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Automatic Typographic Maps

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Slides from IEEE VisWeek 2012 presented by Shehzad Afzal. Automatic Typographic Maps use text to visualize geospatial data.

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Automatic Typographic Maps

  1. 1. Spatial Text Visualization Using Automatic Typographic MapsShehzad Afzal*, Ross Maciejewski†, Yun Jang‡, Niklas Elmqvist*, David S. Ebert* Purdue University*, Arizona State University†, Sejong University in Seoul ‡
  2. 2. MotivationAxisMaps.com 2
  3. 3. Motivation • Typographic Map: Map made entirely of the geographical labels (i.e., “Type”) • Aesthetically pleasing • Exists only for handful of cities • Printed map sold from $30-$150’San Francisco AxisMaps.com 3
  4. 4. MotivationHow are these maps designed? • Manual text placement using Adobe Illustrator over an „OpenStreetMap‟ image • Text options are modified based on underlying spatial features • Process takes several weeks to complete one map• Focus of their current approach is ‘purely aesthetic’• Our work “Automates the Typographic Map Generation Process”• Potential of visualizing data using spatialized text 4 Image Courtesy: AxisMaps.com
  5. 5. Related Work• Maharik et al. (2011) introduced ‘calligrams’ (digital micrography images)• „TagMaps‟ by Yahoo: Word clouds on top of graphical features• ‘Wordle’ by Viegas et al (2009), ‘ManiWordle’ by Koh et al (2010) & ‘SparkClouds’ by Lee et al (2010) 5
  6. 6. System Overview TypographicOpen Street Map Visual Properties/ Map (OSM) File Style Sheet SVG Renderer OSM Parser Region GenerationData Cleaning/ Optimizations Filtering Path/Road SVG File SVG File GenerationBuild GraphicalObjects & Layers SVG Code Generation 6
  7. 7. System Overview Thema- TypographicOpen Street Map Visual Properties/ Spatial Statistical Map (OSM) File Style Sheet Dataset SVG Renderer OSM Parser Region GenerationData Cleaning/ Optimizations Filtering Path/Road SVG File SVG File GenerationBuild GraphicalObjects & Layers SVG Code 7 Generation
  8. 8. Data Model• Layers: Particular class of geographical objects • e.g., Highways, Primary roads, park etc. • Visual Attributes such as font size, color, weight etc.• Graphical Objects belong to exactly one layer • 1D paths(roads) or 2D paths(polygons)• Ordering Layers: • Layers are drawn in ascending order of priority 8
  9. 9. Data Model• Ordering Layers: • 1D Paths have higher priority than 2D Paths• Ordering Graphical Objects within Layers: • Horizontal Paths have higher priority than vertical paths 9
  10. 10. Optimizations• Divided lanes having the same label are merged together to form a single lane• Font size for polygonal areas adjusted according to the area 10
  11. 11. Limitations• Definitions of polygonal areas are not always consistent in OSM. e.g., Rivers & lakes boundaries• Segments of same road have different names or category and they often overlap• OSM data is not completely defined for some geographic regions 11
  12. 12. Paths as Text• Rendering Path using Text: • Fit Text to path and repeat it for the duration of path‟s length • Rotate characters to align with path normal • Path thickness is controlled by font size 12
  13. 13. Paths as Text• Visual Clutter - Path Overlap: Clutter from Label Overlap Character Mask Character Halo 13
  14. 14. Regions as TextBounding Box filled with Oriented Text Clipped Text using Region Path 14
  15. 15. Regions as TextAdjacent Regions: Vary the orientation of the lines in adjacent regions resulting in visual continuity between regions 15
  16. 16. Comparison with AxisMap OutputAxisMaps Map of San Francisco, CA Automatic Typographic Map of San Francisco, CA 16
  17. 17. Comparison with AxisMap OutputAxisMaps Map of San Francisco, CA Automatic Typographic Map of San Francisco, CA 17
  18. 18. Comparison with AxisMap OutputAxisMaps Map of San Francisco, CA Automatic Typographic Map of San Francisco, CA 18
  19. 19. Comparison with AxisMap OutputAxisMaps Map of San Francisco, CA Automatic Typographic Map of San Francisco, CA 19
  20. 20. Typographic Map - Seattle Visweek Venue Automatic Typographic Map – Seattle near VisWeek 2012 Venue 20
  21. 21. Typographic Map - Chicago Automatic Typographic Map – Chicago, IL 21
  22. 22. Thema-Typographic MapsThematic Maps: Geographic Maps where Geospatial variable is visually encoded on the mapThema-Typographic Maps: Modify Font attributes on per character level to convey the value of a statistical variable at each character‟s spatial locationFont Attributes: Typically Size, but color, intensity etc. 22
  23. 23. Thema-Typographic Maps Showing Crime Rate KDE Map for West Lafayette, IN Thema-Typographic Map showing Crime Activity Statistical variable visualized is Crime Rate 23
  24. 24. Thema-Typographic Maps in SVG• Scaling individual characters: Internally we need to calculate where characters end on a path in 2D Space. This helps in following ways: • Correct Lookup of Mapping Variable in Spatial Dataset • # of characters required to fill the path can be calculated • Stroke width of the background mask is now defined as an average of the minimum and maximum font sizeOther Applications: Traffic Intensity, Demographics, political data can be overlaid on a typographic map 24
  25. 25. Conclusions and Future Work• Automatic Generation of Typographic Maps for any Geographic Region within seconds• ‘Thema-Typographic Maps’: Combines Typographic Maps technique with spatial datasetsFuture Work: • Spatial data features as a means of visualizing data • Support Navigation, drilling down and changing map layout 25
  26. 26. Acknowledgements• AxisMaps for their helpful feedback/discussions and permission to use their Typographic Map image in our paper• This work was supported in part by the U.S. Department of Homeland Security‟s VACCINE Center under Award no. 103659 / 2009-ST-061-CI0001 and the Defense Threat Reduction Agency under Award no. HDTRA 1-10-1-0083 26
  27. 27. Thank you Spatial TextVisualization Using AutomaticTypographic Maps[Web Service Client]http://web.ics.purdue.edu/~safzal/typomaps.html Shehzad Afzal safzal@purdue.edu

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