From CS 294-10 Visualization Sp10
A tremendous sum of money has been pledged to help Haiti recover from the devastating quake and rebuild. There are two factors complicating this process. First, a pledge to offer aid is not a guarantee. After the 2004 tsunami, millions of pledged dollars never arrived. Second, there can be a mismatch between funding and use. The total funds raised (both confirmed and unconfirmed) is over $1.7B, but we don't know how these funds are being allocated, or when pledged funds will be confirmed. The UN programs covered by this data graphic represent only a portion of the projects in need of funding in Haiti, but I think they illustrate the difficulty of figuring out what to do with funds that have arrived.
The variables encoded here are the project type being funded (nominal variable, encoded by position), the amount of dollars (quantitative variable, encoded by length), and the status of funding (nominal variable, encoded by brightness of color).
For the funding status I chose dark green, a color associated with money in the U.S., to represent "hard money," or funds that have been delivered or committed in a legally binding agreement. I used a lighter shade of green to represent "soft money," the pledged amounts that donors have not committed to formally. I placed the pledged funds bars inside the space showing the unmet need because these funds would reduce the unmet need. I used white, the absence of green, to indicate a funding shortfall. I reinforced this scheme in the colors of the labels, using red to accentuate the lack of money.
I considered alternate placements of the individual sector bars. The most compelling alternative layout (which I opted against because it has more unused space) would line up the dark green committed bars of each sector, allowing the viewer to quickly gauge how much money had been committed to all programs.
If I could have incorporated more data, I would have liked to use small circles alongside each bar to indicate the number of UN projects proposed in each area, with color indicating their funding status. A list of these projects accompanied the original spreadsheet data at the OCHA site (http://ocha.unog.ch/fts/reports/daily/ocha_R3_A893___1002070235.pdf). There are over 20 proposed projects in the health sector.
My visualization leaves out a significant portion of the provided dataset. In particular, there is no indication of funding sources, and no mention of funds allocated to projects beyond the UN programs outlined here.
The image below is also available in vector format: File:Status-of-un-project-funding.pdf
I created this data graphic by hand in InDesign, which was tedious. I'm looking forward to learning about more automated methods for generating visualizations.