From the experimental data presented in literature, it is often difficult to fully assimilate the interaction between ENMs and biological structures or systems, which limits insights into the MIEs/KEs they can trigger and inhibits the development of nano-related AOPs. Here, we present a proof of principle of implementing semantic web approaches for reporting ENMs, their physicochemical characteristics and their interactions with biomolecules and biological systems. It expands on the work initiated by where a scientific literature analysis was performed to connect ENMs with existing AOPs . That resulted in the identification of ENM-relevant MIEs and KEs, which were used to explore and repurpose chemical-based AOPs and KEs for ENMs to set up in vitro testing strategies, which was demonstrated with two case studies.