Metadata Stewardship in Nanosafety Research: Community-Driven Organisation of Metadata Schemas to Support FAIR Nanoscience Data

Research output: Contribution to journalArticlepeer-review

Authors

  • Frederick C Klaessig
  • Thomas E Exner
  • Sabine Hofer
  • Norbert Hofstaetter
  • Martin Himly
  • Marc A Williams
  • Philip Doganis
  • Mark D Hoover
  • Antreas Afantitis
  • Georgia Melagraki
  • Tracy S Nolan
  • John Rumble
  • Dieter Maier

External organisations

  • Pennsylvania Bio Nano Systems LLC
  • Edelweiss Connect
  • Paris Lodron University of Salzburg
  • U.S. Army Public Health Center (APHC)
  • National Technical University of Athens
  • Mark D Hoover LLC
  • University of Arkansas for Medical Sciences
  • R&R Data Services
  • Biomax Informatics AG

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.

Details

Original languageEnglish
Article number2033
Pages (from-to)1-49
Number of pages49
JournalNanomaterials
Volume10
Issue number10
Publication statusPublished - 15 Oct 2020

Keywords

  • (meta)data, Data curation, Data management roles, Data shepherd, FAIR scientific principles, Nanosafety