The Mirador Open Data Competition
About the competition
Mirador is a tool for visually exploring complex datasets, enabling users to infer new hypotheses from the data and discover correlation patterns.
Our goal with the Mirador Open Data Competition was to promote public participation and transparency in research and governance. The competition took place between Sunday September 28th and Tuesday November 4th, and we chose three winning entries with the help of experts in the four datasets included in the competition.
- First prize ($500): Maria Fernanda Gándara. Correlation between Researchers in R&D and Research and development expenditure, from the World Bank Development Indicators.
- Second prize ($200): Yuliia Khodakivska. Correlation between Salary and Month of Birth in the 2013 Lahman's Baseball Database.
- Third prize ($100): Ching-Hsing Wang. Correlation between General Health and Exercise in the past 30 days, from the 2012 Behavioral Risk Factor Surveillance System.
We choose four datasets in health, sports and global development. In our view they are good representatives of Open Data initatives, because they are publicly available, well documented, and up-to-date. These datasets are complex and rich in interesting and unexpected correlations between thousands of variables!
Click on a dataset below to obtain more information about it and to download the project files for Mirador.
NHANES: National Health and Nutrition Examination Survey
BRFSS: Behavioral Risk Factor Surveillance System
Lahman's Baseball Database
World Bank Development Indicators
We were assisted by Tariq Khokhar, Sean Lahman, and Pearly Dhingra on the selection of the winning entries for the World Bank Development Indicators, the Lahman's Baseball Dataset, and the BRFSS data, respectively.
Visualizing the competition!
Lastly, there was an art project taking place in paralel with the competition. Every time a new correlation was submitted in Mirador, the sequence of steps that lead up to the finding was also stored. The (meta) visualization of these search processes in correlation space are described in this blogpost.