Pinned Repositories
2015-11-refugees-in-the-united-states
Data and analysis supporting the BuzzFeed News article, "Where U.S. Refugees Come From — And Go — In Charts," published on November 19, 2015.
Cardia
Cardia is a rapid-response heart health app for the Jawbone UP3 made for the 2015 Women's Health Codeathon
codeofconduct
Code for America's Code of Conduct
d3.chart.layout
Interactive and reusable d3.layouts built with d3.chart framework.
dclegalhackathon
DC Legal Hackers' First Hackathon
Evolving-Tree
human-services-scoping-plan
Human Services Pilot Project Scoping Plan
LSC-Mapping
The Legal Services Corporation has presented us with a compelling issue for legal hackers with the potential to help many low-income individuals around the country. In a nutshell, LSC offers civil legal services to low-income individuals on the basis of particular "service areas," which are defined on the basis of county, city, town, or other lines, as defined by Congress. LSC providers have locations within these services areas, and are only allowed to provide legal services within those areas. Therefore, it's important for low-income individuals to know which LSC locations can serve them (and, relatedly, which of those locations is closest to them). As it stands, the LSC search tool only offers the ability to search on the basis of state and county. Because counties can be very large, and sometimes the LSC service areas are not drawn on a county basis, the search function is not as helpful as it can be (and in some cases leads to confusing results). See Massachusetts for an example. Ideally, the search tool would be able to take a zip code as input and return the nearby locations in the assigned service area. In this hackathon, we will use the underlying mapping data that LSC has on file to create new and helpful ways for low-income individuals to search for their appropriate LSC location.
Wiki-Edit-Geolocator
R pipeline to pull anonymous Wikipedia edits, geolocate them, and produce a county-scale frequency table.
traviskorte's Repositories
traviskorte/Cardia
Cardia is a rapid-response heart health app for the Jawbone UP3 made for the 2015 Women's Health Codeathon
traviskorte/2015-11-refugees-in-the-united-states
Data and analysis supporting the BuzzFeed News article, "Where U.S. Refugees Come From — And Go — In Charts," published on November 19, 2015.
traviskorte/codeofconduct
Code for America's Code of Conduct
traviskorte/d3.chart.layout
Interactive and reusable d3.layouts built with d3.chart framework.
traviskorte/dclegalhackathon
DC Legal Hackers' First Hackathon
traviskorte/Evolving-Tree
traviskorte/human-services-scoping-plan
Human Services Pilot Project Scoping Plan
traviskorte/LSC-Mapping
The Legal Services Corporation has presented us with a compelling issue for legal hackers with the potential to help many low-income individuals around the country. In a nutshell, LSC offers civil legal services to low-income individuals on the basis of particular "service areas," which are defined on the basis of county, city, town, or other lines, as defined by Congress. LSC providers have locations within these services areas, and are only allowed to provide legal services within those areas. Therefore, it's important for low-income individuals to know which LSC locations can serve them (and, relatedly, which of those locations is closest to them). As it stands, the LSC search tool only offers the ability to search on the basis of state and county. Because counties can be very large, and sometimes the LSC service areas are not drawn on a county basis, the search function is not as helpful as it can be (and in some cases leads to confusing results). See Massachusetts for an example. Ideally, the search tool would be able to take a zip code as input and return the nearby locations in the assigned service area. In this hackathon, we will use the underlying mapping data that LSC has on file to create new and helpful ways for low-income individuals to search for their appropriate LSC location.
traviskorte/Wiki-Edit-Geolocator
R pipeline to pull anonymous Wikipedia edits, geolocate them, and produce a county-scale frequency table.