This dissertation seeks to explore how data sharing can enable circular ecosystems. Circular ecosystems refer to a set of heterogeneous yet interdependent actors that collaborate to achieve a system-level outcome aligned with the principles of the circular economy to value resources and extend products’ lifecycles. Digital technologies, such as platforms and AI, have been extensively recognized as enablers of circular ecosystems. Digital technologies enable them through data collection, sharing, and analysis. Still, companies may be reluctant to share data and open their data boundaries, lowering the potential offered by technologies like AI. Therefore, this dissertation aims to investigate how data boundaries can be opened to really enable circular ecosystems through collaborative initiatives. The dissertation will first require performing a systematic literature review at the intersection of circular ecosystems and digital technologies to gather knowledge about the role of data and data boundaries. Secondly, real-world case studies should be analyzed in order to interview companies leveraging data and digital technologies to enable circular ecosystems.