Introduction The FutureBoston Competitive Edge Landscape is an experimental tool to explore the factors that make or break a city in today’s competitive global economy. It integrates data on economics performance, innovation, population, and quality of life to help the user see where and what is happening in the Boston region. This tool is a proof-of-concept. It is intended to demonstrate the early stages of what a more advanced tool could do, i.e., better understand the complex dynamics that effect people's lives and help them make better decisions. The Landscape tool is part of a larger project, FutureBoston. FutureBoston is a project that tests ways of engaging the public in understanding urbanissues and advancing ideas to make it better. The Competitive Edge Landscape tool is intended to support this process through an online ideas competition, called the IdeaJAM. Click on the thumbnail above to activate the tool and see what makes Boston tick!
How to use the tool 2) Turn on and off layers of interest using the check boxes 3) Use the sliders to weight different variables as more or less important, seeing how they combine to influence different areas 4) Examine local towns and zip codes in more detail using the Zip / Town Search bar
What it means Ultimately, this tool will develop into a more practical application that will help people make more informed decisions. Towards this end, we welcome comments and feedback on how to make it more useful and effective. Finally, the Landscape tool is part of a larger project, FutureBoston. FutureBoston is an even larger experiment to test ways of engaging the public in understanding the issues in their city and advancing proposals that make it better. The Competitive Edge Landscape tool is also therefore intended to support this process through an online ideas competition, called the IdeaJAM.
What it means At the moment the tool is most valuable for showing the highs and lows of different data values through-out the region. A high peak, shown in red, indicates greater concentration of those values. Low concentrations are displayed as blue valleys. What does this mean? That depends on what variables you select. Housing cost in the Boston area, for example, is much higher than the American average. So "high" does not necessarily equal "better". The same is true for variables like "population density". Some people value high concentrations of people, some value low. Thus it is up to you to interpret the meaning of the data relative to your own goals and values. For comparison's sake, the data for each variable is normalized against the national average. This makes the information comparable between both the Boston metro area and to America as a whole. The transition between blue and yellow values represents the national average. Yellow and red indicate areas with values greater than the national average, blue areas indicates values lower than the national average. Finally, checking multiple variables averages their values together. Since the variables are expressed in percent difference from the national average, you can interpret their combination easily. High, red peaks are areas that are on average greater in concentration of the variables selected, while the same is true of low, blue valleys. Different variables are important to different people. That is why the tool currently uses sliders bars to "weight" different variables against each other when checked. This allows you to emphasize one or several variables over another, creating custom "lifestyle pictures" that indicate the best concentration of values in your prefered location. Keep in mind that the tool only displays the data, as is. Red is not always better and blue is not always worse. The burden of interpretation is on you, the viewer, to select and interepret the variables you care about most.
Future direction This project is an experiment. It's main goal is to demonstrate the kind of application that could be used to help the public understand factors influencing the economic competitiveness of their city and region. Version 2.0 of the tool will allow users to perform basic visual queries which reveal combinations of variables in more meaningful ways. User will be able to use the tool to quickly and easily determine where the best places with high income and low housing cost are, for example, or any other combination of the variables presented. The next phase of development for this tool is already underway and will release shortl. Ultimately, we hope that the tool will evolve into a practical application that can help people make more informed decisions about their lives. Towards this end, we welcome comments and feedback on how to make it more useful and effective. Send all comments, questions and ideas Noah Raford at nraford at mit dot edu.
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