This editorial, co-authored by Mila Gasco-Hernandez and J. Ramon Gil-Garcia is published at Electronic Markets at https://link.springer.com/article/10.1007/s12525-024-00736-w

In our globalized world, governments, societies, and economies rely heavily on data. Data drives decision-making, automation, and innovation across public and private sectors. This trend is intensifying with the ongoing advancements in artificial intelligence (AI), which frequently requires vast amounts of data for training purposes. However, the distributed nature of data—spread across various systems and governed by different actors with their own regulations—poses significant challenges. For instance, achieving a circular economy requires data to measure, optimize, and enhance material reuse. Yet, the relevant data for consumer product components is often fragmented across international supply chain partners. Similarly, in the public sector, data about a single social problem is often fragmented and dispersed across multiple agencies and multiple levels of government with no formal sharing mechanisms. Therefore, effective data sharing among different actors is critical to realize the potential of data in order to address complex problems.