Smart cities and connected cars depend on data sharing and data-driven decision making. The best decisions use data from many sources and several stakeholders. Data can be personal, coming from individuals, and also from connected devices. There are also public- and private sector data sources. Bringing these data sources together requires stakeholders to share data. This relies on trust, on privacy management tools, and on ways to control data sharing, either openly or selectively with ecosystem partners.
This presentation will introduce the concept of a data exchange and how it was put into use. It involves four municipalities who applied it in the course of a 2-year pilot, with over 200 types of city and transportation data sources. The trial helped to refine a data sharing blueprint, spanning administrative boundaries and exposing data to independent analytics and application developer firms.
Operating as the oneTRANSPORT data marketplace, the post-pilot system now supports other applications. In the case of connected and autonomous vehicle applications, this involves a data sharing cooperation between:
public-sector highway managers (e.g. traffic flows, messaging via dynamic road signs);
private sector data providers (e.g. car park availability, weather);
and, vehicle providers (location and trip-planning).
The presentation will use application examples to describe how different stakeholders define and exercise their data privacy policies. It will also illustrate several implementation dependencies, including ways of implementing privacy rules that will scale. This is to accommodate new data sources and stakeholders to the marketplace.
There will also be a discussion of data monetization issues, reflecting our market experience. This will touch on the opportunities that service providers are exploring how best to capitalize on data privacy choices.