Data ownership: Taking stock and mapping the issues

The objective of this chapter is to take stock and to map the relevant issues related to data ownership. It covers the central aspects of a potential new property right regarding data: its rationale, characteristics, and implementation. Market failure can be a consequence of overly high transaction costs. According to literature, data ownership could correct this market failure by lowering transaction costs for contractual agreements involving data and by correcting a misallocation of costs and benefits, that is, the fact that data collectors are able to externalize costs while internalizing benefits. Data may be protected at three distinct levels: at the syntactic, semantic, and pragmatic level. According to World Economic Forum taxonomy, volunteered data is explicitly shared by individuals. If individuals share data that is not by them but rather about them, this data should be qualified as observed data. Finally, inferred data refers to different data types originating from various sources, used mostly for predictive purposes.