votech:ds6 kick off - edinburgh1 visualization for votech: visualization@leeds multivariate data...

VOTech:DS6 Kick Off - Edinburgh 1

Visualization for VOTech:

Visualization@Leeds

Multivariate Data Visualization

Ken BrodlieSchool of ComputingUniversity of Leeds


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


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


Imagine this ….

• An explosion!

• A dangerous chemical escapes!

• Where is the fugitive pollutant headed?

• Who needs to be evacuated?


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?


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?


Tracking the Pollution


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


Harnessing Remote Compute Resources

Explorer on single host

Explorer on multiple hosts

Select remote host

Automatic authentication using: •Globus certificate

•SSH Key pair


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


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


internet


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


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


share

share

visualise render


Bring in the Meteorologist Remotely

Is there an analogyfor astrophysical dataanalysis?


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…


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


Background

• Other front-ends can be attached – for example, Matlab

• Or a secure Web service…


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


Visualization Web Service - WebSerViz

Haoxiang Wang

visualization.leeds.ac.uk:8080/jsp/webserviz/form.html


WebSerViz - typical output

Combination of isosurfaceand slices


WebSerViz Architecture

• Apache Tomcat• JavaBean• JSP


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


Anatomy of the Heart Modelling Grid Service


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


Define the N-d region

Each attribute has a range of interestand a focus value

These values can be dynamically changed


Select the Projection

The user can select 1D,2D, 3D or 4D projections

from the graph tool

Here we aredynamicallychangingsubspacesfor functionvisualization


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!


Location of Source in Galactic Coordinates

Subspace (l, b, ebmv)with colouring bymeanclass attribute –An outlier is evident



Removing the ‘green’ classreveals the outlier



Same cell of databut coloured accordingto prfstatb attribute.

Most candidates to beclassified as stars areat bottom, segmentedIn red


Magnitude Values of Sources

Subspace defined by (classmag(b-r1), classmag(r1-i), classmagb))

Coloured by meanclass Colour and size by prfstatri


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


Relating Colour to Shape Attributes

Subspace (prfstatb, prfstatr2, prfstati)

Colour mapped to meanclass

Subspace (ellipb, ellipr1, ellipi)


Following On

• Need to record history of explorations in Nd space

• Could provide as a Web service


Xmdvtool

• Here are some student attempts at the same data using Xmdvtool


Ellipticity of sources

=2 =1Meanclass:Parallel Coordinates


Ellipticity of sources

=2 =1Meanclass:2D Scatterplot


Profile stat of sources

=2 =1Meanclass:Parallel Coordinates


Profile stat of sources

=2 =1Meanclass:2D Scatterplot


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?

votech:ds6 kick off - edinburgh1 visualization for votech: visualization@leeds multivariate data...

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