TIGER/Line Data in the Cloud - Tom MacWright
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The document summarizes making open TIGER/Line data from the US Census Bureau useful in the cloud. It details that over 125GB of TIGER/Line road and geographic boundary data took over 12 hours to download, unzip, and upload to Amazon's cloud. Once in the cloud, a mapping server could be booted up in a minute and the TIGER data connected in two minutes, providing open-source mapping capabilities for over 14,000 school districts and areas without restrictive licenses. Cloud computing allows for scalability while open-source mapping software enables grassroots involvement in projects like OpenStreetMap.
TIGER/Line Data in the Cloud - Tom MacWright
- 1. TIGER/Line Data in the Cloud Making Open Data Useful
- 2. 125 gigabytes of Roads, counties, school districts, census blocks, congressional districts
- 4. 12+ hours to download, unzip, upload into Amazon’s Cloud
- 5. Boot up a mapping server in a minute Connect the TIGER data in two minutes
- 6. 14,000+ Districts + TIGER/line
- 7. Federal Education Budget Program
- 9. Part of a complete open-source mapping stack Without restrictive licenses, distributing and reusing map information is a completely different experience.
- 10. Cloud computing means scalability, the maturity of open-source mapping software means grassroots involvement
- 11. Mapnik, TileCache, MapServer, OpenGeo, PostGIS qGIS, OpenLayers, Google Earth, Consumer GPS http://www.flickr.com/photos/pasma/
- 13. Infrastructure
- 17. OpenStreetMap is creating a worldwide road map 141,000 new miles of African roads
- 18. 150gb “Planet.osm”, 125gb TIGER/line Via FTP & DVDs
- 19. USGS digital elevation data for flooding concerns Population data, land cover data for health and famine crises
Editor's Notes
- #2: Hi, I’m Tom MacWright and I’d like to talk about making Open Data useful with open-source tools and cloud computing. Specifically, I’ve been working with TIGER/line data, which is a great example of incredibly useful data that we only started to tap into
- #3: In the public domain and easily combined with existing data, including 200 gigabytes of Census data
- #4: Every school district in the country, which is keyed so you can combine it with census data.
- #5: Cottage industry of people selling DVDs of free data
- #6: Now it’s fast. You can create a new server in minutes, attach this data in minutes, and start off with ready-made servers
- #13: The historical problem is that slow computers and licensed data meant that there were limited, slow ways to consume geographical data
- #14: But we can do a lot better. Mapping in the cloud, you can put together a system that scales and performs and everyone else can learn from your progress