The WorldFAIR Nanomaterials case study (WP04) has addressed several important topics including undertaking a mapping of the FAIR landscape for nanomaterials (D4.1) and development of best practice for FAIR nanoinformatics models (D4.2). D4.3, presented here, complements and extends the previous two deliverables focussing in particular on Provenance and Persistence of nanomaterials data, considering both human and machine actionable aspects. D4.3 addresses, in particular, FAIR principle R1.2 whereby (Meta)data are associated with detailed provenance, which is essential to enable re-use of data as it provides assurances to potential re-users as to where the data came from, how it was generated and for what purpose, and FAIR principle A2: Metadata should be accessible even when the data is no longer available, which is an essential aspect of ensuring provenance and persistence of data and its associated metadata.
The deliverable builds on work and best practice from:
- FAIR experts and FAIR-focussed projects (e.g., FAIRsFAIR) on the role and importance of persistent identifiers, unique identifiers and resolvable identifiers (collectively persistent identifiers (PIDs), universal unique identifiers (UUIDs) or globally unique, persistent and resolvable identifiers (GUPRIs)) to support data provenance including a landscape mapping of the types of PIDs;
- research performed in the nanomaterials domain as a pilot project around persistent identifiers for nanomaterials themselves, bearing in mind their complexity (as both chemicals and particles) and dynamic nature whereby many of their properties are extrinsic and context-dependent;
- intensive discussions with other case studies from WorldFAIR, mainly Chemistry, Geochemistry, Biodiversity, Agricultural Biodiversity and Cultural Heritage; these were facilitated in part through the WorldFAIR week-long hackathon from 1-6 October 2023 focussed on the WorldFAIR Cross-Domain Implementation Framework (CDIF) to consider how our nanomaterials domain-specific solutions (such as the InstanceMap tool) can be extended to cover other domains, or mapped to the approaches used in other domains (such as biodiversity). This Dagstuhl Workshop created a unique opportunity for the case studies to present and discuss their individual approaches to data provenance related to events (e.g., sampling events, measurement events, data creation events), samples and occurrences, leading to a convergence in approach around the provenance ontology (PROV-O), the Global Biodiversity Information Facility (GBIF) New Data model, and the process for organising events and samples. In the nanomaterials context, we have also mapped an existing provenance ontology (PROV-O) and the GBIF approach to the community developed tools for capturing the evolution of nanomaterials along their lifecycle and in products, formalised via the Instance Map Tool (Exner et al., 2024).
While it has long been known that nanomaterials are very dynamic, this evolution of the materials during storage and sampling has not been systematically incorporated into materials provenance documentation which makes comparison of data challenging, as materials may have been handled differently and thus evolved differently, leading to different outcomes in terms of their toxicity.
The guidance and policy developed and presented here in WorldFAIR D4.3 will support increased implementation of best practice around complete documentation of provenance information about nanomaterials, their samples and the data arising from their production, use, testing, etc. These recommendations are being taken up by current nanosafety projects MACRAME, PINK, CHIASMA and INSIGHT, among others, and will be further documented as a workflow for creation of FAIR digital objects from nanomaterials datasets.
The full report is available on Zenodo.
