The aim of Open Science is to open up data to enrich knowledge creation processes. At present, Open Science actors face problems when trying to find and exchange data. Research data management platforms need to address the issue of interoperability to enable interdisciplinary research. Some solutions are available for specific communities, but none addresses the problem as a whole. Based on an extension of the theoretical model of interoperability, which enables us to define the criteria for an information exchange, we have quantitatively evaluated information exchange in Open Science. On the basis of this explorative study, we propose an inter-community and inter-disciplinary information exchange network solution enabling decentralised and federated data management as well as a unified search for datasets across all the entities registered in this network: the Open Science Data Network (OSDN). We carried out a proof of concept to assess the feasibility of the solution. We also evaluated this solution by applying it to a completed agronomy research project. This evaluation enabled us to measure a 7% increase in the volume of data, with an 80% reduction in the time needed to find this data. In addition, users have been able to design new intra- and interdisciplinary future works with found data.