October 17, 2012
Big data analytics are dependent on just that, big data. For cities, this means a constant stream of information, including purely environmental factors like weather, group-level data like parking spaces filled or public transportation utilized, and individual-level data that is aggregated for analysis. This comprises everything from tweets, which build up a picture of community sentiment, to residential smart water meter data, which enable comprehensive understanding of water infrastructure operations, leaks, and other sources of possible lost revenue. Although vital to any kind of urban big data analytics initiative, the latter category of information initiative, can become a point of contention wherein privacy concerns and a distrust of government intruding on personal information can either preclude the participation and buy-in needed to generate an adequate stream of data or foster retaliation and animosity if this data is collected against or without the permission of citizens.
This challenge raises the question of how governments can effectively incentivize data collection and buy-in so as to create not only a tolerant atmosphere of utilizing citizen-generated data, but also one of enthusiastic involvement. What tactics can government take to help citizens see personal benefits in the free flow of this information and possibly also additional benefit from participation in the civic sphere through data? There are of course a variety of possible approaches a government can take, varying in ease, sustainability, and effects on the relationship between citizens and their government.
Take the case of smart water meter installations in residential homes that are used to generate a complete picture of system-wide water use, flow, and pressure. This information can be used to detect leaks, water theft, exceptionally high use, or other sources of misuse or operational dysfunction. For example, Dubuque, IA has partnered with IBM under the leadership of Mayor Buol to recreate the city as a truly integrated, sustainable smart city. The project includes a pilot of 300 smart water meters installed in citizens’ homes which collect a constant stream of information fed both into city databases and analytical engines, along with dashboards for individual household information access.
The smart water meter pilot informed and facilitated households’ moderation of their own water consumption to save money, while simultaneously helping the city fulfill its conservation goals. The pilot study found that participants realized an average household savings of 6.6%, reported water leaks eight times more frequently, and active portal users reduced their water consumption by 10%. A social platform enhanced conservation efforts through contests, chat between participants and with government employees, and a bulletin board to share best practices.
However, the tension between data utilization and privatization remains. For example, it played out quite vividly when Mayor Bloomberg announced the installation of hundreds of thousands of real-time digital water meters in New York City. One city council member appearing at the news conference allowed his personal water consumption to be shown in the new format, revealing a water spike one Wednesday; several in the audience speculated about a leaking toilet or a long shower. The access to the information provided both insights and also a little bit too much visibility into his lifestyle. For these reasons, Dubuque anonymized participating households with unique user IDs and the city management’s portal access was restricted to display information solely in aggregate. However, the city still had to make it very clear to participants that their data would only be viewed anonymously and in aggregate, it would not be used to allocate or ration water, and any water conservation would remain entirely voluntary.
It might be impossible to entirely eliminate all citizens’ suspicions and concerns, but Dubuque is on the right track in generating citizen buy-in through anonymity and giving citizens access to and utilization of their own data. Important to getting citizens on board is not only allowing them free access to the information they are generating, but also improving their data literacy. The more easily citizens can make sense of these data streams, formatted through the right visualizations and feeds, the more likely they are to easily find their own benefit in data generation and become proponents rather than uneager participants or worse, opponents to big data initiatives. Utilizing data to generate individual streams for household use and aggregate streams for city management use helps everyone gain access to the information they can use to save money and conserve the environment.
Such distributed support shifts the role of citizens from passive participants – having government dictate how households should conserve water – to active participants, sharing the knowledge and data necessary for households to take steps to conserve of their own volition, in the ways best suited for their own circumstances. Other city efforts, like opening up information databases for open app development or distributing live-data maps dealing with issues like crime, education, and disasters, speak to this same tactic of giving citizens agency while using them as the sources and generators of data.
Helpful to the long-term success and maximum utilization of big data analytics in cities is not only getting developers and the computer-savvy on-board, but producing the kinds of dashboards and modes of access that will be of use to a range of ages, computer literacies and education levels. That is true data democratization, and it is what is needed to break down divisions between citizens and their governments for the sake of innovative, sustainable policy with full buy-in from both groups.