Cities embarking on digital transformations, in the form of sensor network deployment and the digitization of services, need to ensure that data sharing and data partnerships are at the heart of their smart city projects. In other words, they face the same data access and sharing problems businesses face everyday. In both environments, automated data pipelines can play an important role.
Let’s examine the specific data sharing issues smart cities face today. In the past, civic services have operated in departmental silos, with their own IT systems and incompatibility issues making it difficult to pass data between departments or to partners. This has led to inefficiencies in deploying public services in a timely manner, as one department may have contradictory data formats, protocols, and standards.
Having a holistic approach to IT systems and data collection is key for smart city projects, as data in the modern age is not held strictly to one department. Resources need to be shared in order for a smart city to budget correctly, alongside providing external partners such as mobility providers, federal agencies, and businesses with data in real-time or close to real-time.
See also: The Evolving Landscape of Data Pipeline Technologies
Automated data pipelines are needed
That type of sharing can be done through the use of APIs, which automate the sharing and authentication of data between organizations. Cities can create automated pipelines that remove any identifiable bits of data from records, before passing them over to external businesses.
External partnerships are very important in a modern smart city, as public services are typically underfunded and unable to attract top level talent to work on technology projects. By opening up data to external organizations and making the process as straightforward as possible, cities will be able to draw in multiple organizations to fulfill the requirements of their smart city projects.
To achieve this, city leaders need to push forward a data-first culture, which understands the benefits of data collaboration and the need for one set of standards. As we saw with Google’s Sidewalk Labs project, which aimed to make the Waterfront Toronto into a smart city, key stakeholders effectively stalled the project and eventually forced Google to end its involvement. This is critical, if key stakeholders aren’t aligned, it is unlikely that the smart city project will be embraced by the community.
Embracing smart city benefits is easier said than done. Some of the leading cities started with a few small projects, such as automated traffic lights, trash pickup based on bin fullness, and real-time bus arrival times. From there, trust is built between the local government and citizens, allowing them to move onto larger smart city projects that will provide even more benefits. It takes time to shift to a data-driven culture, and these smaller projects allow the culture to change overtime with changes in staff and stakeholders.
