Link to the webpage:
http://cse512-15s.github.io/fp-jbare-kaul10-lizehang-nanand/
#Team:
Justin Bare
Nandita Anand
Aditya Kaul
Zehang Richard Li
#Summary Image:
#Abstract: We envision using online tools to introduce information into the political sphere in ways that are transparent and fair, and that hold the producers of facts accountable for the information they provide. As a prototypical example, we are developing an online calculator for a revenue-neutral carbon tax proposal in the state of Washington. The data visualization discussed here is one of the features of this tool aimed at facilitating voters' understanding of the policy and its impacts. We hope that features such as these will provide a basis of information from which democratic processes can proceed more effectively. Following the tradition of exploratory visualizations, our tool allows users to find their own insights from a large body of data using various filtering options and both broad and specific views of the data.
Poster is available here
Final paper is available here
#Software instructions: Go here to access the visualization or download this repository and run python -m SimpleHTTPServer 8888 and access this from http://localhost:8888/.
#Division of Labor: All members in the group participated in regular discussion, literature review, and writing. Each member's focus is provided below:
- Justin Bare
- Data retrieval, cleaning, and computation
- Filtering and variable selection
- Map geographic boundaries display and coloring
- Histogram computation and design
- Mouse event update scheme
* Nandita Anand
+ Implemented zoom and tooltip feature in the map + Reviewed the relevant literature + Brainstormed ideas and provided ideas on data representation
* Aditya Kaul
+ Implemented zoom and tooltip feature in the map + Worked on the initial phase of histogram creation on map click + Implemented tooltip on histogram + Introduced the drop down to select different variables
* Zehang Richard Li + Navigate and locate external dataset to combine with the main PUMS data. + Perform data cleaning and missing data imputation. + Pre-compute aggregated data table and bubble locations in the bubble chart. + Implement the bubble chart, including interaction with the main map.
#Research/Development Process: We all met very soon after signing up for this project and we discussed the goals of the project and began storyboarding. We then discussed how to divide up the work. We communicated often throughout the process and we ended up working across our original divisions a lot when specific help was required. Throughout most of the project process we were working on getting better data and computing the variables we needed, which was somewhat annoying. However, in the end we still had ample time to develop the visualization and the project turned out well.