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Grand Challenges Robert Moorhead Mississippi State University Mississippi State, MS 39762 rjm@erc.msstate.edu
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May 2, 20052 A Summary from Café Application Grand Challenges Digital Human (Physiome Project) Situational Awareness/Management Mapping the Universe Health of humanity and the universe Intelligent Sensor Fusion Change Detection (slow growth, trends, automatic detection) Business Analytics Intelligence Information and Security My Name, title and AffiliationMy Name, Title, and Affiliation
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May 2, 20053 A Summary from Café Application Grand Challenges “Photoshop” for Scientists (explanatory) How to see flame fronts and how to see how mathematics are progressing Reliable Integration Automated Data Analysis Explanation of what is going on, something I don’t understand – automatic, self-explanatory answers Personalization (drug dosage, entertainment, information reception) Education My Name, title and AffiliationMy Name, Title, and Affiliation
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May 2, 20054 A Summary from Café Visualization Research Challenges Multi-Scale Large Data Multi-modal Uncertainity + error Multi-field, high-dimensional Time-varying Scalable Ontologies + interaction My Name, title and AffiliationMy Name, Title, and Affiliation
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May 2, 20055 A Summary from Café Visualization Research Challenges Data coordination Data collection (data reliability) Pro-active and reactive My Name, title and AffiliationMy Name, Title, and Affiliation
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May 2, 20056 Research Challenges from Sept 2004 workshop Quantification of good visual design principles Abstraction & clarity Evaluation Visual explanation vs. visual exploration Truth & uncertainty Interaction New input / output devices
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May 2, 20057 Application Challenges from Sept 2004 workshop Digital Human From walk-through scanning to personalized digital model Digital Medical Illustrator “What if we knew everything?” J. Statsko Computer Aided Diagnosis
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May 2, 20058 Grand Challenges from Sept 2004 Workshop Key national visualization investments? Digital Human Crisis Management, disasters, real time Dynamic Data Driven Application Systems (DDDAS) Bioinformatics - big data, clear questions, and funding Software toolkits for a larger number of scientists and engineers that scientists really use, better user interface How do we build and fund better teams (and team members get credit for doing so). Collaborative visualization Better health care Accelerating science
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May 2, 20059 Far Out Ideas from Sept 2004 Workshop Scientific visualization editing tool of the future Doctor's office of the future - imaging, genomics, diagnosis, visualization, simulation, etc. - Chris Millions of senors on the earth, map the earth's environmental status at multiple levels in real time - an earth health vis app - Hanspeter
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May 2, 200510 CRJ’s Top Visualization Research Issues 1.Think About the Science 2.Quantify Effectiveness 3.Error and Uncertainty Visual Representation 4.Perceptual Issues 5.Efficiently Using Novel Hardware Architectures, including high resolution displays 6.HCI 7.Global/Local Visualization (details within context) 8.Integrated PSEs (Pipeline complexity) 9.Multi-field Visualization 10.Integrating Sci and Info Visualization 11.Feature Extraction and Analysis 12.Time Dependent Visualization 13.Scalable, Distributed, and Grid Visualization 14.Visual Abstractions 15.Theory of Visualization
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