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ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing...

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ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds
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Page 1: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.1

Envisioning Information

Lecture 1

Part 1: Introduction

Ken BrodlieSchool of ComputingUniversity of Leeds

Page 2: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.2

• 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

• … that is, to ‘Envision Information’

Visualization

Page 3: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.3

Envisioning Information

• So where did we get the title??

• Edward Tufte has written a series of books on the design of good visualizations

• Visit:http://www.edwardtufte.com/tufte/

Page 4: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.4

• 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?

Getting Started

Page 5: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.5

First : An Experiment

• You need a watch with a second-hand

• Without using pencil and paper (or a calculator!!), multiply 72 by 34

• How long did it take?

• Now you need pencil and paper as well as watch

• Multiply 47 by 54

• How long did it take?

• Conclusion?

Page 6: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.6

What is Visualization?

• Generally:– The use of computer-supported, interactive, visual representations

of data to amplify cognition Card, McKinlay and Schneiderman

• Two ‘branches’:– Scientific Visualization

– Information Visualization

Page 7: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.7

Visualization – Twin Subjects

• Scientific Visualization– Visualization of physical

data

• Information Visualization– Visualization of abstract

data

Ozone layer around earthAutomobile web site- visualizing links

Page 8: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.8

Visualization – Bridging the Gap between the Computer and the Mind

Visualization

HumanInformation

Analyst

ComputationResources

InformationResources

Page 9: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.9

Applications - Meteorology

Pressure at levelsin atmosphere- illustrated by contour lines in aslice plane

Generated bythe Vis5D systemfrom University ofWisconsin (nowVis5d+) Vis5d: http://www.ssec.wisc.edu/~billh/vis5d.html

Vis5d+ : http://vis5d.sourceforge.net

Page 10: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.10

Applications - Medicine

From scanner data, we canvisualize 3D picturesof human anatomy, usingvolume rendering

Generated by Anatomy.TVused by our medical studentsto learn anatomy

Look under Anatomy.TV in Library electronic resources

Page 11: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.11

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 www.climateprediction.net to participate!

Page 12: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.12

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

Page 13: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.13

Applications – Computational Fluid Dynamics

• Flow of air around a car

– Vectors and particle paths illustrate flow

– Coloured slice indicates pressure

Page 14: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.14

Applications – Information Networks

• Visualization can be applied to networks of information

• Chaomei Chen’s Pathfinder visualizations have been used to study trends in scientific research

• Here we see articles on terrorism, coloured by year of publication, and clustered by topic…

• For more on this, see:

http://cluster.cis.drexel.edu/~cchen/citespace/

Page 15: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.15

Applications – Integrative Biology

• The School is a partner in a large e-science project on Integrative Biology

http://www.integrativebiology.ox.ac.uk

• This involves modelling behaviour of human heart, and of cancer tumours

• Visualization is of electrical activity in heart, showing the spiral wave pattern that is a precursor to fibrillation

Page 16: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.16

Applications - Astronomy

• The Astrogrid project is building a virtual observatory

http://www.astrogrid.org

http://www.eurovotech.org

• Visualization is a fundamental tool in presenting star maps and in understanding relationships between observations

Page 17: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.17

• Imagination or visualization, and in particular the use of diagrams, has a crucial part to play in scientific investigation.– Who said this? When?

• 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)

Visualization BC

Answer: Rene Descartes, 1637

Page 18: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.18

The First Visualization

This and following two pictures are taken from BrianCollins ‘Data Visualization - Has it all been seen before?’in ‘Animation and Scientific Visualization’, Academic Press

Page 19: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.19

The First Business Graphics

Page 20: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.20

The First Contour Map

Page 21: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.21

• 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

http://www.krasnow.gmu.edu/twest/maxwell_visual.html

Maxwell’s clay model now in New Cavendish Laboratory, Cambridge(picture by Tom West)

Visual Thinkers

Page 22: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.22

• From early days of computing, scientists have carried out numerical simulation - and looked to visualizationvisualization to help understand the results.

• Visualization systems have evolved in four different styles - all still in use today (so not really history!)

Early Computer Visualization

Page 23: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.23

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 1970-1985 era were:

– GHOST (UKAEA Culham)– NAG Graphics Library

NAG Graphics : www.nag.co.uk

Page 24: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.24

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 : www.visualizationtoolkit.org

Page 25: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.25

• From late 1970 onwards

• Specialist packages allowing data to be visualized using special purpose scripting language

• Example:– gnuplotwww.gnuplot.info

• Less flexible, but simpler (provided commands are easy to learn!)

gnuplot

Interactive Packages

Page 26: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.26

Interactive Packages

• Matlab is a powerful system for computation and visualization

– Has its own C-like language

www.mathworks.com

Page 27: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.27

Interactive Packages

• This style continues today…

• R is a powerful interactive environment for statistical computation and visualization

• Freely available – for both linux and Windows

Page 28: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.28

Interactive Packages

• The popularity of spreadsheets has brought a requirement to provide visualization charts…

• Excel has a chart wizard to guide construction of a variety of chart types…

Page 29: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.29

• Recent surge of interest in scientific visualization was sparked by an NSF report:

Visualization in Scientific Computing– McCormick, de Fanti and Brown - 1987

• 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...

Scientific Visualization

Page 30: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.30

• From late 1980s onwards• Scientific 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

Visual Programming Systems

Page 31: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.31

Visual Programming - IRIS Explorer

Page 32: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.32

• Visual programming allows easy experimentation which is what one needs in visualization

• Examples are:– IRIS Explorer

www.nag.co.uk– AVS

www.avs.com– OpenDX (grown from IBM Visualization Data Explorer)

www.opendx.org

Visual Programming Systems

Page 33: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.33

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….

www.sdsc.edu/vizwiz

Page 34: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.34

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 – the Web standard for 3D graphics

Page 35: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.35

Service Based Visualization

• Kartoo allows you to visualize results of web searches..

• See:www.kartoo.com

Search for ‘EnvisioningInformation’

Page 36: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.36

• 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

The Four Phases of Visualization Systems

Page 37: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.37

• Sessions– 10 till 12; 2 till 4

• Mix of:– Lectures (10-11; 2-3)

– Study sessions

– Practical work

– Research conference

• Background study

Outline of the Course – Visualization Tuesdays

Page 38: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.38

Module Outline - Lectures

• Introduction and historical view• Simple graphs• Data tables – multivariate data visualization• Graphs and Networks• Sequences• Documents; maps; software• Interaction techniques• Perception issues• Scientific visualization

– Scalar values – 1D, 2D, 3D

– Flow visualization

• Collaborative visualization; web based visualization

Page 39: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.39

Module Outline – Study Sessions

• A research paper to read…• A web link to follow…• A case study from Edward Tufte…• A request …

• To be presented by you as well as me!

Page 40: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.40

• Simple graphs and charts:– Gnuplot, R, Excel

• Data tables:– Xmdvtool

• Scientific visualization - use of IRIS Explorer– state of art visualization system– Linux pc’s– practical sessions

Module Outline – Practical work

Page 41: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.41

Module Outline – Research Conference

• During module we shall prepare for a closing conference

– Topic to be identified

– Background research done

– Novel idea explored

– Paper submitted for critical review

– Paper revised for publication

– Paper presented

Page 42: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.42

• There is no single course textbook

• The Web is of course a fundamental resource

• Envisioning Information– Edward Tufte

• Information Visualization– R. Spence – Addison-Wesley (2001)

• The Visualization Toolkit (3rd edition)– W Shroeder, K Martin, W Lorensen – Kitware Inc

• Set of links will be maintained on a ‘Resources’ page

Reference Material

Page 43: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.43

• 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 appreciate design issues in visualization

• To be skilled in the use of a number of state of art visualization systems

Objectives

Page 44: ENV 2006 1.1 Envisioning Information Lecture 1 Part 1: Introduction Ken Brodlie School of Computing University of Leeds.

ENV 2006 1.44

• E-mail– [email protected]

• Newsgroup for my postings:– local.modules.env

• Newsgroup for your postings:– local.modules.env.talk

• World Wide Web – My Home Page– http://www.comp.leeds.ac.uk/kwb/

• World Wide Web – Module Page– http://www.comp.leeds.ac.uk/kwb/ENV

Keeping in Touch


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