VOTech:DS6 Kick Off - Edinburgh 1
Visualization for VOTech:
Visualization@Leeds
Multivariate Data Visualization
Ken BrodlieSchool of ComputingUniversity of Leeds
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Background
• Involved in a number of UK e-Science projects
– Developing visualization middleware to provide a visual front-end to distributed and Grid computing
– Range of application areas from environmental science to computational biology
• gViz project has studied middleware to link simulation and visualization processes
– Simulation runs remotely– Pollution dispersion as
demonstrator application– Plus collaborative visualization
IRIS Explorer as front-end visualization system
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Dataflow Visualization Systems
• Visualization represented as pipeline:
– Read in data– Construct a visualization in
terms of geometry– Render geometry as image
• Realised as modular visualization environment
– IRIS Explorer is one example– Visual programming paradigm– Extensible – add your own
modules– Others include IBM Open
Visualization Data Explorer
data visualize render
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Imagine this ….
• An explosion!
• A dangerous chemical escapes!
• Where is the fugitive pollutant headed?
• Who needs to be evacuated?
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Understanding what will happen
• Model the dispersion by solving system of PDEs
• Understand solution by visualization
• What if scenarios … need to be able to steer the simulation
• For example, what if the wind changes direction?
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Linking Simulation and Visualization - Steering
• Computational steering:
– By including a control module in the pipeline, we can direct the simulation in response to the visualization
simulate visualize rendercontrol
PRO: not only can we track, we can alterthe actual course of the simulation
‘Human-in-the-loop’‘Human-in-the-loop’
Question for VOTech: Is this a potential paradigm for data mining?
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Tracking the Pollution
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Bring on the Grid!
• Real time computing is not fast enough for this application…
• … we need to predict the possible pollutant paths before they reach critical areas..
• So… can we run the simulation module on a powerful remote compute node, keeping visualization on the desktop?
• Solution: Grid-enabled IRIS Explorer
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Harnessing Remote Compute Resources
Explorer on single host
Explorer on multiple hosts
Select remote host
Automatic authentication using: •Globus certificate
•SSH Key pair
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Simulation Runs Remotely
Here the simulation runs on Grid machine…
Again… in VOTech, we might mine on the Grid, vis on the desktop
…but note it is often useful to run visualization modules remotely too
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Gathering the expertise…
• Environmental disaster!!!!
• We need to gather together group of experts..
• .. To understand the science…
• .. and get the message to the politicians
• Again do it fast.. No time to physically collocate
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internet
data visualize render
Sharing the Visualization
• Extend the dataflow model to interlink pipelines across the Internet
– Each person has their own pipeline but they can share data
• Collaborative server provides the link
• So one user – for example - can send geometry to another person for viewing
collaborative server
share
share
render
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Programming the Collaboration
• It is useful to be able to program the collaboration
– To adapt to how people want to collaborate
– To adapt to network bandwidths
• Here raw data is exchanged so a different visualization can be created
internet
collaborative server
data visualize render
share
share
visualise render
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Bring in the Meteorologist Remotely
Is there an analogyfor astrophysical dataanalysis?
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Background
• In Integrative Biology we are applying the gViz middleware to help biologists study models of electrical activity of the heart
• Multiple simulations initiated and monitored from the desktop
• Here IRIS Explorer as front-end…
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Detaching the Simulation – the gViz Library
• gViz library allows simulation writer to expose steering parameters and return results
• Simulation has ‘life of its own’, independently of visualization system
• Scientist can ‘tap-in’ to monitor long running simulation
Simulationcode
Sim com visualize render
control
discover/launch
GridInformation
Gridresources
ResearcherDesktop
gViz-lib
gViz-lib
This work is quite general:gViz links back-end computationwith front-end visualization – nodependence on IRIS Explorer
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Background
• Other front-ends can be attached – for example, Matlab
• Or a secure Web service…
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Web Visualization Services
• Web technology offers us ways of delivering visualization services to the wider community
– Early demonstrator: air quality data visualization
– HTML form as front-end, CGI script drives IRIS Explorer on server, VRML returned
– New era of Web services brings new opportunities
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Visualization Web Service - WebSerViz
Haoxiang Wang
visualization.leeds.ac.uk:8080/jsp/webserviz/form.html
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WebSerViz - typical output
Combination of isosurfaceand slices
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WebSerViz Architecture
• Apache Tomcat• JavaBean• JSP
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Grid Services
• Grid services add authentication to Web services
• Heart Modelling Grid Service uses:
– Web interface where user specifies user name and passphrase, and location of gViz directory service
– gViz library to connect with simulations
– ImageService to build image from simulation data
• Returned as a Web page
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Anatomy of the Heart Modelling Grid Service
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Multivariate Visualization: Hypercell
• Hypercell is an approach to visualization of multivariate datasets
– Developed by Selan dos Santos
• Basic concept:– Map each observation to a
position in N-dimensional space– Define an N-d region of interest,
and a focus point within it– Navigate through this space by
an organised sequence of projections
• Applied to range of applications– Astrophysics– E-Learning– Nonlinear optimization
• Concept implemented in IRIS Explorer
• Complement to existing techniques available in eg Xmdvtool:
– Parallel coordinates– 2D scatter plots– Glyphs
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Define the N-d region
Each attribute has a range of interestand a focus value
These values can be dynamically changed
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Select the Projection
The user can select 1D,2D, 3D or 4D projections
from the graph tool
Here we aredynamicallychangingsubspacesfor functionvisualization
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Astrophysical Application
• Joint study with Bob Mann
• SuperCOSMOS Science Archive
• Only looked at subset of 57 attributes and 1000 observations
• Analytical task:– Calibration of SSA data– Look for expected and
unexpected correlations
• … and made us rethink some ideas!
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Location of Source in Galactic Coordinates
Subspace (l, b, ebmv)with colouring bymeanclass attribute –An outlier is evident
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Location of Source in Galactic Coordinates
Removing the ‘green’ classreveals the outlier
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Location of Source in Galactic Coordinates
Same cell of databut coloured accordingto prfstatb attribute.
Most candidates to beclassified as stars areat bottom, segmentedIn red
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Magnitude Values of Sources
Subspace defined by (classmag(b-r1), classmag(r1-i), classmagb))
Coloured by meanclass Colour and size by prfstatri
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Magnitude Values of Sources
Subspace defined by (classmag(b-r1), gcormag(b-r1), scormag(b-r1))
Colour mapped to meanclass Colour and size to prfstatr1
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Relating Colour to Shape Attributes
Subspace (prfstatb, prfstatr2, prfstati)
Colour mapped to meanclass
Subspace (ellipb, ellipr1, ellipi)
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Following On
• Need to record history of explorations in Nd space
• Could provide as a Web service
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Xmdvtool
• Here are some student attempts at the same data using Xmdvtool
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Ellipticity of sources
=2 =1Meanclass:Parallel Coordinates
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Ellipticity of sources
=2 =1Meanclass:2D Scatterplot
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Profile stat of sources
=2 =1Meanclass:Parallel Coordinates
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Profile stat of sources
=2 =1Meanclass:2D Scatterplot
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DS6 Developments
• Visualization– Understand the data to be
visualized– Determine the appropriate
technique• Parallel coordinates• Scatter plots• Glyphs
• Visualization and Data Mining– Understand the relationship– Can we borrow ideas from
computational steering?
• Visualization software– Many existing systems
• IRIS Explorer• IBM Open Visualization
Data Explorer• Vtk
– Integration with other Astrogrid/VO tools
• Delivery– Web service– Grid service
• Collaboration in project– How do we exploit the different
skills and experiences in the project, to maximum effect?