Non-Traditional City Index
Many of my peers are planning to move to other cities within the next few years, and while some are travelling to take a new job or meet up with family, others are more uncertain about their future location. Part of this uncertainty stems from the lack of effective and transparent city ranking systems available to the public: when it comes to looking up city information, most people either have to rely on unclear and arbitrary Top 10 lists, or else laboriously dig up statistics from a variety of different sources.
In an era when cities market themselves to attract investment and the young "creative class," it is important for the public to have access to clear, objective information that describes the differences between them. This project fills that need: it allows for users to differentiate between cities based on their personal needs, using clear and objective metrics, and then visualize those differences with an easily-understood interactive map. Additionally, this project includes a number of unconventional indices and a diverse group of urban areas, which may encourage users to widen their search.
How it Works
The Non-Traditional City Index is composed of demographic, housing, and locational indicators that are selected by the user. The user can select an indicator for inclusion by checking the box to its left. Each indicator is linked to three variables for each city: the actual, numeric value for that indicator; a rank, out of 147; and a normalized value, where the best value for that indicator is set to 1, the worst value for that indicator is set to 0, and everything else is somewhere in between. Some indicators are location-based, and describe whether or not certain points of interest can be found within a given distance of the city center. These indicators are binary (0/1): either the urban area is within range of the given features, or it is not.
The user also assigns a weight for each indicator that he or she wishes to include in the Index. The weighting determines how important each indicator is in the calculation of the final score. Weights are proportional: an indicator with a weight of
6 is considered twice as important as an indicator with a weight of
3, and three times as important as an indicator with a weight of
2. Note that weights are not rankings of importance: the same weight can be assigned to multiple indicators, and higher-numbered weights are assigned more importance than lower-numbered weights.
To calculate the MetaScore for each city, an algorithm multiplies the normalized (0-1) value for each selected indicator and multiplies it by the weight for that indicator. The algorithm then adds all of the weighted indicators together into a single score. Next, these summed scores are normalized from 0 to 1 across all 147 cities. Finally, the algorithm color-codes cities based on their scores.
When the Non-Traditional City Index is calculated, at least one urban area will have a score of 1; according to the algorithm, this urban area is the best possible match for the user based on his or her selected criteria. At least one other urban area will have a score of 0; according to the algorithm, this urban area is the worst possible match for the user based on the selected criteria. All other cities will fall somewhere on the 0-1 scale, where higher scores (symbolized with blue) indicate a better match, and lower scores (symbolized with red) indicate a worse match.