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26 days ago
Unfiled. Edited by Josh kennedy 26 days ago
311 days ago
Unfiled. Edited by Cristos Lianides-Chin 311 days ago
Cristos L
  • Tabula is a tool for liberating data tables trapped inside PDF files.
312 days ago
Unfiled. Edited by Tim Herbert 312 days ago
Currently have a basic RSS reader app with a responsive design that looks fairly good in the browser. Have a small MapQuest view on a tab on its own. Have the calendar RSS feed being processed and parsed into sub-fields that include date/time and location. I have a very basic geocoding process going (using Geocodio as Tim suggested), but the locations from the data feed are often very generic, local names for things, so I'll have to come up with a way of pre-processing them to more specific addresses. Probably a long shot, but I'm wondering if Alexandria would be receptive to including the full address in its news alerts. Of all the city council members I've heard speak, Justin Wilson seems the most tech-savvy. I could possibly see him willing to consider standardizing the address info of Alexandria news items.
So this is about what it looks like on a smartphone right now. This is just a scaffolding proof-of-concept sort of thing for now. I'll eventually be processing this text in a similar way to how email servers process email to categorize it as spam or not spam. Of course, the updates aren't "spam", but "interesting" vs. "uninteresting" works in exactly the same way. Looks like a great start; looking forward to seeing it. 
315 days ago
Unfiled. Edited by Andrew Pasquale 315 days ago
There's a repository in the Hack for Western Mass Github group with some worldwide hunger information and other indicators: https://github.com/hackforwesternmass/hunger-story. The Python code isn't critical for the viz--it's just there to stash the source files and for transparency into the data munge process.
Andrew P
  • Website
The story of hunger is online here!
315 days ago
8 / 22
Unfiled. Edited by John Broglio 315 days ago
John B
  • Updates 6/8/14 1 am EDST
I added addresses and coordinates to the sculptures in the spreadsheet, cleaned up the empty columns and used a node script to turn it into JSON (saved as csv with quotes, then read it in and wrote it out as JSON, making sure the coordinates got into an array).. 
The new JSON data is in the file public/landmarks2.json.
For convenience I used property names closer to what the spreadsheet had.
  • 'landmark_type', 
  • 'title', 
  • 'artist', 
  • 'image_url', 
  • 'image_credit', 
  • 'description',
  • 'offsite_url',
  • 'address', 
  • 'coordinates',
  • 'photo' ,
  • 'photo_credit'
There may be some confusion between the image_url and the photo. It may be that there is no 'photo' property and the 'photo_credit' column data should be moved to the 'image_credit' column.

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