CIS 467/602-01: Data Visualization

Transcription

1 CIS 467/602-01: Data Visualization Maps Dr. David Koop

2 Assignment 3 ~dkoop/cis467/assignment3.html Networks and Maps Little East Women's Basketball data Network of games with forcedirected layout Mapping all schools Mapping UMassD games (602-01) Tournament Partition Map Sample Solution Posted CORS Issue Fixed Due Wednesday, April 1 2

3 Geometry Shape information that is not determined by an attribute Data is often derived from realworld positions - Medical scans - Earth boundaries We use the geometry because we are familiar with the existing layout Geometry (Spatial) Position [Munzner (ill. Maguire), 2014] Tables Networks & Trees Fields Geometry Clusters, Sets, Lists Items Items (nodes) Grids Items Items Attributes Links Positions Positions Attributes Attributes 3

4 Geographic Data Spatial data Cartography: the science of drawing maps - Lots of history and well-established procedures - May also have non-spatial attributes associated with items - Thematic cartography: integrate these non-spatial attributes (e.g. population, life expectancy, etc.) Goals: - Respect cartographic principles - Understand data with geographic references with the visualization principles 4

5 Search Tasks Location known Location unknown Target known Lookup Locate Target unknown Browse Explore [Munzner (ill. Maguire), 2014] 5

6 Lookup 6

7 Route Maps Rendering Effective Route Maps: Improving Usability Through Generalization Maneesh Agrawala Chris Stolte Stanford University Figure 1: Three route maps for the same route rendered by (left) a standard computer-mapping system, (middle) a person, and (right) LineDrive, our route map rendering system. The standard computer-generated map is difficult to use because its large, constant scale factor causes the short roads to vanish and because it is cluttered with extraneous details such as city names, parks, and roads that are far away from the route. Both the handdrawn map and the LineDrive map exaggerate the lengths of the short roads to ensure their visibility while maintainaing a simple, clean design that emphasizes the most essential information for following the route. Note that the handdrawn map was created without seeing either the standard computer-generated map or the LineDrive map. (Handdrawn map courtesy of Mia Trachinger.) Abstract Route maps, which depict a path from one location to another, have emerged as one of the most popular applications on the Web. Current computer-generated route maps, however, are often very difficlarity of the map and to emphasize the most important information [16, 21]. This type of generalization, performed either consciously or sub-consciously, is prevalent both in quickly sketched maps and in professionally designed route maps that appear in print advertisements, invitations, and subway schedules [25, 13]. [Agrawala & Stolte, 2001] 7

8 Locate 8

9 Adding Data Discrete: a value is associated with a specific position - Size - Color Hue - Charts Continuous: each spatial position has a value (fields) - Heatmap - Isolines 9

10 Discrete Categorical Attribute: Shape [Acadia NP, National Park Service] 10

11 Discrete Categorical Attribute: Shape [Acadia NP, National Park Service] 10

12 Discrete Quantitative Attribute: Color Saturation 11

13 Discrete Quantitative Attribute: Size 12

14 Discrete Quantitative Attributes: Bar Chart [ 13

15 Continuous Quantitative Attribute: Color Hue [ 14

16 Time as the attribute [ 15

17 Isolines [USGS via Wikipedia] 16

18 Isolines Scalar fields: - value at each location - sampled on grids Isolines use derived data from the scalar field - Interpret field as representing continuous values - Derived data is geometry: new lines that represent the same attribute value Scalability: dozens of levels Other encodings? 17

19 Choropleths 18

20 Area Marks and Color Hue & Saturation 19

21 Map Projection [P. Foresman, Wikimedia] 20

22 Flattening the Sphere? [USGS Map Projections] 21

23 Lambert Conformal Conic Projection [USGS Map Projections] 22

24 Map Projections [ 23

25 Midterm Fairly Difficult CIS467: Possible: 100, Median: 70, Mean: 66.85, Std. Dev.: CIS602: Possible: 115, Median: 69, Mean: 71.04, Std. Dev: Specific Questions: - D3 Update/Enter/Exit - Adding Extra Attribute: Separability - Why Bar/Line Chart? Quantitative & Categorical - Color: Hue or Saturation or Luminance? 24