Data sharing and data ownership
Data sharing ensures a faster evolution of digital products and enables applications that create more value for those using it. This is accepted in many commercial settings. Data sharing is considered a business necessity to accelerate any digital offering and is ‘an engine of innovation and transformation.’ Data collection is no longer enough. Such processes are anything but simple with ever-changing service provision, eligibility criteria and differing individual needs.
Data sharing vs. data ownership
Data sharing does not mean releasing ownership of the data. Given the need to maintain such information, any data sharing models need to include data ownership principles. Each provider of data must retain control over the data quality and must be able to withdraw ownership at any point. This could result in different rules for how data is used and shared within the network, rather than a specific set of rules for all providers.
Examples from other sectors
- Credit Scores: Credit scores are created using shared data between traditional lenders, telecommunication providers, utility companies and credit reference agencies. The aim of sharing data about a customer’s spending and repayment behaviour is to get a full picture of that person’s financial situation and assign a credit score as a result. All companies can use this to better understand how safe it is to lend to that customer and how likely they are to pay their bills, to identify and support financially vulnerable consumers and to reduce losses by motivating customers to pay. Sharing data with at least one credit reference agency is adopted by almost all traditional lenders and telecommunication providers. However, adoption is much lower for utility companies.
- Aircraft wing development: The Advanced Product Concept Analysis Environment project (APROCONE) involves Airbus sharing data using engineering data on the design, analysis and development of aircraft components with supply-chain partners. This is done to increase the efficiency and accuracy of the components, and reduce the time needed to do research and development.
- Smart cities: Smart cities aim to improve efficiencies, accessibility and the quality of communities lives through the use of technology, data sharing and data analysis. The work is set up as a mixture of technologies, networks, and user interfaces that share and aggregate real-time data. This could be anything from vehicles, home appliances, smart street light sensors, ride sharing and smart parking metres.