1. VOTech:DS6 Kick Off - Edinburgh1 Visualization for VOTech: Visualization@Leeds Multivariate Data Visualization Ken Brodlie School of Computing University of Leeds

2. VOTech:DS6 Kick Off - Edinburgh2 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

3. VOTech:DS6 Kick Off - Edinburgh3 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

4. VOTech:DS6 Kick Off - Edinburgh4 Imagine this …. An explosion! A dangerous chemical escapes! Where is the fugitive pollutant headed? Who needs to be evacuated?

5. VOTech:DS6 Kick Off - Edinburgh5 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?

6. VOTech:DS6 Kick Off - Edinburgh6 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 simulatevisualize rendercontrol PRO: not only can we track, we can alter the actual course of the simulation ‘Human-in-the-loop’ Question for VOTech: Is this a potential paradigm for data mining?

7. VOTech:DS6 Kick Off - Edinburgh7 Tracking the Pollution

8. VOTech:DS6 Kick Off - Edinburgh8 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

9. VOTech:DS6 Kick Off - Edinburgh9 Harnessing Remote Compute Resources Explorer on single host Explorer on multiple hosts Select remote host Automatic authentication using: Globus certificate SSH Key pair

10. VOTech:DS6 Kick Off - Edinburgh10 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

11. VOTech:DS6 Kick Off - Edinburgh11 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

12. VOTech:DS6 Kick Off - Edinburgh12 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 render

13. VOTech:DS6 Kick Off - Edinburgh13 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 visualise render

14. VOTech:DS6 Kick Off - Edinburgh14 Bring in the Meteorologist Remotely Is there an analogy for astrophysical data analysis?

15. VOTech:DS6 Kick Off - Edinburgh15 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…

16. VOTech:DS6 Kick Off - Edinburgh16 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 Simulation code Sim com visualize render control discover/ launch Grid Information Grid resources Researcher Desktop gViz-lib This work is quite general: gViz links back-end computation with front-end visualization – no dependence on IRIS Explorer

17. VOTech:DS6 Kick Off - Edinburgh17 Background Other front-ends can be attached – for example, Matlab Or a secure Web service…

18. VOTech:DS6 Kick Off - Edinburgh18 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

19. VOTech:DS6 Kick Off - Edinburgh19 Visualization Web Service - WebSerViz Haoxiang Wang visualization.leeds.ac.uk:8080/jsp/webserviz/form.html

20. VOTech:DS6 Kick Off - Edinburgh20 WebSerViz - typical output Combination of isosurface and slices

21. VOTech:DS6 Kick Off - Edinburgh21 WebSerViz Architecture Apache Tomcat JavaBean JSP

22. VOTech:DS6 Kick Off - Edinburgh22 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

23. VOTech:DS6 Kick Off - Edinburgh23 Anatomy of the Heart Modelling Grid Service

24. VOTech:DS6 Kick Off - Edinburgh24 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

25. VOTech:DS6 Kick Off - Edinburgh25 Define the N-d region Each attribute has a range of interest and a focus value These values can be dynamically changed

26. VOTech:DS6 Kick Off - Edinburgh26 Select the Projection The user can select 1D, 2D, 3D or 4D projections from the graph tool Here we are dynamically changing subspaces for function visualization

27. VOTech:DS6 Kick Off - Edinburgh27 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!

28. VOTech:DS6 Kick Off - Edinburgh28 Location of Source in Galactic Coordinates Subspace (l, b, ebmv) with colouring by meanclass attribute – An outlier is evident

29. VOTech:DS6 Kick Off - Edinburgh29 Location of Source in Galactic Coordinates Removing the ‘green’ class reveals the outlier

30. VOTech:DS6 Kick Off - Edinburgh30 Location of Source in Galactic Coordinates Same cell of data but coloured according to prfstatb attribute. Most candidates to be classified as stars are at bottom, segmented In red

31. VOTech:DS6 Kick Off - Edinburgh31 Magnitude Values of Sources Subspace defined by (classmag(b-r1), classmag(r1-i), classmagb)) Coloured by meanclassColour and size by prfstatri

32. VOTech:DS6 Kick Off - Edinburgh32 Magnitude Values of Sources Subspace defined by (classmag(b-r1), gcormag(b-r1), scormag(b-r1)) Colour mapped to meanclassColour and size to prfstatr1

33. VOTech:DS6 Kick Off - Edinburgh33 Relating Colour to Shape Attributes Subspace (prfstatb, prfstatr2, prfstati) Colour mapped to meanclass Subspace (ellipb, ellipr1, ellipi)

34. VOTech:DS6 Kick Off - Edinburgh34 Following On Need to record history of explorations in Nd space Could provide as a Web service

35. VOTech:DS6 Kick Off - Edinburgh35 Xmdvtool Here are some student attempts at the same data using Xmdvtool

36. VOTech:DS6 Kick Off - Edinburgh36 Ellipticity of sources =2=1 Meanclass:Parallel Coordinates

37. VOTech:DS6 Kick Off - Edinburgh37 Ellipticity of sources =2=1 Meanclass:2D Scatterplot

38. VOTech:DS6 Kick Off - Edinburgh38 Profile stat of sources =2=1 Meanclass:Parallel Coordinates

39. VOTech:DS6 Kick Off - Edinburgh39 Profile stat of sources =2=1 Meanclass:2D Scatterplot

40. VOTech:DS6 Kick Off - Edinburgh40 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?