ARRA Recipient Activities
The ARRA Recipient Activities database is a tool for exploring the kinds of activities that recovery act funds are being spent on, and the populations that are being served by the funding. Combining data reported by recipients of funds from the American Reinvestment and Recovery Act (ARRA) with data from the National Center for Charitable Statistics (NCCS) and data from the North American Industry Classification System (NAICS), the database allows users to view recipient funding across broad levels of activity, such as “Education,” as well as to drill down to more specific activities, such as “Vocational & Technical Schools.” The database also includes information on populations (“Migrant Workers,” for example) that funding recipients reported serving based on NCCS population codes.
Air quality and Traffic
Nowadays, near real-time air quality and traffic data are available in the internet. It would be interesting to put them together on a single map so that the correlations between them could be observed and analyzed. Using Google map, air quality data could be shown on the map along with real-time Google traffic. This is a prototype to demonstrate the idea. This idea will be further developed in the Mobile Millennium Project (a project in Berkeley that uses cell phones as mobile traffic sensors) with historical traffic data available. This allows us to examine the effect of air pollution from vehicles in a new perspective.
Created as a campaign research tool to help identify counties as areas of intrest based on user choices California Registered is a website that generates comparative heat maps with California’s registration information. The maps can be used to identify how counties compare to each other in an easy to read and ready for presentation format. The coloring system makes it simple to see possible swing counties as well as areas that have high densities or populations of a key voter demographic.
California Registered gathers registration data from the general election of 2008 in a MySQL database and combines that with user selected data sets and color schemes to produce the XML used by the fla-shop interactive flash map.
ARRA Data Mashup
Ayush Khanna and Emily Wagner
The American Recovery and Reinvestment Act of 2009 (ARRA) was passed on February 13, 2009 with three immediate goals in mind:
1. Create new jobs and save existing ones
2. Spur economic activity and invest in long-term growth
3. Foster unprecedented levels of accountability and transparency in government spending
Our data mash-up project attempts to take a closer look at whether or not the ARRA was successful in its ﬁrst goal of creating new jobs and saving existing ones by looking at how unemployment levels changed (or didnʼt change) as ARRA award money was dispersed.
Due to data speciﬁcity problems associated with jobs “created” by each award, we chose to use unemployment data as a more reliable, although less tightly-related metric for comparison. We also chose to examine only data for the state of California for our proof-of-concept visualizations which could later be expanded to the entire country in future work. Two ﬁnal mash-ups were created. The ﬁrst uses the Google Visualization API to create a motion chart of unemployment changes as ARRA award money is dispersed over time. The second uses the commercially available product Tableau to incorporate information about geographic space and senses of scale.
Park Smarter allows drivers who park in San Francisco neighborhoods with residential parking restrictions to answer a key question: “What’s the smartest place I can park my car today?” Many of the blocks in these neighborhoods require that all cars be moved elsewhere once a week for scheduled street sweeping, and that leaves drivers juggling a long list of street locations, days, and times when parking is available. This mashup is a web application that combines San Francisco’s publicly available street-sweeping data and code from the
Google Maps API to map which blocks in a user’s neighborhood have street sweeping on a given day. An optional component uses Twitter geolocation information and RSS feeds to map tweets about parking
conditions, such as when a certain street has been swept for the week or when spaces will be blocked off for temporary construction. The object is to provide an easier way for residents with particular parking objectives in mind — say, combining moving their car with their regular Thursday yoga class or Monday carpool — to target the streets that will best meet their parking needs.
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