Szalay},
editor = {Julian M. Kunkel and Rio Yokota and Pavan Balaji and David Keyes},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/ExtremeEventAnalysisinNextGenerationSimulationArchitectures.pdf},
doi = {10.1007/978-3-319-58667-0_15},
isbn = {978-3-319-58667-0},
year = {2017},
date = {2017-01-01},
booktitle = {High Performance Computing: 32nd International Conference, ISC High Performance 2017, Frankfurt, Germany, June 18--22, 2017, Proceedings},
pages = {277--293},
publisher = {Springer International Publishing}},
organization = {Springer, Cham},
abstract = {Numerical simulations present challenges because they generate petabyte-scale data that must be extracted and reduced during the simulation. We demonstrate a seamless integration of feature extraction for a simulation of turbulent fluid dynamics. The simulation produces on the order of 6 terabytes per timestep. In order to analyze and store this data, we extract velocity data from a dilated volume of the strong vortical regions and also store a lossy compressed representation of the data. Both reduce data by one or more orders of magnitude. We extract data from user checkpoints in transit while they reside on temporary burst buffer SSD stores. In this way, analysis and compression algorithms are designed to meet specific time constraints so they do not interfere with simulation computations. Our results demonstrate that we can perform feature extraction on a world-class direct numerical simulation of turbulence while it is running and gather meaningful scientific data for archival and post analysis.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Numerical simulations present challenges because they generate petabyte-scale data that must be extracted and reduced during the simulation. We demonstrate a seamless integration of feature extraction for a simulation of turbulent fluid dynamics. The simulation produces on the order of 6 terabytes per timestep. In order to analyze and store this data, we extract velocity data from a dilated volume of the strong vortical regions and also store a lossy compressed representation of the data. Both reduce data by one or more orders of magnitude. We extract data from user checkpoints in transit while they reside on temporary burst buffer SSD stores. In this way, analysis and compression algorithms are designed to meet specific time constraints so they do not interfere with simulation computations. Our results demonstrate that we can perform feature extraction on a world-class direct numerical simulation of turbulence while it is running and gather meaningful scientific data for archival and post analysis.
54.
Berres, Anne; Turton, Terece; Rogers, David; Ahrens, James; Petersen, Mark
Video Compression for Ocean Simulation Image Databases Proceedings Article
In: Rink, Karsten; Middel, Ariane; Zeckzer, Dirk; Bujack, Roxana (Ed.): Workshop on Visualization in Environmental Sciences (EnvirVis), The Eurographics Association, 2017, ISBN: 978-3-03868-040-6, (LA-UR-17-21590).
@inproceedings{info:lanl-repo/lareport/LA-UR-17-21590,
title = {Video Compression for Ocean Simulation Image Databases},
author = {Anne Berres and Terece Turton and David Rogers and James Ahrens and Mark Petersen},
editor = {Karsten Rink and Ariane Middel and Dirk Zeckzer and Roxana Bujack},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/VideoCompressionforOceanSimulationImageDatabases.pdf},
doi = {10.2312/envirvis.20171104},
isbn = {978-3-03868-040-6},
year = {2017},
date = {2017-01-01},
booktitle = {Workshop on Visualization in Environmental Sciences (EnvirVis)},
publisher = {The Eurographics Association},
abstract = {Climate research requires monitoring a large range of spatial and temporal scales to understand the climate system and potential future impacts. Climate simulations are now run with very high resolution (1–10 km gridcells) ocean, sea ice, and atmosphere components, and can easily produce petabytes of output. This overloads storage systems and hinders visualization and analysis. Image databases can decrease storage sizes from petabytes of simulation output down to several hundred gigabytes of images.
In this paper, we introduce video compression as a method to further decrease database sizes by 2-4 orders of magnitude. We compare compression and access speeds, compressed sizes, and compression quality over a range of settings. Quality is assessed through image quality metrics and expert feedback. Overall, we were able to show that video compression techniques provide an efficient means of storing image databases at a shareable size, while preserving image quality. This enables the wise use of available disk space, so scientists can more easily study the physical features of interest.},
howpublished = {Visualization in Environmental Sciences 2017 ; 2017-06-12 - 2017-06-13 ; Barcelona, Spain},
note = {LA-UR-17-21590},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Climate research requires monitoring a large range of spatial and temporal scales to understand the climate system and potential future impacts. Climate simulations are now run with very high resolution (1–10 km gridcells) ocean, sea ice, and atmosphere components, and can easily produce petabytes of output. This overloads storage systems and hinders visualization and analysis. Image databases can decrease storage sizes from petabytes of simulation output down to several hundred gigabytes of images.
In this paper, we introduce video compression as a method to further decrease database sizes by 2-4 orders of magnitude. We compare compression and access speeds, compressed sizes, and compression quality over a range of settings. Quality is assessed through image quality metrics and expert feedback. Overall, we were able to show that video compression techniques provide an efficient means of storing image databases at a shareable size, while preserving image quality. This enables the wise use of available disk space, so scientists can more easily study the physical features of interest.
In this paper, we introduce video compression as a method to further decrease database sizes by 2-4 orders of magnitude. We compare compression and access speeds, compressed sizes, and compression quality over a range of settings. Quality is assessed through image quality metrics and expert feedback. Overall, we were able to show that video compression techniques provide an efficient means of storing image databases at a shareable size, while preserving image quality. This enables the wise use of available disk space, so scientists can more easily study the physical features of interest.
55.
Ware, Colin; Turton, Terece; Samsel, Francesca; Bujack, Roxana; Rogers, David
Evaluating the Perceptual Uniformity of Color Sequences for Feature Discrimination Proceedings Article
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.
56.
Turton, Terece; Ware, Colin; Samsel, Francesca; Rogers, David
A Crowdsourced Approach to Colormap Assessment Proceedings Article
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.
@inproceedings{Turton2017crowdsourced,
title = {A Crowdsourced Approach to Colormap Assessment},
author = {Terece Turton and Colin Ware and Francesca Samsel and David Rogers},
editor = {Kai Lawonn and Noeska Smit and Douglas Cunningham},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/ACrowdsourcedApproachtoColormapAssessment.pdf},
doi = {10.2312/eurorv3.20171106},
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 = {Despite continual research and discussion on the perceptual effects of color in scientific visualization, psychophysical testing is often limited. In-person lab studies can be expensive and time-consuming while results can be difficult to extrapolate from meticulously controlled laboratory conditions to the real world of the visualization user. We draw on lessons learned from the use of crowdsourced participant pools in the behavioral sciences and information visualization to apply a crowdsourced approach to a classic psychophysical experiment assessing the ability of a colormap to impart metric information. We use an online presentation analogous to the color key task from Ware’s 1988 paper, Color Sequences for Univariate Maps, testing colormaps similar to those in the original paper along with contemporary colormap standards and new alternatives in the scientific visualization domain. We explore the issue of potential contamination from color deficient participants and establish that perceptual color research can appropriately leverage a crowdsourced participant pool without significant CVD concerns. The updated version of the Ware color key task also provides a method to assess and compare colormaps.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Despite continual research and discussion on the perceptual effects of color in scientific visualization, psychophysical testing is often limited. In-person lab studies can be expensive and time-consuming while results can be difficult to extrapolate from meticulously controlled laboratory conditions to the real world of the visualization user. We draw on lessons learned from the use of crowdsourced participant pools in the behavioral sciences and information visualization to apply a crowdsourced approach to a classic psychophysical experiment assessing the ability of a colormap to impart metric information. We use an online presentation analogous to the color key task from Ware’s 1988 paper, Color Sequences for Univariate Maps, testing colormaps similar to those in the original paper along with contemporary colormap standards and new alternatives in the scientific visualization domain. We explore the issue of potential contamination from color deficient participants and establish that perceptual color research can appropriately leverage a crowdsourced participant pool without significant CVD concerns. The updated version of the Ware color key task also provides a method to assess and compare colormaps.
57.
Turton, Terece; Berres, Anne; Rogers, David; Ahrens, James
ETK: An Evaluation Toolkit for Visualization User Studies Proceedings Article
In: Kozlikova, Barbora; Schreck, Tobias; Wischgoll, Thomas (Ed.): EuroVis 2017 – Short Papers, The Eurographics Association, 2017, ISBN: 978-3-03868-043-7.
@inproceedings{Turton2017etk,
title = {ETK: An Evaluation Toolkit for Visualization User Studies},
author = {Terece Turton and Anne Berres and David Rogers and James Ahrens},
editor = {Barbora Kozlikova and Tobias Schreck and Thomas Wischgoll},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/ETKAnEvaluationToolkitforVisualizationUserStudies.pdf},
doi = {10.2312/eurovisshort.20171131},
isbn = {978-3-03868-043-7},
year = {2017},
date = {2017-01-01},
booktitle = {EuroVis 2017 – Short Papers},
publisher = {The Eurographics Association},
abstract = {This paper describes the design and features of the Evaluation Toolkit (ETK), a set of JavaScript/HTML/CSS modules leveraging the Qualtrics JavaScript API that can be used to automate image-based perceptual user evaluation studies. Automating the presentation of the images can greatly decrease the time to build and implement an evaluation study while minimizing the length and complexity of a study built within Qualtrics, along with decreasing the possibility of error in image presentation. The ETK modules each focus on automating a specific psychophysical or experimental approach. Because each module is an extension or plug-in to a Qualtrics question, the resultant study can be easily used in a laboratory setting or in a crowdsourced approach. We present the open source repository of ETK with the six modules that currently make up the toolkit and invite the community to explore, utilize, and contribute to the toolkit.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper describes the design and features of the Evaluation Toolkit (ETK), a set of JavaScript/HTML/CSS modules leveraging the Qualtrics JavaScript API that can be used to automate image-based perceptual user evaluation studies. Automating the presentation of the images can greatly decrease the time to build and implement an evaluation study while minimizing the length and complexity of a study built within Qualtrics, along with decreasing the possibility of error in image presentation. The ETK modules each focus on automating a specific psychophysical or experimental approach. Because each module is an extension or plug-in to a Qualtrics question, the resultant study can be easily used in a laboratory setting or in a crowdsourced approach. We present the open source repository of ETK with the six modules that currently make up the toolkit and invite the community to explore, utilize, and contribute to the toolkit.
58.
Bujack, Roxana; Flusser, Jan
Flexible Moment Invariant Bases for 2D Scalar and Vector Fields Proceedings Article
In: Proceedings of International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG), 2017, (LA-UR-17-20144).
@inproceedings{bujack2017flexible,
title = {Flexible Moment Invariant Bases for 2D Scalar and Vector Fields},
author = {Roxana Bujack and Jan Flusser},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/09/LA-UR-17-20144.pdf},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings of International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG)},
abstract = {Complex moments have been successfully applied to pattern detection tasks in two-dimensional real, complex, and vector valued functions.
In this paper, we review the different bases of rotational moment invariants based on the generator approach with complex monomials. We analyze their properties with respect to independence, completeness, and existence and present superior bases that are optimal with respect to all three criteria for both scalar and vector fields.},
note = {LA-UR-17-20144},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Complex moments have been successfully applied to pattern detection tasks in two-dimensional real, complex, and vector valued functions.
In this paper, we review the different bases of rotational moment invariants based on the generator approach with complex monomials. We analyze their properties with respect to independence, completeness, and existence and present superior bases that are optimal with respect to all three criteria for both scalar and vector fields.
In this paper, we review the different bases of rotational moment invariants based on the generator approach with complex monomials. We analyze their properties with respect to independence, completeness, and existence and present superior bases that are optimal with respect to all three criteria for both scalar and vector fields.
59.
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 Proceedings Article
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.
60.
Berres, Anne; Turton, Terece; Petersen, Mark; Rogers, David; Ahrens, James
Video Compression for Ocean Simulation Image Databases Proceedings Article
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.
@inproceedings{Berres2017-VideoCompression,
title = {Video Compression for Ocean Simulation Image Databases},
author = {Anne Berres and Terece Turton and Mark Petersen and David Rogers and James Ahrens},
editor = {Karsten Rink and Ariane Middel and Dirk Zeckzer and Roxana Bujack},
url = {http://ecxproject.org/wp-content/uploads/sites/18/2018/04/envirvis17-video-compression.pdf},
doi = {10.2312/envirvis.20171104},
isbn = {978-3-03868-040-6},
year = {2017},
date = {2017-01-01},
booktitle = {Workshop on Visualisation in Environmental Sciences (EnvirVis)},
publisher = {The Eurographics Association},
abstract = {Climate research requires monitoring a large range of spatial and temporal scales to understand the climate system and potential future impacts. Climate simulations are now run with very high resolution (1--10 km gridcells) ocean, sea ice, and atmosphere components, and can easily produce petabytes of output. This overloads storage systems and hinders visualization and analysis. Image databases can decrease storage sizes from petabytes of simulation output down to several hundred gigabytes of images.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Climate research requires monitoring a large range of spatial and temporal scales to understand the climate system and potential future impacts. Climate simulations are now run with very high resolution (1--10 km gridcells) ocean, sea ice, and atmosphere components, and can easily produce petabytes of output. This overloads storage systems and hinders visualization and analysis. Image databases can decrease storage sizes from petabytes of simulation output down to several hundred gigabytes of images.