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Lecture 1 - Introduction

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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: World Wide Web

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