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Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1
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Page 1: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Introduction to Data Visualization

CS 4390/5390 Fall 2014Shirley Moore, Instructor

svmoore.pbworks.com

August 25, 2014

Page 2: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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The Industrial Revolution of Big Data (Joe Hellerstein, 2008)

Image credit: http://www.uberb2b.com/b4b-presents-the-first-industry-4-0-mini-conference/

Page 3: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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How much data is out there?

Page 4: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Image credit: http://www.opentracker.net/solutions/big-data-analytics

Page 5: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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The ability to take data – to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it – that’s going to be a hugely important skill in the next decades…

Because now we really do have essentially free and ubiquitous data. So the complementary scarce factor is the ability to understand that data and extract value from it.

Hal Varian, Google’s Chief Economist The McKinsey Quarterly, Jan 2009

Page 6: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Data-Intensive ScienceImage credit: Synergistic Challenges in Data-Intensive Science and Exascale Computing, DOE

ASCAC Data Subcommittee Report, March 2013, available on science.energy.gov

Page 7: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Computing with Big Data

Slide courtesy of Kathy Yelick

Page 8: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Sources of Big Scientific Data

Page 9: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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How much scientific data?

• ATLAS and CMS experiments at the Large Hadron Collider enerate data at rates of petabytes per second running round the clock for a large fraction of the year.

• Climate simulations generating several petabytes of data per year.

• Computational biology and genomics producing extreme volumes of data for – biophysical simulations of cellular environments– cracking the code of the genome across species– correlating observational ecology and models of population

dynamics– reverse engineering the brain

Page 10: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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CERN Large Hadron ColliderImage credit: wiki.creativecommons.org/Case_Studies/CERN

Page 11: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Higgs Boson Particle

Simulated data modeled forthe CMS particle detectoron the Large Hadron Collider(LHC) at CERN.

Here, following a collision of two protons, a Higgs boson is produced that decays intotwo jets of hadrons and twoelectrons.

Image credit:http://www.tacc.utexas.edu/news/feature-stories/2011/testing-technicolor-physics

Page 12: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Data Collection Growth

Page 13: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Why Use Visualization?

1. Cognition is limited.2. Memory is limited.

Page 14: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Selective Attention

• The Door Studyhttps://www.youtube.com/watch?v=FWSxSQsspiQ• The Invisible Gorillawww.invisiblegorilla.com • Mueller and Krummenacher,

“Visual search and selective attention”, Visual Cognition 14: 389-410, 2006.

Page 15: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Working Memory Capacity

• Test your working memory capacity– http://www.gocognitive.net/demo/working-memory-capacity

• The Magical Number Seven Plus or Minus Two– George Miller,

“The magical number seven, plus or minus two: Some limits on our capacity for processing information”, The Psychological Review 63: 81-97, 1956.

Page 16: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Visualization Works By

• Using perception to point out interesting things

• Using pictures to enhance working memory

Page 17: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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How Many Letter V’s

MTHIVLWYADCEQGHKILKMTWYNARDCAIREQGHLVKMFPSTWYARNGFPSVCEILQGKMFPSNDRCEQDIFPSGHLMFHKMVPSTWYACEQTWRN

Page 18: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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How Many Letter V’s

MTHIVLWYADCEQGHKILKMTWYNARDCAIREQGHLVKMFPSTWYARNGFPSVCEILQGKMFPSNDRCEQDIFPSGHLMFHKMVPSTWYACEQTWRN

Page 19: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Which Number Appears Most Often?

15 19 60 33 11 75 57 34 79 58 51 9273 22 13 71 60 22 72 10 68 73 18 5565 46 29

Page 20: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Which Number Appears Most Often? (cont.)

60 73 22 46 92 97 10 58 4657 17 83 26 99 33 88 92 60 91 29 57 96 12 47

Page 21: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Class Exercise 1

• Can you devise a visualization that makes this task easier?

Page 22: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Definition of Visualization

• http://www.merriam-webster.com/dictionary/visualization 1. formation of mental visual images2. the act or process of interpreting in visual terms or of

putting into visible form

“Computer-based visualization systems provide visual representations of datasets intended to help people carry out some task more effectively.” --Tamara Munzner

Page 23: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Class Exercise 2

• How does triglyceride level vary by age and income level?

TRIGLYCERIDE LEVEL

• Can you devise a visualization that enables seeing the answer at a glance?

Males Females

Income Under 65 65 or Over Under 65 65 or Over

0-$24,999 250 200 275 450

$25,000+ 320 150 400 200

Page 24: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Purposes of Visualization

• Answer questions• Generate hypotheses• Make decisions• See data in context• Expand memory• Support computational analysis• Find patterns• Tell a story• Inspire

Page 25: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Visualization Critique

• What is the purpose of the visualization?• What techniques are used? • Are the techniques used effectively?• Does the visualization focus our attention on

important aspects of the data?• Does the visualization accomplish its purpose?• How could the visualization be improved?

Page 26: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Exemplar

• Hans Rosling TED Talk– https://www.youtube.com/watch?v=usdJgEwMinM

• Homework assignment #1– Write a critique of a visualization from this video– Bring to class to share on Wednesday, Sept 3

Page 27: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Course Logistics

• Course website: http://svmoore.pbworks.com/ (click on Data Visualization)• Instructor: Shirley Moore– Office: CCSB 3.0422– Office hours: MW 3:00-4:00pm, others by appointment

• Teaching assistant: Henry Moncada– Office: CCSB 3.1202H– Office hours:

Page 28: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Grading

• Grades will be posted on Blackboard• Approximate breakdown– 35% homework and lab assignments– 15% class preparation and participation– 25% course exam– 25% project

Page 29: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Textbooks

• Visualization Design and Analysis: Abstractions, Principles, and Methods by Tamara Munzner, AK Peters 2014 (to appear). Draft available at http://www.cs.ubc.ca/~tmm/courses/533/book/vispmp-draft.pdf

• Visual Thinking for Design by Colin Ware, Morgan Kaufman, 2008.

• Visualizing Data: Exploring and Explaining Data with the Processing Environment, by Ben Fry, O’Reilly, 2007.

• The ParaView Tutorial, Version 4.1, by Kenneth Moreland, Sandia National Lab, 2013. http://www.paraview.org/Wiki/The_ParaView_Tutorial

Page 30: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Software

• Processing– processing.org– Programming language and development environment for

information visualization applications– Download and install on your laptop

• ParaView– www.paraview.org– Open-source data analysis and visualization application– Developed to analyze extremely large datasets using

distributed computing resources• Others to be determined

Page 31: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Course Project

• Implementation of a visualization for a significant dataset– You may choose your own dataset or use one

provided by the instructor• Report describing background and design

decisions• Presentation during last week of class or final

exam period (or special poster/demo session?)• Work individually or in teams of up to three

Page 32: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Connections to Other Courses

• CPS 5310 Simulation and Modeling• CS 5334 Parallel & Concurrent Programming• CS 4342 Database Management• CS 4390/5339 Web-based Systems• CS 4317/5317 Human-Computer Interaction• CS 3370 Computer Graphics• Graphic Design • Psychology

Page 33: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Why Take This Course

• Build more complex and insightful visualizations than your current skills and tools allow

• Learn how to effectively communication information about complex data to others

• Ask questions about, explore, and understand data for your job or research

• The set of people who need to be able to visualize data is growing beyond experts in visualization.

Page 34: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Opportunity: Vizzies Visualization Challenge

• http://www.nsf.gov/news/special_reports/scivis/• Sponsored by National Science Foundation and Popular Science• Deadline September 30, 2014• Cash prizes• Categories

– Photography– Illustration– Posters and graphics– Games and apps– Videos

• Extra credit and/or use as basis for project for this class

Page 35: Introduction to Data Visualization CS 4390/5390 Fall 2014 Shirley Moore, Instructor svmoore.pbworks.com August 25, 2014 1.

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Preparation for Next Class

• Read Munzner Chapter 1• Readings on Visualization Techniques• Download Processing software and install on

your computer (see me if you don’t have a computer you can use for this)– Will start using Processing second week of class– Will also get Processing installed on lab computers

• Start on Homework Assignment 1


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