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1.1 Vis_04 Data Visualization MSc Module School of Computing Ken Brodlie Semester 1 2004-2005 Lecture 1 - Introduction.

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Presentation on theme: "1.1 Vis_04 Data Visualization MSc Module School of Computing Ken Brodlie Semester 1 2004-2005 Lecture 1 - Introduction."— Presentation transcript:


2 1.1 Vis_04 Data Visualization MSc Module School of Computing Ken Brodlie Semester Lecture 1 - Introduction

3 1.2 Vis_04 Visualization n Visualization now seen as key part of modern computing n High performance computing generates vast quantities of data... n High resolution measurement technology likewise... – microscopes, scanners, satellites n Information systems involve not only large data sets but also complex connections... n... we need to harness our visual senses to help us understand the data

4 1.3 Vis_04 Getting Started n What is Visualization? - a definition n Where is it useful? - some applications n What is the history? n What tools are now available? n How are we going to study it? – MSc in Distributed Multimedia Systems – MSc in Computational Fluid Dynamics

5 1.4 Vis_04 Data Visualization = Scientific Vis + Information Vis n Scientific Visualization – Numerical data from science, engineering and medicine n Information Visualization – Numeric and non- numeric data Ozone layer around earth Automobile web site - visualizing links

6 1.5 Vis_04 Scientific Visualization - What is it? Images, animation Visualization Reality Data ObservationSimulation

7 1.6 Vis_04 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+ :

8 1.7 Vis_04 Applications - Medicine From scanner data, we can visualize 3D pictures of human anatomy, using volume rendering Generated by VOXELman software from University of Hamburg

9 1.8 Vis_04 Applications – Climate Prediction n Simulation of 21 st century climate evolution n Real-time display of results – temperature, cloud, precipitation, etc n Massive ensemble of runs : distributed public- resource computing project – see to participate!

10 1.9 Vis_04 Applications – Computational Fluid Dynamics n Flow of air around a car – Vectors and particle paths illustrate flow – Coloured slice indicates pressure

11 1.10 Vis_04 Applications – Computational Fluid Dynamics n Interface between immiscible fluids – e.g. oil / water n Loops and fingers arise when mixing starts – Rayleigh-Taylor instability n Simulated on ASCII Blue Pacific (Cook & Dimotakis, 2001) n Interface visualized using a density isosurface

12 1.11 Vis_04 Applications - Molecular Modelling n 2D potential energy function – molecule inside a zeolite channel n Displayed as coloured surface (left) – part also displayed using contour plot (right)

13 1.12 Vis_04 Applications - Molecular Modelling n 3D potential energy function – three atoms in a box n Displayed as isosurface (left) – interactive probe also shows how potential varies between two points (right)

14 1.13 Vis_04 Visualization BC n Imagination or visualization, and in particular the use of diagrams, has a crucial part to play in scientific investigation. – Rene Descartes, 1637 n 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)

15 1.14 Vis_04 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

16 1.15 Vis_04 The First Business Graphics

17 1.16 Vis_04 The First Contour Map

18 1.17 Vis_04 Visual Thinkers n Many of the great scientists were good at visual thinking: – Leonardo da Vinci – James Clerk Maxwell – Michael Faraday – Albert Einstein n This was often at the expense of verbal skills n Tom West : In the Minds Eye – See also edu/twest/maxwell_visual.html Maxwells clay model now in New Cavendish Laboratory, Cambridge (picture by Tom West)

19 1.18 Vis_04 Early Computer Visualization visualization n From early days of computing, scientists have carried out numerical simulation - and looked to visualization to help understand the results. n Visualization systems have evolved in four different styles - all still in use today (so not really history!)

20 1.19 Vis_04 Subprogram Libraries n 1960 onwards n Libraries of subprograms to draw graphs, contour plots … n Scientists include calls to library routines from within their own code n Leading examples from era were: – GHOST (UKAEA Culham) – NAG Graphics Library NAG Graphics :

21 1.20 Vis_04 Subprogram Libraries n This style continues today – NAG Graphics Library still available – Vtk C++ classes provide modern version of this style n Great flexibility – but need to program n Application Programming Interface Vtk :

22 1.21 Vis_04 Interactive Packages n From late 1970 onwards n Menu-driven packages allowing data to be visualized without need to write programs n Example: – gnuplot n Less flexible, but no programming! gnuplot

23 1.22 Vis_04 Interactive Packages n Matlab is a powerful system for computation and visualization – Has its own C-like language

24 1.23 Vis_04 Visualization Today n Recent surge of interest in visualization was sparked by an NSF report: Visualization in Scientific Computing – McCormick, de Fanti and Brown n Argued that investment in high performance computing in US was wasted unless there was corresponding investment in visualization n This motivated a third style of visualization system...

25 1.24 Vis_04 Visual Programming Systems n From late 1980s onwards n Visualization seen as a sequence of simple processing steps: eg contouring – read in data – create contour lines – draw contour lines n Systems provide modules implementing simple steps in a visualization pipeline n Scientist uses visual programming to connect modules together

26 1.25 Vis_04 Visual Programming - IRIS Explorer

27 1.26 Vis_04 Visual Programming Systems n Visual programming allows easy experimentation which is what one needs in visualization n Examples are: – IRIS Explorer – AVS – OpenDX (grown from IBM Visualization Data Explorer)

28 1.27 Vis_04 Service-based Visualization n The Internet era has introduced a fourth style of system – where a visualization service is delivered over the internet using Web technologies n Client-side with Java applets….

29 1.28 Vis_04 Service-based Visualization n … or server side n Here a form on a web page is used to make a visualization request n Processed by a visualization system on server and returned to client as VRML IRIS Explorer SerVis

30 1.29 Vis_04 The Four Phases of Visualization Systems n These four phases correlate with four phases in computing generally n Subprogram libraries – begun in era of batch computing n Interactive packages – begun in era of interactive computing, with terminals connected to host n Visual programming systems – begun in era of workstation computing, with graphical user interfaces n Service-based visualization – begun in era of internet computing

31 1.30 Vis_04 Information Visualization n 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

32 1.31 Vis_04 Outline of the Course n Lectures – Monday 10 (Parkinson-B9) ; Friday 9 (LT11) n Practical sessions using gnuplot, IRIS Explorer and xmdvtool under Linux n Background study

33 1.32 Vis_04 Outline of Lecture Course Data Visualization - I n Introduction and historical view n Fundamental concepts n 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

34 1.33 Vis_04 Outline of Lecture Course Data Visualization - II n Publication of visualization – VRML for 3D web presentation n Visualization Systems n Computational steering – linking simulation and visualization – Grid computing and visualization n Collaborative Visualization – Group working on the Internet … this will complete the programme for CFD students … but DMS students continue

35 1.34 Vis_04 Outline of Lecture Course: Data Visualization - III n Web-based visualization – using the Web as a distributed computing environment n Information Visualization – how to interpret large quantities of data using visualization – multivariate data

36 1.35 Vis_04 Practical Work n For DMS and CFD students - use of IRIS Explorer – state of art visualization system – Linux pcs – practical sessions n For DMS students – xmdvtool (multivariate data) n Publication using the World Wide Web n Assessment – assignments to visualize datasets n Experience of other systems – gnuplot

37 1.36 Vis_04 Background Study n Reading – mainly recent papers n World Wide Web – IRIS Explorer training materials – generally... a source of up-to-date information and examples

38 1.37 Vis_04 Books n The Visualization Toolkit (3 rd edition) – W Shroeder, K Martin, W Lorensen – Kitware Inc n Introduction to Volume Rendering – B. Lichtenbelt et al - Prentice Hall (1998) n Information Visualization – R. Spence – Addison-Wesley (2001) n Scientific Visualization Tech & Applns – K W Brodlie et al – Springer Verlag (1992)

39 1.38 Vis_04 Objectives n To be aware of the value of visualization to gain insight into both numeric data (from science, engineering and medicine for example) … n … and also non-numeric information (such as networks and documents) n To understand the fundamental techniques for data visualization n To be skilled in the use of a state of art visualization system DMS CFD

40 1.39 Vis_04 Keeping in Touch n – n Newsgroup for my postings: – local.modules.vis n Newsgroup for your postings: – n World Wide Web –

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