FAIR assessment of nanosafety data reusability with community standards

New nanomaterials improve our society. Understanding their effects on biological systems is of importance to improve our understanding of their properties and safety. However, reusability of previously produced data to help developing computational risk assessment tools is still limited, due to the inconsistency in experimental reporting, the lack of generally accepted machine-readable metadata standards, and the ability to combine between such standards. Fortunately, the research community has developed multiple minimum reporting standards (MRS) to address a number of these issues. This makes the development of a machine-friendly approach possible to annotate and assess datasets' reusability according to those standards. In this work, we identified twelve published minimum reporting standards relevant to nanosafety research and converted them into a machine-readable representation in the form of FAIR maturity indicators. Moreover, as part of this NanoSafety Data Reusability Assessment framework, we developed a metadata generator web application to be integrated into experimental data management. Finally, a new web application can summarize the nanosafety-related reusability of digital resources against one or more subsets of maturity indicators selected, aimed at specific computational risk assessment use cases. With this approach, we show that we can transparently record and communicate the reusability of experimental data and metadata. This improved FAIR approach will help the community make nanosafety research more reusable for exploration, toxicity prediction, and regulation.