Chapter 10: Data Display Table, Graphs, Maps, Visualizations

1. Chapter 10: Data DisplayTable, Graphs, Maps, Visualizations Book: An Introduction to Scientific Research Methods in Geography (Montello & Sutton) 2006 GEOG4020-Research MethodsInstructor: Paul C. Sutton University of Denver, Dept. of Geography Prepared by: Katie Williams February 9, 2010

2. Chapter 10 Overview • Principles of Data Display • Guidelines for Designing Displays • Tables • Graphs • Maps • New Trends in Scientific Visualization

3. Learning Objectives • Understand the best use and design alternatives for tables and graphs • Understand principles of good graphing • Understand the powers and pitfalls of maps • Explore how computer technologies are applied to display data in innovative and powerful ways

4. Data Display • Depict rather than describe data patterns • Aid in understanding & communicating data • Highlight and clarify relevant data properties • Purposes of Data Display: • Examine • Interpret • Communicate

5. Exploratory Data Analysis Correlation? • Evaluating how “well-behaved” the data is • What is the distribution of the data? • How homogenous is the data? • Does the data fit expected values? • Are there extremes (outliers)? • Are there impossible values? • Submersive, graphical, ad hoc approach

6. Communication of Data • Written and Oral • Articles, books, papers, talks, interviews, etc. • Archival • Viewed more frequently by more people • Relatively permanent records • Displays should be constructed more thoughtfully and thoroughly

7. Data Display • Improper Data Display: • Abstract concepts—often better explained with words • Small amount of data—in text explanation is sufficient • Non-data Display • Communicate information other than data • Equipment used • Material employed

8. Designing a Display • Goal: Effective Communication • Access the complex; not complicate the simple • Depict valid, relevant information clearly, accurately, and unambiguously • Aesthetics • Attractiveness draws people’s attention • But, communication should never be compromised for aesthetics

9. Tables • Table: organized lists, arrays, or matrices of data • Only minimum use of spatiality • Good choice to show data precisely and in detail • Round adequately • Two depictions: • Distribution Tables • Descriptive Index Tables

10. Table Types • Distribution Tables • Frequency, relative frequency, cumulative frequency, relative cumulative frequency • Contingency tables—show relationships between nominal variables or metric variables that can be grouped into discrete classes • Descriptive Index Tables • Central tendency, variability, relationship, etc. • Organized into rank or class

11. Graphs • Graph: pictorial representation of data • Effective for communicating general rather than precise patterns (especially useful with large datasets) • Three Dictums: • 1. Clearly and sufficiently label the graph and its parts • 2. Avoid uninformative and content-free marks • 3. Fill the graph space with data marks

12. Graph Styles • Distribution graphs: depict distribution of variables • Value of variable on x-axis (abscissa) • Frequency of occurrence on y-axis (ordinate) • Types of Distribution Graphs • Bar graph—discrete graph style • Histogram—bar graph with quantitative class bins • Circle diagram—nominal variable level • Line—continuous variables • Curve-fitting—statistical model fitted to data distribution

13. More Graph Styles • Relationship Graphs: depict the form and strength of relationship between pairs of variables • Types: • Scatterplot—plot of X,Y intersection of two variables • Ternary diagram—relationship among three variables • Small multiples—repeating graph showing change over time • Simulated 3D—graphing data in three dimensions

14. Maps • Maps: graphic displays that depict earth-referenced features and data • Quintessential geographic display • Reference Map—Depict earth features accurately and precisely • Significant features are large, stable, & relevant • Encoded in coordinate system • Thematic Maps—Special-purpose displays • Spatial distribution of thematic variables • Little earth-surface detail; “map graphs”

15. Map Issues • Any flat rendering of the earth’s surface will result in distortion • Projections are different methods to flatten the earth while minimizing distortion • Examples: Mercator, Sinusoidal (hundreds more) • Selectivity is required; one projection will not minimize distortion for the entire surface

16. More Map Issues • Generalization of level of detail • Simplification, selection, enhancement • Map Symbols • Iconic: closely resemble reality (e.g. spatial layout of earth) • Abstract: not representative of reality (e.g. contour lines, checkered patterns, words) • Feature representation • Color, symbols, classes, choropleth regions

17. Principles of Good Mapping • 1. Facilitate effective & efficient communication • 2. Choose relevant and high-quality data • 3. Show data clearly and truthfully • 4. Highlight the important & downplay less important • 5. Focus on the data, not decoration • 6. Make good choices for map symbols

18. New Trends in Scientific Visualization • Computer driven innovations • Thematic mapping • Computationally intensive analytics • Capacity for complex and prolific amounts of data • Great opportunities, but also great challenges

19. Exploratory Data Analysis Techniques • Information visualization • Geo-visualization—visualizing data against geographic background • Spatialization—simulated landscapes • Animations—dynamic displays of change over time • Augmented reality—digital displays over actual surroundings • Virtual reality—simulating places • Sonification—proposed sound, touch, & smell maps

20. Questions • When does it make most sense to use tables to display data? • What are some principles of good graphing and specific design guidelines that derive from them? • Selectivity, projection, generalization, and varying symbol abstractness are always involved in mapping. Why are they always involved and why are them potentially misleading to map viewers?