Transcript Visual Analytics Vision and Strategy

RVAC
Washington
D.C.
RVAC
RVAC
RVAC
National and Regional
Visual Analytic Centers
NVAC and RVACs
R&D System Architecture
Don Jones, Ph.D.
System Architect
National Visualization & Analysis Center
Pacific Northwest National Laboratory
Detecting the Expected -- Discovering the UnexpectedTM
Web, Service-Base Architecture
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Functional Architecture Diagram
User Applications:
Analyst
MSOffice In-Spire Starlight Nebraska
Notebook
Graph Viewer
Cross Cutting
Services:
Visualization Services:
Presentation
Multi-visualization Techniques
Graph
Generation
Time Sequence
Generation
Authentication
Volume
Generation
Surface
Generation
Privacy
Analysis Services:
Volume Visualization Preparation
Visual Representation Generation
Simulation Management
Statistical Analysis
Feature Detection and Extraction
Query Translation
Data Fusion & Comparison
Data Services:
Permutation
M→N
Delegation
Collaborative
Control
Event
1D/2D Subsetting
Filtering
Data Mapping
Format/Representation
Conversion
Data Algebra
x,y,z → mag/Φ
Language
Translation
Logging
Preferences
Infrastructure:
Hardware
Authorization
Libraries
Data Store
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Architecture Design, Approach
Research & Development, RVAC Integration
“Platforms” created from “web/portal” services
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Production, deployment, by mission systems not NVAC
Infrastructure components need to be identified
Based on three tier Web, Client-Server
Architecture
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Data Services (Data management)
Multi-layer computer Services (Process Management)
User Services (User System Interface)
Privacy & security will be a service
Reference model for SW development.
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Interoperability
What is interoperability and why do we want it?

Interoperability is the idea that different developers, working
almost entirely independently, can contribute software
components to a common, quality-assured collection (eg, a
repository) AND that components can easily obtained from this
collection and easily combined into a larger assemblies using a
variety of interconnection mechanisms.
Costs/Barriers/Risks of Interoperability
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Cost, technical, psychological & legal.
Major Challenges
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Applications and enhanced analysis
Very large, multiple & diverse datasets
Scalability
Human-computer interfaces
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Research Challenges interoperability
Research and Barriers to Interoperability
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Large/comlex data
Performance
Heterogeneity
Rate of Change
Diverse application domains
Fundamental change to the visualization process/
system
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Establish NVAC Architecture Panel
Provide leadership and technical expertise for
evolving NVAC R&D architecture.
To achieve the best, most flexible design.
Have investment of concepts from various
related projects
Group knowledge on available technologies
Increase visibility of project, becoming
advocates for NVAC R&D Architecture.
Provide current functionality from projects.
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Items of interest
SC2005 - HPC Analytics challenge
competition. Web page will be operational at
SC2004 (or sooner).
Visual Analytics Research and Development
Challenges Book
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AAAS/IEEE
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February, 2005
Don Jones, [email protected]
URL - http://nvac.pnl.gov/
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