1. Lecture 1 - Introduction
Data Visualization
MSc Module
School of Computing
Ken Brodlie
Semester
Lecture 1 - Introduction

2. Visualization Visualization now seen as key part of modern computing
High performance computing generates vast quantities of data ...
High resolution measurement technology likewise ...
microscopes, scanners, satellites
Information systems involve not only large data sets but also complex connections...
... we need to harness our visual senses to help us understand the data

3. Getting Started What is Visualization? - a definition
Where is it useful? - some applications
What is the history?
What tools are now available?
How are we going to study it?
MSc in Distributed Multimedia Systems
MSc in Computational Fluid Dynamics

4. Data Visualization = Scientific Vis + Information Vis
Scientific Visualization
Numerical data from science, engineering and medicine
Information Visualization
Numeric and non-numeric data
Ozone layer around earth
Automobile web site
- visualizing links

5. Scientific Visualization - What is it?
Reality
Observation
Simulation
Data
Images, animation
Visualization

6. Applications - Meteorology
Pressure at levels
in atmosphere
- illustrated by
contour lines in a
slice plane
Generated by
the Vis5D system
from University of
Wisconsin (now
Vis5d+)
Vis5d:
Vis5d+ :

7. Applications - Medicine
From scanner data, we can
visualize 3D pictures
of human anatomy, using
volume rendering
Generated by VOXELman
software from University
of Hamburg

8. Applications – Climate Prediction
Simulation of 21st century climate evolution
Real-time display of results
temperature, cloud, precipitation, etc
Massive ensemble of runs : distributed public-resource computing project
see to participate!

9. Applications – Computational Fluid Dynamics
Flow of air around a car
Vectors and particle paths illustrate flow
Coloured slice indicates pressure

10. Applications – Computational Fluid Dynamics
Interface between immiscible fluids
e.g. oil / water
Loops and fingers arise when mixing starts
Rayleigh-Taylor instability
Simulated on ASCII Blue Pacific (Cook & Dimotakis, 2001)
Interface visualized using a density isosurface

11. Applications - Molecular Modelling
2D potential energy function
molecule inside a zeolite channel
Displayed as coloured surface (left)
part also displayed using contour plot (right)

12. Applications - Molecular Modelling
3D potential energy function
three atoms in a box
Displayed as isosurface (left)
interactive probe also shows how potential varies between two points (right)

13. Visualization BC
Imagination or visualization, and in particular the use of diagrams, has a crucial part to play in scientific investigation.
Rene Descartes, 1637
There are many examples of the use of visualization Before Computers (BC)
graph plots in 10th century
business graphics in 18th century (Playfair)
contour plots in 18th century (Halley)

14. The First Visualization
This and following two pictures are taken from Brian
Collins ‘Data Visualization - Has it all been seen before?’
in ‘Animation and Scientific Visualization’, Academic Press

15. The First Business Graphics

16. The First Contour Map

17. Visual Thinkers
Many of the great scientists were good at visual thinking:
Leonardo da Vinci
James Clerk Maxwell
Michael Faraday
Albert Einstein
This was often at the expense of verbal skills
Tom West : “In the Mind’s Eye”
See also
Maxwell’s clay model now
in New Cavendish Laboratory, Cambridge
(picture by Tom West)

18. Early Computer Visualization
From early days of computing, scientists have carried out numerical simulation - and looked to visualization to help understand the results.
Visualization systems have evolved in four different styles - all still in use today (so not really history!)

19. Subprogram Libraries 1960 onwards
Libraries of subprograms to draw graphs, contour plots …
Scientists include calls to library routines from within their own code
Leading examples from era were:
GHOST (UKAEA Culham)
NAG Graphics Library
NAG Graphics :

20. Subprogram Libraries This style continues today
NAG Graphics Library still available
Vtk C++ classes provide modern version of this style
Great flexibility – but need to program
Application Programming Interface
Vtk :

21. Interactive Packages From late 1970 onwards
Menu-driven packages allowing data to be visualized without need to write programs
Example:
gnuplot
Less flexible, but no programming!
gnuplot

22. Interactive Packages
Matlab is a powerful system for computation and visualization
Has its own C-like language

23. Visualization Today
Recent surge of interest in visualization was sparked by an NSF report:
Visualization in Scientific Computing
McCormick, de Fanti and Brown
Argued that investment in high performance computing in US was wasted unless there was corresponding investment in visualization
This motivated a third style of visualization system...

24. Visual Programming Systems
From late 1980s onwards
Visualization seen as a sequence of simple processing steps: eg contouring
read in data
create contour lines
draw contour lines
Systems provide modules implementing simple steps in a visualization pipeline
Scientist uses ‘visual programming’ to connect modules together

25. Visual Programming - IRIS Explorer

26. Visual Programming Systems
Visual programming allows easy experimentation which is what one needs in visualization
Examples are:
IRIS Explorer
AVS
OpenDX (grown from IBM Visualization Data Explorer)

27. Service-based Visualization
The Internet era has introduced a fourth style of system – where a visualization ‘service’ is delivered over the internet using Web technologies
Client-side with Java applets….

28. Service-based Visualization
… or server side
Here a form on a web page is used to make a visualization ‘request’
Processed by a visualization system on server and returned to client as VRML
IRIS Explorer SerVis

29. The Four Phases of Visualization Systems
These four phases correlate with four phases in computing generally
Subprogram libraries
begun in era of batch computing
Interactive packages
begun in era of interactive computing, with terminals connected to host
Visual programming systems
begun in era of workstation computing, with graphical user interfaces
Service-based visualization
begun in era of internet computing

30. Information Visualization
Has emerged over last decade
Building on success of scientific visualization
Driven by the escalating volumes of data fuelled by the new technologies (eg supermarket checkouts!) and the accessibility of data via the Internet
Characterised by large quantities of data – not necessarily numbers – and search for relationships amongst the data …
… but no absolute dividing line between SciVis and InfoVis

31. Outline of the Course Lectures
Monday 10 (Parkinson-B9) ; Friday 9 (LT11)
Practical sessions using gnuplot, IRIS Explorer and xmdvtool under Linux
Background study

32. Outline of Lecture Course Data Visualization - I
Introduction and historical view
Fundamental concepts
Scientific Visualization techniques
Scalar data - one value at a point
1D - graphs, ..
2D - contour maps, ..
3D - isosurfaces, volume rendering
Vector data - many related values at a point
velocity values : flow visualization

33. Outline of Lecture Course Data Visualization - II
Publication of visualization
VRML for 3D web presentation
Visualization Systems
Computational steering
linking simulation and visualization
Grid computing and visualization
Collaborative Visualization
Group working on the Internet
… this will complete the programme for CFD students
… but DMS students continue

34. Outline of Lecture Course: Data Visualization - III
Web-based visualization
using the Web as a distributed computing environment
Information Visualization
how to interpret large quantities of data using visualization
multivariate data

35. Practical Work For DMS and CFD students - use of IRIS Explorer
state of art visualization system
Linux pc’s
practical sessions
For DMS students – xmdvtool (multivariate data)
Publication using the World Wide Web
Assessment
assignments to visualize datasets
Experience of other systems
gnuplot

36. Background Study Reading World Wide Web mainly recent papers
IRIS Explorer training materials
generally ... a source of up-to-date information and examples

37. Books The Visualization Toolkit (3rd edition)
W Shroeder, K Martin, W Lorensen – Kitware Inc
Introduction to Volume Rendering
B. Lichtenbelt et al - Prentice Hall (1998)
Information Visualization
R. Spence – Addison-Wesley (2001)
Scientific Visualization Tech & Applns
K W Brodlie et al
Springer Verlag (1992)

38. Objectives
To be aware of the value of visualization to gain insight into both numeric data (from science, engineering and medicine for example) …
… and also non-numeric information (such as networks and documents)
To understand the fundamental techniques for data visualization
To be skilled in the use of a state of art visualization system
DMS
CFD
DMS

39. Keeping in Touch E-mail Newsgroup for my postings:
Newsgroup for my postings:
local.modules.vis
Newsgroup for your postings:
local.modules.vis.talk
World Wide Web