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Pulse is a data visualization based decision support system built for planners, leaders and the public to better understand and learn more about their communities
The project started out as an attempt to understand happiness and mental health through the lens of a community. My hypothesis was that the happiness and mental health were correlated to community health measure through physical activity and wellness initiatives. In my initial research, I discovered various indices in the literature which have been used to quantify happiness, usually at a national level.
On further research, I started to understand that it is really hard to quantify concepts of happiness - maybe even futile. Happiness was not only personal, but the community surrounding a happy/unhappy individual had too many variables which could not be tested within the scope of my project.
Pulse is a step in understanding the numerous variables - both quantifiable and unquantifiable - which affect the communities we live in. My intention was to build a tool which could be used by planners, leaders, or anyone from the public to understand the complexity of a community and to glean possible correlations or actionable insights from data.
The main section of Pulse uses a parallel-coordinate graph to plot the data related to these variables. The user can select two entities - communities/cities/countries - to compare and understand the relations between the different variables. The tool also provides filters which can be used to quickly narrow down the choices. The main dashboard also includes a correlation graph which gives more information about the data under the hood. An additional tool was created to quickly and easily understand or communicate correlations throughout the data.