The data sharing market is taking off and there is enormous uncaptured value. Many organisations are looking for new trustworthy ways to create value from data collaboration. Individuals can also benefit tremendously if data can be more readily shared across service providers.
Organisations are afraid of losing control of their valuable data if they share it with others. People are asking for fairness, transparency, and better means of control when their personal data is being used. There is a big need to improve trust in data and AI, while creating trust between collaborating parties. Similar rules and policies are instrumental in scaling up data ecosystems, also across domains.
The Rulebook model developed under the umbrella of Finnish Innovation Fund Sitra’s fair data economy program is a planning and development tool for data sharing. Rulebook is aimed at companies and people developing businesses based on data originating from other companies or sources. It helps identifying, structuring, and communicating critical aspects related to data sharing. Rulebook works like a manual divided into key areas (business, ethics, legal, technology, security) and key contracts concretising the data sharing principles between data sharing participants.
As an example, the rulebook model was adopted by the City of Helsinki to guide the usage of personal data across services provided by the city, often together with other public and private organisations involved in the broader urban data ecosystem. Possible use cases range from authorisation of use of vehicles owned by the city, checking parents’ income level related to preschool subsidies, to more efficient use of personal app data in municipal healthcare services.
In MyData Global’s Human-Centric Companies and Cities (H3C) project, we took the Rulebook model and MyData for Cities approach as a basis. We applied these principles to two health data use cases: making diabetes app data available for healthcare, and collecting data on rare diseases globally. These tackled the issues of fair data broadly: first focusing on business models and transparency of use, and the second on efficient mechanisms for consenting and collecting data.
As the data economy grows and organisations have to deal with increasingly complex data sets, processes, and regulations, managing the data becomes difficult. Using the rulebook approach to implement the data sharing, can save a lot of time, money and headaches.
Written by Marko Turpeinen, CEO of 1001 Lakes
1001 Lakes is a company specialised in trusted data ecosystems and creating business value out of data sharing. It is one of the thought leaders in Europe related to data spaces and involved in activities such as International Data Spaces Association (IDSA), Big Data Value Association (BDVA) and MyData Global.