Smart cities may be the ultimate expression of the promise of data sharing and artificial intelligence. They provide citizens with connected services that are more efficient and effective than traditional methods of service delivery. A person’s average day can start with them leaving their house, their climate control turned off, and with a vehicle waiting to take them to work —while he or she is at work, the city may detect that their waste containers are full and need to be emptied or that a streetlamp has been damaged and needs repair. These smart services promise to be more convenient and greener, meeting goals of both the givers and receivers of services.
Data collection for smart cities is a governance challenge
The expansive and connected nature of these smart services means that a lot of data is being collected, but also that a lot of different types of data are being connected. As seen in the Waterfront Toronto example, this can have implications for data privacy, but can also represent technical challenges of coordinating data collectors who have different data needs and processes. The challenge is two-fold: both different organisations are collecting data, but also companies are operating in different sectors. This makes harmonising data collection rules and adopting data standards even more complex.
Data governance proves to be difficult
Mature digital organisations recognise that data needs to be governed—and this often proves to be more difficult than agreeing to technical standards. For stakeholders that do not belong to the same organisation, rules for data sharing look to ensure that data is being collected according to strict technical and ethical standards, while at the same time, ensuring that companies are not disincentivised from collecting and sharing their data. It needs to be clear for participants in a data space that they will benefit by participating in the ecosystem, but also that they will not face legal or business challenges (such as GDPR concerns, for example). Well-known standards do exist and set the tone, including quality standards and rules on whether data can be shared.
Trust between collectors and providers is critical for a successful data space
These well-known standards create ground rules that are critical for the successful operation of the data space. If companies are worried about incurring fines from the government or that other data providers will use the data that they provide to gain valuable business intelligence, they will not want to participate. They need to trust the other participants. At the same time, in a smart city context (which is Business-to-Customer (B2C), the residents of the smart city need to trust that the data that they are providing will be used in a clear and ethical way. Some may respond that people are already willing to give quite a bit of data to Google as a part of using their Android smartphones, and that the need for rules to govern data to build trust is exaggerated. However, residents in a smart city likely have few options to “opt out” of certain data collection activities, which can lead to ever-increasing tensions in the community. Again, the Waterfront Toronto example is instructive.
How does data governance look?
Within a particular data space, good data governance requires an authority or organisation that can approve of what has happened with the data—a part of the sharing process requires checks on data quality, including metadata, to ensure that all the rules are being followed. These checks are particularly important for smart cities where harmonising the data from providers across sectors is all the more important to provide as much opportunity as possible allow providers to take advantage of the breadth of information and innovate.
Governments play an important role in developing trust
In some data spaces with limited and specific data collection, data can be governed by the players themselves based on internal negotiations. In data spaces such as smart cities, with its broad data collection, governments play an important role in developing trust. Governments can play a role in setting common standards that facilitate technical discussions and lay down basic standards. But more importantly, the support of government—as well as civil society groups—can be critical to build trust between residents of these smart cities who are expected to give up their data in exchange for the services that will be provided.
Data governance should bring in trusted members of the community
While governments play an important role in building trust and developing checks and balances between data collectors, governments also interact with civil society groups, who cannot be ignored as a part of wider data governance issues. Data governance, and potentially the boards that determine the rules, should have cross-representation. This means bringing in organisations and individuals that are trusted members of the community from both the public and private sector. Again, this is an area that requires balance, as too much representation slows decision-making, while too little can lower trust and increase the chance for conflict.
|Context||Data collection for smart cities is a governance challenge, and proves to be difficult. According to Derilinx and the OGCIO,
trust between collectors and providers is critical for a successful data space and governments play an important role in developing that trust. They also emphasize that data governance should bring in trusted members of the community.