Abstract
The emergence of nanoinformatics as a key component of nanotechnology and nanosafety assessment for the prediction of engineered nanomaterials (NMs) properties, interactions, and hazards, and for grouping and read-across to reduce reliance on animal testing, has put the spotlight firmly on the need for access to high-quality, curated datasets. To date, the focus has been around what constitutes data quality and completeness, on the development of minimum reporting standards, and on the FAIR (findable, accessible, interoperable, and reusable) data principles. However, moving from the theoretical realm to practical implementation requires human intervention, which will be facilitated by the definition of clear roles and responsibilities across the complete data lifecycle and a deeper appreciation of what metadata is, and how to capture and index it. Here, we demonstrate, using specific worked case studies, how to organise the nano-community efforts to define metadata schemas, by organising the data management cycle as a joint effort of all players (data creators, analysts, curators, managers, and customers) supervised by the newly defined role of data shepherd. We propose that once researchers understand their tasks and responsibilities, they will naturally apply the available tools. Two case studies are presented (modelling of particle agglomeration for dose metrics, and consensus for NM dissolution), along with a survey of the currently implemented metadata schema in existing nanosafety databases. We conclude by offering recommendations on the steps forward and the needed workflows for metadata capture to ensure FAIR nanosafety data.
Highlights
As long-term historical data on the effects of engineered nanomaterials (NM) are lacking, the extensive use of NM in everyday life raises questions regarding their fate, the environmental and biological exposure routes and the potential risks for the environment, biological organisms, and humans [1,2]
IOM contains data spanning a wide spectrum of nanosafety research, as it is populated with data from various EU funded projects, like MARINA [81], SUN [82], NanoSolutions [83], PATROLS [84], Gracious [85], and more
In terms of FAIR metrics and FAIRification, we quickly present the current status from the reviewed databases, on the technical FAIR principles according to the classification above
Summary
As long-term historical data on the effects of engineered nanomaterials (NM) are lacking, the extensive use of NM in everyday life raises questions regarding their fate, the environmental and biological exposure routes and the potential risks for the environment, biological organisms, and humans [1,2]. A key challenge for the risk assessment of NM is their dynamic nature, whereby NM may transform during storage [3,4], in product formulations [5], and when released and exposed to media or living organisms [6,7] Regulatory frameworks, such as the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) in Europe and the Toxic Substances Control Act (TSCA) in the United States, were instituted prior to the widespread application of nanotechnologies and did not differentiate between nanomaterials and their larger, bulk forms. For existing NMs, the U.S Environmental Protection Agency (U.S EPA) requires information on the chemical identity, the manufacturing methods, and production volumes, processing, use, ecological and human exposure, release information, and available health and safety data
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