Everyone is familiar with the term smartphone. These devices have become ubiquitous and many individuals have come to depend on them to navigate through our complicated world. They can assist users in a wide variety of ways that were unthinkable a mere 20 years ago. You might be tempted to take a look at yours right now.
Smart technology has also been incorporated into other consumer devices to create the smart home paradigm for improving the quality of life of an individual or family. A logical next step is the development of smart cities to bestow the same benefits on the general public.
There is no simple and all-encompassing definition of a smart city. In broad terms, a smart city makes use of information and communication technologies (ICT) to enhance the quality of life of its citizens. This is done by improving services such as transportation, energy consumption, and other utilities to streamline their delivery and reduce excess costs. Information regarding various aspects of negotiating city life, like finding the best route to work in the morning, is made available to the population through real-time data processing.
Developing Viable Smart Cities Requires Data Governance
As with many other aspects of modern society, the creation of smart cities relies on the intelligent use of data. If a municipality does not use the information wisely and responsibly, it can lead to a failure of the planned initiatives and a lack of public trust. The goal is to use the data for financial and quality of life improvements as well as to instill confidence with the population that the systems are working effectively.
Seven layers of data governance and management are incorporated into the best practices that drive the smart city paradigm. Starting without these strategic building blocks dooms the enterprise to failure. They create a strong foundation of secure and actionable data that can be used to implement new services and businesses with full public support.
Data categorization is essential to ensure that data is used intelligently and for the right purposes. The information used in constructing smart cities comes from sensors, vehicles, and individuals. The categories adopted by the city’s developers need to be useful for current and future projects that advance the smart paradigm.
The consent of individuals over what personal data is being collected, how it is used, and how long it is retained is a critical factor in obtaining public support for smart city initiatives.
How data collection is conducted is critical in the development of smart cities. Analyzing, encrypting, and standardizing the tremendous volume of data generated by the connected devices and individuals that encompass the targets of data collection poses a significant challenge to the success of smart city projects.
Anonymization of collected data is vital to protect it from misuse by unscrupulous entities. Individuals should not be able to be identified by data that they are generating toward the functioning of the smart city.
Data storage plays a role in supporting every aspect of smart cities. It needs to be secure and scalable with robust disaster recovery and contingency plans to keep things moving in the event of an infrastructure failure.
Access to the data resources is necessary to use it to further any of the projects that power the smart city. Access needs to take regulatory and privacy concerns into account that may harken back to the categorization stage.
Monetizing the collected data is dependent on properly handing the previous layers of data management. Combining various categories of data can lead to numerous possibilities of value-added services constructed from dynamically generated information.
A successful smart city strategy needs to insist on providing value to its citizens to develop and maintain a high level of buy-in. Demonstrable benefits to the population will go a long way toward building public support as new services are introduced.
Implementing Data Governance
The massive scale of smart city data collection implies that many different methods are employed. One constant is that the information will find its way into databases where it is analyzed and put to good use for the benefit of the city’s population. These data resources are the raw materials that will be used to populate the layers of data governance required for a successful smart city.
