1 i247: Information Visualization and Presentation Marti Hearst Data Types and Graph Types

2 Outline The Roles and Stages of Visualization (briefly) Data Models and Types of Data Which Kinds of Graphs for Which Types of Data? Class Exercise

3 The Roles and Stages of Visualization

4 What Visualization Can Do (Ware) Allows comprehension of huge amounts of data. Allows perception of emergent properties Enables problems with the data to stand out Facilitates understanding at both large and small scales; patterns linking local features Facilitates hypothesis formation.

5 What Visualization Can Do (Tufte ’83) Show the data Induce to viewer to think about the data 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 overview to fine structure Serve a clear purpose: –Description, exploration, tabulation, or decoration Be closely integrated with the statistical and verbal descriptions of a data set.

6 Stages of Visualization (Ware) Collection and storage of data Preprocessing to transform data into something understandable Hardware and graphics algorithms for producing an image on the screen Human perceptual and cognitive system. (I think he’s missing a stage … Design of the visualization.)

7 Put it Into Questions What are our goals? What questions do we want to answer? What kind of data might we collect? How might we convey the information associated with this data?

8 Visualization Components Techniques Graphs & plots Maps Trees & Networks Volumes & Vectors … Design Process Iterative design Design studies Evaluation Design Principles Visual display Interaction Frameworks Data types Tasks Human Abilities Visual perception Cognition Motor skills Imply Constrain design Inform design From Melanie Tory

9 Data Models and Types of Data

10 Adapted from Stone & Zellweger Basic Elements of a Data Model A data model represents some aspect of the world Data models consist of these basic elements: –objects –values (also called attributes) –relations

11 Adapted from Stone & Zellweger Basic Elements: Objects Objects are items of interest –people, plants, cars, films, etc… Objects allow you to define and reason about a domain –ecosystem: ponds, streams, woodlands, mountains, plants, animals, etc.

12 Adapted from Stone & Zellweger Basic Elements: Values Values (or attributes) are properties of objects Two major types –quantitative –categorical Appropriate visualizations often depend upon the type of the data values

13 Adapted from Stone & Zellweger Basic Elements: Relations Relations relate two or more objects –leaves are part of a plant –a department consists of employees Ecosystem –connections between streams and lakes –predator/prey network of what eats what –…

14 Types of Data (Ware) Entities Relationships Attributes of Entities or Relationships –Nominal / Ordinal / Interval / Ratio (Stevens ’46) –Categorical / Integer / Real Operations Considered as Data –Mathematical –Merging lists –Transforming data, etc. –Metadata (derived data)

15 Adapted from Stone & Zellweger Types of Data (Few) Quantitative (allows arithmetic operations) Categorical (group, identify & organize; no arithmetic) Nominal Ordinal Interval Hierarchical

16 Adapted from Stone & Zellweger Types of Data Quantitative (allows arithmetic operations) -123, 29.56, … Categorical (group, identify & organize; no arithmetic) Nominal (name only, no ordering) Direction: North, East, South, West Ordinal (ordered, not measurable) First, second, third … Hot, warm, cold Interval (starts out as quantitative, but is made categorical by subdividing into ordered ranges) Time: Jan, Feb, Mar 0-999, , , , … Hierarchical (successive inclusion) Region: Continent > Country > State > City Animal > Mammal > Horse

17 Which Types of Graphs for Which Kinds of Data?

18 From Few, "Quantitative vs. Categorical Data: A Difference Worth Knowing", DM Review Magazine, April 2005 Quantitative Against Categorical

19 From Few, "Quantitative vs. Categorical Data: A Difference Worth Knowing", DM Review Magazine, April 2005 Quantitative against Quantitative

20 Questions to ask when creating a graph Is a graph needed? –Yes, if illustrating relationships among measurements What information is being conveyed? –What is most important? –Start by writing a title

21 Questions to ask when creating a graph What data is needed to answer specific questions? –Overview? Relationships? –Grice’s maxims combine relevant information together don’t show extraneous information Who is your audience?

22 What Format to Use? Bertin has a notion of efficiency Tufte says “show the data” Let’s start with familiar graph types –line graphs –bar charts –scatter plots –layer graphs When to use each?

23 Anatomy of a Graph (Kosslyn 89) Framework –sets the stage –kinds of measurements, scale,... Content –marks –point symbols, lines, areas, bars, … Labels –title, axes, tic marks,...

24 When to use which type? Line graph –x-axis requires quantitative variable –differences among contiguous values –familiar/conventional ordering among ordinals Bar graph –comparison of relative point values Scatter plot –convey overall impression of relationship between two variables

25 What to put on the x axis? Independent vs. Dependent variables –we often measure one quantitative variable against another –the value of one changes in relation to the other –the dependent variable changes relative to the independent one –the independent variable acts as a “measuring stick” Independent usually goes on the x (horizontal) axis

26 Independent vs. Dependent Independent vs. Dependent variables –heat in degrees against time –sales against season –tax revenue against city What happens when there is more than one independent variable? –Choose one for the x axis, and another as a variation in the mark (color, shape)

27 Few on How to Show Information The best way to show a single value? –Use a textual representation. –Why? How to draw attention to a number?

28 Few on How to Show Information What are tables good for? –Data lookup –Hierarchical relationships

29 Class Exercise

30 How to Combine Data Types? Class Exercise: –Using data about autos from the 70’s –Each person get a column of data First, identify the data type Then, stand up Then, repeat the following several times: –Walk up to someone else. If they have a different column than you do, discuss whether and how you should plot your two columns. »If yes, what question are you answering? »If no, why not? Then, repeat this, but with groups of three people.