Scientific Visualization University of Houston, Fall 2012

COSC 6344 Visualization

University of Houston, Fall 2015

Instructor: Guoning Chenchengu@cs.uh.edu

1Course InformationLocation: AH 302Time: 10am~11:30am Tu/ThOffice Hours: 11:30am~12:30pm Tu /Thor by appointmentOffice: PGH 566Course webpage: http://www2.cs.uh.edu/~chengu/Teaching/Fall2015/Visualization_fall2015.html Course InformationPrerequisites:Knowledge and experience in programming, especially C/C++ programming.Knowledge on linear algebra, calculus, geometry, numerical analysis.Experience on computer graphics and OpenGL (recommended)

Textbook: (recommended)Alexandru C. Telea, Data Visualization: Principles and Practice, A.K.Peters, 2008Charles D. Hansen and Chris R. Johnson, Visualization Handbook, Elsevier, 2004Introduction to Information Visualization. Riccardo Mazza, Springer, 2009Reading materials and course notes given in class or on course page.

Course InformationGrading: 6 assignments (50%) 1 mid-term exam (15%) 1 final project presentation (25%) course participation (10%)

Late Policy: Late assignments will be marked off 10% for each weekday that it is late. You can ask for a delay for one assignment for up to 5 weekdays.

Academic Dishonesty: Do you own work! No code copy!

4A Glimpse of the Schedule (tentative)TIMELINEMATERIAL COVEREDWEEK 1Class PreliminariesIntroduction History of visualization, Visualization pipeline, Data types and representationsWEEK 2Elementary plots (Assignment 1 out); OpenGL tutorial, skeleton code WEEK 3Visualization systems; Colors coding for scalar field visualization (Assignment2 out)WEEK 4Iso-surfacing; Direct volume rendering Ray casting (Assignment3 out)WEEK 5Direct volume rendering Splatting; Transfer function design (Assignment 4 out)WEEK 6Flow visualization introduction; Flow visualization techniques in 2D (arrow and color plots and streamlines);Streamline placement, Information theory frameworkWEEK 7Flow visualization techniques in 2D - texture-based (Assignment 5 out) ; Topology-based vector field visualization IWEEK 8Topology-based vector field visualization II; Final project topic reviewWEEK 9Non-topological feature-based flow visualization; 3D flow visualization (Assignment 6 out) (Final project proposal due)WEEK 10Mid-term exam (IEEE Visualization 2015)WEEK 11Tensor data application introduction and math; Geometric-based tensor visualizationWEEK 12Texture-based tensor field visualization; Glyph-based technique WEEK 13Information visualization graph and hierarchy data visualizationWEEK 14Information visualization high dimensional data visualization (Thanksgiving)WEEK 15Visual analytics, user study theoryWEEK 16Final project presentationsBackground

Data is generated everywhere and everyday

How to efficiently help data owners extract useful information (e.g., patterns and trends) and understand it?

Cognitive study has shown that human visual system is the most effective channel to transport information to the brain.Visual representation is one effective way to convey information

Leading to the introduction of visualization.History of VisualizationVisualization = rather old L. da Vinci (1452-1519)

Often an intuitive step: graphical illustration

Image source: http://www.leonardo-da-vinci-biography.com/leonardo-da-vinci-anatomy.htmlIn 1987the National Science Foundation (of the U.S.) started Visualization in scientific computing as a new discipline, and a panel of the ACM coined the term scientific visualization Scientific visualization, briefly defined: The use of computer graphics for the analysis and presentation of computed or measured scientific data.Oxford Engl. Dict., 1989to form a mental vision, image, or picture of (something not visible or present to the sight, or of an abstraction); to make visible to the mind or imagination

Visualization transforms data into images that effectively and accurately represent information about the data. Schroeder et al. The Visualization Toolkit, 2nd ed. 1998

What is Visualization?The Foundation of Modern Visualization?15In 1987the National Science Foundation (of the U.S.) started Visualization in scientific computing as a new discipline, and a panel of the ACM coined the term scientific visualization Scientific visualization, briefly defined: The use of computer graphics for the analysis and presentation of computed or measured scientific data.Oxford Engl. Dict., 1989to form a mental vision, image, or picture of (something not visible or present to the sight, or of an abstraction); to make visible to the mind or imagination

Visualization transforms data into images that effectively and accurately represent information about the data. Schroeder et al. The Visualization Toolkit, 2nd ed. 1998

What is Visualization?Means to enable the insights into DataThe Foundation of Modern Visualization?16History of Modern VisualizationVisualization = being its own discipline for more than 25 yearsFirst dedicated conferences: 1990Conferences:IEEE Visualization (SciVis, InfoVis, VAST)EuroVisPacificVisOthersJournals:IEEE Transactions on Visualization and Computer GraphicsComputer Graphics ForumOthers

17Why is Visualization Important?18To effectively convey information to data stakeholdersWhy is Visualization Important?

19To effectively convey information to data stakeholdersTo make invisible phenomena visibleWhy is Visualization Important?Astrophysicssource: VACET

Combustionsource: VACET

Aerodynamics around missiles [Kelly et al. Vis06]

Automobile design [Chen et al. Vis11]20Education

Why is Visualization Important?21Education

Why is Visualization Important?

22Education

Why is Visualization Important?

23Education

Understand mathematical concepts and physical phenomena that are invisible

Why is Visualization Important?

Source: SuperStockRecommended site: http://www.pbs.org/wgbh/nova/

Fusion physics24Three types of goals for visualization to presenteverything known about the data,Vis. used for Communication of Results

What Does Visualization Do?25Three types of goals for visualization to presenteverything known about the data,Vis. used for Communication of Results to analyzeThere are hypotheses,Vis. used for Verification or FalsificationWhat Does Visualization Do?26Three types of goals for visualization to presenteverything known about the data,Vis. used for Communication of Results to analyzeThere are hypotheses,Vis. used for Verification or Falsification to exploreNothing is known,Vis. used for data exploration

What Does Visualization Do?27Evolution of Visualization ResearchFrom direct visualization to derived information visualization.

From simple data forms to more complex forms.

From represent the data with fidelity to reveal new findings.

From scientific visualization to information visualization, bio-visualization, geographical data visualization, and beyond.SciVis vs. InfoVisScientific visualization is mostly concerned with:(physical) spatial or spatio-temporal data (dimension < 4)Representation: spatial discretization (or samples)Examples: temperature/pressure fields, potential fields, wind fields, etc.

Information visualization focuses on:high-dimensional, abstract data (no geometric meaning)discrete data in the natureExamples: financial data, logs and records, tweeter posts, family trees or organization structure, computer/social networks, survey data, etc.

Age of Big Data

We are not concerned with the big data issue in this course but rather building the foundation for eventually addressing the big data challenges!!!Goals and TopicsGoals of this CourseKnow the representative methods and standards of classic visualization problems

Familiar with classical techniques for the visualizations of various data types

Able to develop the customized visualization techniques and systems for the practical and research needsWhat will be covered?Colors, plotsScalar field visualizationVector field visualizationTensor field visualizationInformation visualization (graphs, high-dimensional, etc.)Hop topics in visualization

Will make use of a lot of branches in mathematicsCalculus, trigonometry, linear algebra, discrete math, differential geometry, topology, dynamical systems, numerical algebra, etc

Will also need knowledge in from the following sub-field computer scienceAlgorithms, data structures, graphics, human-computer interaction, imaging, etc.

It will be a plus+ to have the following backgroundArt and design, Psychophysics, scientific computingTopics to Be Covered in this Course34Preview of TopicsColor theory and visual representation

Which is brighter?HSV Color WheelPreview of TopicsPlots

Preview of TopicsScalar field visualization 2D

is given by a function f(x1,...,xn):RnR with n independent variables xi

Examples include high fields, temperatures, pressures, potential energy, eigenvalues,

Source: V_Simhttp://www-drfmc.cea.fr/L_Sim/V_Sim/Preview of TopicsScalar field visualization 3D

Zebra fish head (image by Fluorender)

The impact of the ball entering the porous solid from the left

Volume Rendering

Iso-surfacingVisualizations of magnetically unstable cylindrical Couette flow. This image shows the enstrophy and regions of high hydrodynamic dissipation, and was created by Cristina Siegerist, LBNL, in a collaborative effort between VACET, the NERSC Analytics program (www.nersc.gov)Simulations by F. Cattaneo(1,2), P. Fischer(1) & A. Obabko(2)(1) Argonne National Laboratory(2) University of Chicagoas part of DOE's INCITE program. 38Preview of TopicsScalar field visualization IIITopology

The impact of the ball entering the porous solid from the leftA single timestep of a dataset of a simulated Raleigh-Taylor instability simulating themixing of two fluids. This timestep has a resolution of 115211521000 and is an earlytimestep of the simulation. The data is noisy, therefore we perform a 5% persistence simplificationto remove excess features. We compute the complex for the entire dataset, andthe inset shows a small subsection of the data with selected nodes and arcs of the complex.Minima and maxima (blue and red spheres) and their saddle connections trace out thebubble structure in the data. The maxima represent isolated pockets of high-density fluidthat have crossed the boundary between the two fluids. The structural complexity is overwhelming,but our prototype allows interactive exploration and visualization, and selectiveinclusion/omission of user-specified components of the MS complex39Preview of TopicsVector field visualization I Hedge-HodgeParticle tracingIntegration-based

Hurricane Isabel

Preview of TopicsVector field visualization IITexture-based

(Bruno Jobard, Gordon Erlebacher, and M. Yousuff Hussaini)

Preview of TopicsVector field visualization IIIFeature-based

Preview of TopicsTensor field visualization

Second order tensorPreview of TopicsTensor field visualization

Texture-basedGlyph-basedGeometry-basedPreview of TopicsInformation visualization

Text visualization http://willscullypower.wordpress.com/Graph visualization http://infosthetics.com

Tree/hierarchy data visualizationhttp://infosthetics.comhttp://datamining.typepad.com

High-dimensional data visualizationhttp://eagereyes.orgPreview of TopicsVisualization systemsGeneral purpose (open source)ParaviewVisItSCIRun

Preview of TopicsRecent hot topics in visualization Multi-field visualizationUncertainty visualizationBig data visualizationNovel applications

Scientific visualization (SciVis):Data typically come from natural sciences and life sciencesData are usually numeric and defined over a space with geometric structures

Information visualization (InfoVis):Data are typically abstractData are usually not numeric and not necessarily related to a spatial domain

Software visualization, bio-visualization, geographical data visualization, etc.

Visual analyticsBranches of Visualization48