Big Data's Implications on Healthy Living Communities

Big Data's Implications on Healthy Living Communities

How does one define a healthy living community? A healthy living community accounts for three things: human health, environmental health and economic health. In such communities everyone has access to basic human services, such as healthy food, safe housing, parks, public transportation, good jobs and schools, all within an environment that has clean air, water and soil. Creating healthy living communities is undoubtedly the holy grail for city planners and government officials, as such communities reflect fundamental human rights. However, how does one develop a plan to achieve such a utopia? The first step is through collecting data to assess where the current health of a community stands and collect other data to see patterns and trends that can help make that community healthier.  

One possibility for quantifying and assessing the health of a community is through collecting Big Data information on the behavior of community citizens in relation to where they live. Big Data refers to extremely large datasets so big and complex that traditional software used to process data have a hard time doing so. This data is created from a variety of sources including: GPS signals from cell phones, social media messages, updates and photos, sensors worn by humans for exercise, online shopping transactions, public transportation videos and much more (Mergel, 2016). Big Data is continuously being generated from our activities, always alive and always changing. Because there is so much varied information coming in at incredible rates and nonstop, the ability for software to capture, store and analyze the data is difficult. However, when Big Data is processed with a specific question or intention in mind, such as measuring the walkability of a community, it can reveal patterns and trends in human behavior and interactions that can help us make better decisions and improve the human condition and our communities.  

Walkability very much is at the core of healthy living communities. It is the measure of how friendly an area is to walk; determined by the quality of sidewalks, bike paths, footpaths, ADA compliance, land use patterns, building accessibility, safety, traffic and road conditions, and proximity to work, school and recreational activities. When a city has high walkability it not only improves the health of community members, by getting people walking and biking more, but also has many positive environmental and economic benefits. When measuring walkability, we need to look beyond daily traffic numbers and infrastructure and measure multiple dimensions of how people are interacting with the layout of their communities, and how the design of the physical space influences social interaction, public health, physical activity and economic development.  Big Data can play a part in developing more walkable communities by using data on where people live in relation to where they work, exercise and eat.  

Of course, there are structural deficiencies in technology, so we need as much human input as possible to verify data. Humans are cynical of data mining and very protective of their privacy. If, however, the relationship between companies and consumers is more transparent and respectful, and ownership of data lies with the consumer first, then consumers may be more willing to share data. This practice of sharing data is called the “New Deal” of Big Data. (Pentland, 2014). For example, though measuring the distance from your house to your child’s school is an important measure to assess the likelihood of your child walking or biking to school, no parent would like to readily disclose where their child goes to school. If, however, community members were given the choice to provide such information, knowing that the goal of collecting such information is to create the best route for a bike path to the school, parents would be much more likely to share this personal information. Another example would be collecting commute information for the University of Alabama at Birmingham (UAB). UAB is the number one employer in the state of Alabama, providing close to 65,000 jobs. Most employees commute to downtown Birmingham to work, which has led to increased traffic congestion, lack of parking, increased pedestrian-car fatalities and increased pollution. In the New Deal of Big Data, UAB employees could opt in to provide commute data so that city planners could develop future public transportation and ride share routes to help reduce car numbers within the city. 

 Another example would be collecting more information for the future Red Rock Trail System. The grand vision of this system is to provide residents complete access to routine transportation and recreation through an extensive network of 750 miles of multi-use trails, parks, bike lanes, and sidewalks. Each of these paths lies near our natural water ways (Jones Valley and Valley Creek, Village Creek, Five Mile Creek, Shades Creek, Cahaba River, Turkey Creek, and Northern Beltway). Big Data can help promote this initiative by seeing how many people live close to the future paths and how many could benefit from using them to travel to work, buy groceries or for recreation. In summation, Big Data coupled with voluntary information provided by residents, can help drive infrastructure and policy changes that ultimately can create healthier living communities.

Mergel, I. (2016). Big data in public affairs education. Journal of Public Affairs Education. 22(2). 231-248. Retrieved from http://www.naspaa.org/JPAEMessenger/Article/VOL22-2/09_Mergel.pdf

Pentland, A.S., & Berinato, S. (2014, November). With big data comes big responsibility. Harvard Business Review. Retrieved from https://hhbre.org/2014/11/1with-big-data-comes-big-responsibliity.