CS382:Unit-mashup

Data Visualization

Overview

The goal of this unit is to teach students to:

• Understand the goals of visualization.
• Know what the issues involved in visualization are.
• Be able to recognize and reason about the different types of visualization.
• Be introduced to a sampling of the tools used to visualize data.

Background Reading for Teachers and TAs

• web tool for non-programmers for making mashups
• chapter 1 of book on power of geo mashups
• Wikipedia page on Information Visualization
• Wikipedia page on Visualization
• "The Visual Display of Quanitative Information" by Edward Tufte
• "Visualizing Data" by William Cleveland

Reading Assignments for Students

• Needs to be created I think

Lecture Notes

• Introduction
  • At this point students have already created/worked with a couple models and created basic graphs to visualize them. Talk about how even with just the simple models created so far, understanding the data is hard without having a visual representation of it.
  • Visualization is a graphical representation of data for the purpose of allowing humans to understand aspects of the data.
    • Couple of illustrative but basic graphs as examples.
  • Tufte's aspects of visualization, just a run through (From "The Visual Display of Quanitative Information"):
    • Show the data.
    • Induce the viewer to think about the substance rather than about the methodology, graphic design, the technology of graphic production, or something else.
    • Avoid distorting what the data have to say.
    • Present many numbers in a small space.
    • Make large data sets coherent.
    • Encourage the eye to compare different pieces of data.
    • Reveal the data at several levels of detail, from broad overview to the fine structure.
    • Serve a reasonable clear purpose: description, exploration, tabulation, or decoration.
    • Be closely integrated with the statistical and verbal descriptions of a data set.
  • Show some more complex examples like the Napoleon one, an interesting mashup.
• Issues of visualization
  • Objective. There is always a goal or objective when visualizing by which one can judge effectiveness. In this class I don't think things like marketing should be mentioned but certainly the difference between using visualization to explore data and to explain data to others.
  • Data Selection. When given a set of data, often one wants to single in on a subset of that data to look at.
  • Psychology. Visualization is fundamentally about how humans perceive visual information so you have to think about the ways in which you want to take advantage of human psychology.
  • Systemization. While elaborate visualizations like the Napoleon one are very compelling, in Computer Science we are often more interested in visualizations that can be systematically generated.
• Go through a couple of examples of creating visualizations referring back to Tufte's list and the issues.
• Types of Visualizations (A sampling)
  • Tables
  • Graphs
  • Charts
  • Sparklines
  • Time Series
  • Data maps and mashups

Lab

Use online tools to generate tabular data from the U.S. Census and then use R to explore visualization.

• Use a web site for generating census tables and walked through generating a predetermined table.
• Load up R and generate simple pie charts and bar graphs using the predetermined table
• Use provided tools in R for generating other types of more complex graphs (e.g. Trellis plots), apply them to the data, and then explain the differences between them.
• Use the web site to come up with your own data sets and play around with generating different visualizations in R.
• Come up with 1 or 2 interesting examples and explain why you used the visualization you used and what you learned from the visualization.

Software

• R

Evaluation

CRS Questions

• Whats the best type of visualization for X set of data?
• XXX
• XXX

Quiz Questions

• XXX A question.

Visualizing Data - Metadata

XXX This section contains information about the goals of the unit and the approaches taken to meet them.

Scheduling

Doesn't matter.

Concepts and Techniques

XXX This is a placeholder for a list of items from the context page.

General Education Alignment

• Analytical Reasoning Requirement
  • Abstract Reasoning - From the [Catalog Description] Courses qualifying for credit in Abstract Reasoning typically share these characteristics:
    • They focus substantially on properties of classes of abstract models and operations that apply to them.
      • XXX Analysis of this unit's support or not for this item.
    • They provide experience in generalizing from specific instances to appropriate classes of abstract models.
      • XXX Analysis of this unit's support or not for this item.
    • They provide experience in solving concrete problems by a process of abstraction and manipulation at the abstract level. Typically this experience is provided by word problems which require students to formalize real-world problems in abstract terms, to solve them with techniques that apply at that abstract level, and to convert the solutions back into concrete results.
      • XXX Analysis of this unit's support or not for this item.
  • Quantitative Reasoning - From the [Catalog Description] General Education courses in Quantitative Reasoning foster students' abilities to generate, interpret and evaluate quantitative information. In particular, Quantitative Reasoning courses help students develop abilities in such areas as:
    • Using and interpreting formulas, graphs and tables.
      • XXX Analysis of this unit's support or not for this item.
    • Representing mathematical ideas symbolically, graphically, numerically and verbally.
      • XXX Analysis of this unit's support or not for this item.
    • Using mathematical and statistical ideas to solve problems in a variety of contexts.
      • XXX Analysis of this unit's support or not for this item.
    • Using simple models such as linear dependence, exponential growth or decay, or normal distribution.
      • XXX Analysis of this unit's support or not for this item.
    • Understanding basic statistical ideas such as averages, variability and probability.
      • XXX Analysis of this unit's support or not for this item.
    • Making estimates and checking the reasonableness of answers.
      • XXX Analysis of this unit's support or not for this item.
    • Recognizing the limitations of mathematical and statistical methods.
      • XXX Analysis of this unit's support or not for this item.
• Scientific Inquiry Requirement - From the [Catalog Description] Scientific inquiry:
  • Develops students' understanding of the natural world.
    • XXX Analysis of this unit's support or not for this item.
  • Strengthens students' knowledge of the scientific way of knowing — the use of systematic observation and experimentation to develop theories and test hypotheses.
    • XXX Analysis of this unit's support or not for this item.
  • Emphasizes and provides first-hand experience with both theoretical analysis and the collection of empirical data.
    • XXX Analysis of this unit's support or not for this item.

Scaffolded Learning

XXX Some prose.

Inquiry Based Learning

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