How should the completeness and quality of curated nanomaterial data be evaluated?

Abstract

Nanotechnology is of increasing significance. Curation of nanomaterial data into electronic databases offers opportunities to better understand and predict nanomaterials’ behaviour. This supports innovation in, and regulation of, nanotechnology. It is commonly understood that curated data need to be sufficiently complete and of sufficient quality to serve their intended purpose. However, assessing data completeness and quality is non-trivial in general and is arguably especially difficult in the nanoscience area, given its highly multidisciplinary nature. The current article, part of the Nanomaterial Data Curation Initiative series, addresses how to assess the completeness and quality of (curated) nanomaterial data. In order to address this key challenge, a variety of related issues are discussed: the meaning and importance of data completeness and quality, existing approaches to their assessment and the key challenges associated with evaluating the completeness and quality of curated nanomaterial data. Considerations which are specific to the nanoscience area and lessons which can be learned from other relevant scientific disciplines are considered. Hence, the scope of this discussion ranges from physicochemical characterisation requirements for nanomaterials and interference of nanomaterials with nanotoxicology assays to broader issues such as minimum information checklists, toxicology data quality schemes and computational approaches that facilitate evaluation of the completeness and quality of (curated) data. This discussion is informed by a literature review and a survey of key nanomaterial data curation stakeholders. Finally, drawing upon this discussion, recommendations are presented concerning the central question: how should the completeness and quality of curated nanomaterial data be evaluated?

Integration among databases and data sets to support productive nanotechnology: Challenges and recommendations

“…However, the question of which physico-chemical properties need to match (Stefaniak et al, 2013), not to mention complexities associated with different measurement techniques and experimental protocols, make uniquely identifying and matching nanomaterials a significant scientific challenge. Further discussion of metadata (including batch identifiers) that could support unique identification and matching of nanomaterial database records is provided in an earlier article in the NDCI series (Marchese-Robinson et al, 2016). …”

“…A thorough discussion of the challenges associated with assessing the completeness and quality of nanomaterial data was presented in an earlier paper in the NDCI series (Marchese-Robinson et al, 2016). …”

“…It is one in a series of papers focusing on important aspects of nanoinformatics produced by the Nanomaterials Data Curation Initiative (NDCI), which is part of the National Cancer Institute (NCI) Nanotechnology Working Group (Hendren et al, 2015). Other articles in this series discuss data curation workflows (Powers et al, 2015) and data completeness and quality (Marchese-Robinson et al, 2016). …”

“…A variety of physical-chemical characterization information (such as the size, shape, purity, and surface properties) are included in different resources, but the methods and techniques used to perform the characterization are not always included in sufficient detail or standardized in a way that supports cross-study comparison of reported values (Stefaniak et al, 2013; Marchese-Robinson et al, 2016). Repositories collect and store information in support of their organization’s needs and goals, for which the role of nanomaterials data can differ considerably as indicated using the following examples.…”

“…1. Data that are measured, the information derived from those data, and the level of detail targeted for inclusion in a resource are all informed by the purpose for which data are being collected (Marchese-Robinson et al, 2016). Examples are provided below.…”