1. Book: An Introduction to Scientific Research Methods in Geography (Montello & Sutton) 2006 GEOG4020-Research Methods Instructor: Paul C. Sutton University of Denver, Dept. of Geography Prepared by: Katie Williams February 9, 2010

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

3. 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 3

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

5. 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 5

6. 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 6

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

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

9. 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 9

10. Distribution Tables Frequency, relative frequency, cumulative frequency, relative cumulative frequency Contingency tablesshow 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 10

11. 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 11

12. 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 graphdiscrete graph style Histogrambar graph with quantitative class bins Circle diagramnominal variable level Linecontinuous variables Curve-fittingstatistical model fitted to data distribution 12

13. Relationship Graphs: depict the form and strength of relationship between pairs of variables Types: Scatterplotplot of X,Y intersection of two variables Ternary diagramrelationship among three variables Small multiplesrepeating graph showing change over time Simulated 3Dgraphing data in three dimensions 13

14. 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 14

15. Any flat rendering of the earths 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 15

16. 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 16

17. 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 17

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

19. 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 19

20. 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? 20