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Title: Visual Data Exploration and Analysis - Report on the Visualization Breakout Session of the SCaLeS Workshop

Abstract

Scientific visualization is the transformation of abstract information into images, and it plays an integral role in the scientific process by facilitating insight into observed or simulated phenomena. Visualization as a discipline spans many research areas from computer science, cognitive psychology and even art. Yet the most successful visualization applications are created when close synergistic interactions with domain scientists are part of the algorithmic design and implementation process, leading to visual representations with clear scientific meaning. Visualization is used to explore, to debug, to gain understanding, and as an analysis tool. Visualization is literally everywhere--images are present in this report, on television, on the web, in books and magazines--the common theme is the ability to present information visually that is rapidly assimilated by human observers, and transformed into understanding or insight. As an indispensable part a modern science laboratory, visualization is akin to the biologist's microscope or the electrical engineer's oscilloscope. Whereas the microscope is limited to small specimens or use of optics to focus light, the power of scientific visualization is virtually limitless: visualization provides the means to examine data that can be at galactic or atomic scales, or at any size in between. Unlike the traditional scientific toolsmore » for visual inspection, visualization offers the means to ''see the unseeable.'' Trends in demographics or changes in levels of atmospheric CO{sub 2} as a function of greenhouse gas emissions are familiar examples of such unseeable phenomena. Over time, visualization techniques evolve in response to scientific need. Each scientific discipline has its ''own language,'' verbal and visual, used for communication. The visual language for depicting electrical circuits is much different than the visual language for depicting theoretical molecules or trends in the stock market. There is no ''one visualization too'' that can serve as a panacea for all science disciplines. Instead, visualization researchers work hand in hand with domain scientists as part of the scientific research process to define, create, adapt and refine software that ''speaks the visual language'' of each scientific domain.« less

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Director, Office of Science. Computational and Technology Research (US)
OSTI Identifier:
815467
Report Number(s):
LBNL/PUB-886
R&D Project: K11107; TRN: US200319%%267
DOE Contract Number:
AC03-76SF00098
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 14 Jul 2003
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; COMPUTERS; DESIGN; EXPLORATION; GREENHOUSE GASES; IMPLEMENTATION; MARKET; MICROSCOPES; OPTICS; TRANSFORMATIONS

Citation Formats

Bethel, E. Wes, Frank, Randy, Fulcomer, Sam, Hansen, Chuck, Joy, Ken, Kohl, Jim, and Middleton, Don. Visual Data Exploration and Analysis - Report on the Visualization Breakout Session of the SCaLeS Workshop. United States: N. p., 2003. Web. doi:10.2172/815467.
Bethel, E. Wes, Frank, Randy, Fulcomer, Sam, Hansen, Chuck, Joy, Ken, Kohl, Jim, & Middleton, Don. Visual Data Exploration and Analysis - Report on the Visualization Breakout Session of the SCaLeS Workshop. United States. doi:10.2172/815467.
Bethel, E. Wes, Frank, Randy, Fulcomer, Sam, Hansen, Chuck, Joy, Ken, Kohl, Jim, and Middleton, Don. Mon . "Visual Data Exploration and Analysis - Report on the Visualization Breakout Session of the SCaLeS Workshop". United States. doi:10.2172/815467. https://www.osti.gov/servlets/purl/815467.
@article{osti_815467,
title = {Visual Data Exploration and Analysis - Report on the Visualization Breakout Session of the SCaLeS Workshop},
author = {Bethel, E. Wes and Frank, Randy and Fulcomer, Sam and Hansen, Chuck and Joy, Ken and Kohl, Jim and Middleton, Don},
abstractNote = {Scientific visualization is the transformation of abstract information into images, and it plays an integral role in the scientific process by facilitating insight into observed or simulated phenomena. Visualization as a discipline spans many research areas from computer science, cognitive psychology and even art. Yet the most successful visualization applications are created when close synergistic interactions with domain scientists are part of the algorithmic design and implementation process, leading to visual representations with clear scientific meaning. Visualization is used to explore, to debug, to gain understanding, and as an analysis tool. Visualization is literally everywhere--images are present in this report, on television, on the web, in books and magazines--the common theme is the ability to present information visually that is rapidly assimilated by human observers, and transformed into understanding or insight. As an indispensable part a modern science laboratory, visualization is akin to the biologist's microscope or the electrical engineer's oscilloscope. Whereas the microscope is limited to small specimens or use of optics to focus light, the power of scientific visualization is virtually limitless: visualization provides the means to examine data that can be at galactic or atomic scales, or at any size in between. Unlike the traditional scientific tools for visual inspection, visualization offers the means to ''see the unseeable.'' Trends in demographics or changes in levels of atmospheric CO{sub 2} as a function of greenhouse gas emissions are familiar examples of such unseeable phenomena. Over time, visualization techniques evolve in response to scientific need. Each scientific discipline has its ''own language,'' verbal and visual, used for communication. The visual language for depicting electrical circuits is much different than the visual language for depicting theoretical molecules or trends in the stock market. There is no ''one visualization too'' that can serve as a panacea for all science disciplines. Instead, visualization researchers work hand in hand with domain scientists as part of the scientific research process to define, create, adapt and refine software that ''speaks the visual language'' of each scientific domain.},
doi = {10.2172/815467},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jul 14 00:00:00 EDT 2003},
month = {Mon Jul 14 00:00:00 EDT 2003}
}

Technical Report:

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  • This article describes the role of scientific visualizationin computational and experimental sciences with emphasis upon futureresearch challenges.
  • This document is the report from the Visualization breakoutsession at the SCaLeS (Science Case for Large-scale Simulation) workshopheld in 2003 in Bethesda, MD. The document presents current researchchallenges in visualization of large-scale scientific data.
  • Workshop breakout questions: Is it possible to use load response for ancillary services? Is it desirable? Is it worth the effort? What is required? What are the obstacles? How can DOE help?
  • The focus of this article is on how one group of researchersthe DOE SciDAC Visualization and Analytics Center for EnablingTechnologies (VACET) is tackling the daunting task of enabling knowledgediscovery through visualization and analytics on some of the world slargest and most complex datasets and on some of the world's largestcomputational platforms. As a Center for Enabling Technology, VACET smission is the creation of usable, production-quality visualization andknowledge discovery software infrastructure that runs on large, parallelcomputer systems at DOE's Open Computing facilities and that providessolutions to challenging visual data exploration and knowledge discoveryneeds of modern science, particularly the DOE sciencecommunity.
  • An ongoing challenge in visual exploration and analysis of large, multi-dimensional datasets is how to present useful, concise information to a user for some specific visualization tasks. Typical approaches to this problem have proposed either reduced-resolution versions of data, or projections of data, or both. These approaches still have some limitations such as consuming high computation or suffering from errors. In this work, we explore the use of a statistical metric as the basis for both projections and reduced-resolution versions of data, with a particular focus on preserving one key trait in data, namely variation. We use two different casemore » studies to explore this idea, one that uses a synthetic dataset, and another that uses a large ensemble collection produced by an atmospheric modeling code to study long-term changes in global precipitation. The primary findings of our work are that in terms of preserving the variation signal inherent in data, that using a statistical measure more faithfully preserves this key characteristic across both multi-dimensional projections and multi-resolution representations than a methodology based upon averaging.« less