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Geovisual Analytics – Exploring and analyzing large spatial and multivariate data Prof Mikael Jern & Civ IngTobias Åström
http://ncva.itn.liu.se/
Agenda
Introduction to a Geovisual AnalyticsDemo Explore OECD data GAV ToolkitDemo very large spatial Swedish Zip code dataSpatial-temporal and multivariate dataDemo - Communicate result and knowledgeConclusion
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Partners and Funding Group
Director: Professor Mikael Jern http://ncva.itn.liu.se
Geovisual Analytics - Definition
The science of analytical reasoning facilitated by interactive visual interfaces;E plo ing and anal ing la ge spatial tempo al and Exploring and analyzing large spatial-temporal and multivariate data;Discern trends or patterns - derive insight and draw conclusions;Communicate discovery and knowledge effectively for action;Moving Research into PracticeMoving Research into Practice
http://nvac.pnl.gov/
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Scope of Visual Analytics and Related Sciences
InformationVisualization Interactive
PerformanceScientificVisualization
VisualAnalytics
GeoVisualization
PresentationCognitive Perceptual
VisualQueryFilter
PresentationCommunication
VisualData Mining
StatisticalAnalysis
PerceptualScience
DataTransformation
Background - Definition – Geovisual Analytics
Explore and analyse voluminous nature of social scientific, environmental, energy, logistics and economic data;Geovisual Analytics is now actively pursued by research groups worldwide;Our objective is to provide effective Geovisual Analytics tools for exploring large time variant and multivariate attributes simultaneous including a spatial dimension;We present a toolkit called “GAV” for customizing Geovisual Analytics applications;Analytics applications;We present a number of GeoWizard applications such as a World or OECD Data ExplorerFree available
http://vita.itn.liu.se/geowizard
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World Map Pop 65+ - an example of a small data set
Belgium
OECD European TL3 data – Pop Growth 98-03
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Table Lens
Map View
Interact with data from different perspectives simultaneouslyMultiple-linked and Coordinated Views
Scatter Plot Scatter Matrix
Parallel CoordinatesParallel CoordinatesList ViewList View
Background - Definition – Geovisual Analytics
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The 3 DimensionsSpatial – Temporal and Multivariate Data
Shape Coordinate Data and Attribute Excel Data
Shape (map) Coordinate datawith region ID Attribute DataRegion ID
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attributesspatial
EXCEL
Parallel Coordinates
Multivariate Geovisual Analytics and Parallel Coordinates
Profile for Belgium
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Compare Profiles for two Countries
CLUSTER
Spain
USA
Parallel Coordinates – Exploration Tools
HistogramMean, Median
Percentiles OutliersDynamic Filter FocusMean, Median
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Geovisual Analytical Reasoning Process
Gather information – Tasks?Visual representationVisual representation
Choose visual forms that aid analysis
Develop insightThrough exploration anddynamic visual inquiries
Produce results (knowledge)Produce results (knowledge)Presentation, Communication and Story Telling
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“Geovisual Analytics” - GAV toolkit
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“GeoAnalytics Visualization” GAV Framework
GAV is based on C# and .NET – Integrates with Visual Studio;Optimized for Interaction – we use DirectX;Cli t b d h f d t l tiClient-based approach for data exploration;Appropriate for multiple-linked views applications;3D data model for spatial-temporal and multivariate attribute data;Integrated mechanism for saving and packaging the results of a visual reasoning process;Public Domain Software;
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Glue GAV components together to build a tailor-made GeoAnalytics application
Parallel CoordinatesTable lens Scatter Plot Scatter Matrix
Excel Data Reader
Geowizard Application
Map
One panel hosts one or more visualizationsImproves view organizing
Splitters and resizable
Glue GAV components together with Visual Studio
Splitters and resizable
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Explore World data
Flood Viewer
3D Oceanographic Visualization
Interactive Visual Interface
Interactivity and Information DensityAvoid traditional GUI elements and pop-ups;Maximum screen area reserved for visualization;Maximum screen area reserved for visualization;Optimized performance;Interactivity is embedded in the Components
Brushing, picking, drag-and-drop, move splitters, zoom, pan, query and filter, focus & context;
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GeoZip 10,000 zip code regions
Spatial – Temporal and Multivariate Energy DataSee the whole visual analysis
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Spatial – Temporal and Multivariate Energy DataSee the whole visual analysis
Spatial – Temporal and Multivariate Energy DataSee the whole visual analysis
removed
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Step1: Explorative Data Analysis Step2: Collaborative and Communicate Analytical Reasoning
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Interactive Visualization embedded into HTML Documents
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Conclusion
Applications or Toolkit for Geovisual Analytics
Low learning threshold;
Easy and flexible data access through Excel;Easy and flexible data access through Excel;
Multiple-linked views applications becomes easy;
Scalable applications – easy to replace a component;
Shorten development time by utilising already developed and assessed components;
We have released publicly applications and toolkit, please visit http://ncva.itn.liu.se
Special thanks to Lars Thygesen and staff for providing OECD data and shape files for this presentation
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Challenges for our GeoVisual Analytics Research Agenda
Large spatial-temporal and multivariate data;
Integrate statistics and data transformation;
Explore uncertainty in data;Explore uncertainty in data;
Integrated Explorative Data Analysis and Communication through Snapshots and Story Telling;
Expand GAV with Atomic VA components for more scalability;
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Make and Visual Analytics available to research & education, industry and governmental institutions;
Comprehensive and usable Web site: http://ncva.itn.liu/
Demonstrators, education material, GAV Framework
http://ncva.itn.liu.se
Prof Mikael JernProf Mikael Jern
Thank you !!!Thank you !!!
Prof Mikael JernProf Mikael JernLinköping University, Sweden
