GAFFTA Visualizing and Mapping Data, Day Two

Transcript

1. Visualizing and Mapping Data Michal Migurski & Shawn Allen, Stamen Design GAFFTA February 2012 http://sta.mn/zr3
2. Day Two: Data
3. The Sources of Data
4. http://sta.mn/b84 Passive Data IBM’s Data Baby advertising campaign
5. Data is Choices “Accepting data shaped by someone else’s choices is a tacit acceptance of their view of the world, their notion of what is interesting or important or valid. … if we are going to work intelligently with data we must remember that it can always be constructed some other way.” —Mitchell Whitelaw http://sta.mn/gb
6. http://sta.mn/vxc Illustrating a Problem Open Source Spying, Lisa Strausfeld
7. …or showing a mess?
8. Problems vs. Messes “Systems above a certain level of complexity, and life is definitely one of them, do not present us with problems. They present us with messes. Problems have solutions, but messes can only be managed.” —Donella Meadows by way of Adam Greenfield
9. “There is no such thing as raw data” —Laura Kurgan, Columbia SIDL
11. Francis Galton, 1863 http://sta.mn/ww7 Data wasn’t always easy
12. Tagging Pacific Predators, http://topp.org
13. Social Data
14. http://sta.mn/m3r
15. http://sta.mn/gxb
17. http://sta.mn/9bm
18. http://weeplaces.com
19. http://popvssoda.com Proprietary Research
20. http://popvssoda.com “soda” Proprietary Research
21. http://popvssoda.com “soda” “soda” Proprietary Research
22. http://popvssoda.com “soda” “pop” “soda” Proprietary Research
23. http://popvssoda.com “soda” “pop” “coke” “soda” Proprietary Research
24. Official Data
27. http://sta.mn/kjb
28. http://sta.mn/y8v ← Chinatown
29. http://sta.mn/y8v
30. “The Data Is The Public Good”
31. “The Data Is The Public Good”
32. http://sta.mn/mz2
33. Follow along… http://sta.mn/zr3
34. Useful Data Formats Formats you’re likely to encounter when dealing with data on the web
35. Plain text, CSV
37. Comma/Tab Separated Values • Ubiquitous format • Used with every spreadsheet application, ever • Super easy to parse (though you often have to do this yourself, which is a hassle) • Text editors are often completely sufficient for preparing and handling this form of data
38. Shapefiles
40. Shapefiles • Store vectors: points, lines, polygons • Also store data attributes for vectors, like a spreadsheet • Once a proprietary format, now common language for most GIS software • QGIS is a useful-though-annoying free program for dealing with shapefiles
41. Shape “files” are four files • .shp for geometry • .dbf for data, like a spreadsheet • .prj for projection (sometimes) • .shx for geometry index
42. JSON
43. Geo + JSON = GeoJSON { "type": "FeatureCollection", "features": [ { "type": "Feature", "properties": { "STATEFP10": "06", "ZCTA5CE10": "94131", "ALAND10": 5386048.000000, "AWATER10": 50550.000000 }, "geometry": { "type": "Polygon", "coordinates": [ [[-122.441886, 37.753365], [-122.442525, 37.752380], ..., [-122.441289, 37.755606]] ] } }, ...
44. JSON (“Object Notation”) • Minimal syntax, tiny language. • Valid Javascript, valid Python = copy/paste • Used by essentially all web services, replacing XML over recent years • QGIS can convert shapefiles to GeoJSON for use in browser applications
45. Tweets
46. Raffi Krikorian’s Map of a Tweet, http://sta.mn/hq3
47. Try Me https://stream.twitter.com/1/statuses/sample.json