Your Spreadsheets Can Be FAIR: A Tool and FAIRification Workflow for the eNanoMapper Database

Abstract

The field of nanoinformatics is rapidly developing and provides data driven solutions in the area of nanomaterials (NM) safety. Safe by Design approaches are encouraged and promoted through regulatory initiatives and multiple scientific projects. Experimental data is at the core of nanoinformatics processing workflows for risk assessment. The nanosafety data is predominantly recorded in Excel spreadsheet files. Although the spreadsheets are quite convenient for the experimentalists, they also pose great challenges for the consequent processing into databases due to variability of the templates used, specific details provided by each laboratory and the need for proper metadata documentation and formatting. In this paper, we present a workflow to facilitate the conversion of spreadsheets into a FAIR (Findable, Accessible, Interoperable, and Reusable) database, with the pivotal aid of the NMDataParser tool, developed to streamline the mapping of the original file layout into the eNanoMapper semantic data model. The NMDataParser is an open source Java library and application, making use of a JSON configuration to define the mapping. We describe the JSON configuration syntax and the approaches applied for parsing different spreadsheet layouts used by the nanosafety community. Examples of using the NMDataParser tool in nanoinformatics workflows are given. Challenging cases are discussed and appropriate solutions are proposed.

Data Shepherding in Nanotechnology. The Exposure Field Campaign Template

“…By offering a consistent terminology throughout a subject, ontologies are used to facilitate communication between people and organizations [ 39 ]. The most used nano-specific ontologies are the NanoParticle Ontology (NPO) and the eNanoMapper (eNM) ontology [ 26 , 40 ]. All descriptors in the measurement and instrument tabs are semantically annotated (see Supplementary Materials, tab Dictionary ), to supplement the metadata.…”

“…All descriptors in the measurement and instrument tabs are semantically annotated (see Supplementary Materials, tab Dictionary ), to supplement the metadata. The descriptors can be annotated with several ontological terms, allowing the usage of numerous dictionaries to improve interoperability [ 40 ]. We combined and integrated different ontological IDs from diverse libraries when a single annotation from a source was missing.…”

FAIRification of nanosafety data to improve applicability of (Q)SAR approaches: A case study on in vitro Comet assay genotoxicity data

“…Since available Comet in vitro data have been generated in the last decade by different laboratories within different research initiatives, and reported in diverse formats and without the use of controlled vocabularies, many inconsistencies in the terminology exist ( e.g. , naming of materials, endpoint, methods, cell types, concentrations, time points, etc…) [65] . Examples of lack of controlled vocabularies and standardization in the reported data are displayed in Table 2 .…”

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“…The definition of the methods, protocols and parameters that guide data generation is in fact evolving together with knowledge on the determining factors of the physico-chemical and toxic effects. The eNanoMapper database and related tools are ongoing efforts to improve the FAIRness of data infrastructures (Kochev et al, 2020). One of the strengths of this FAIR-compliant data repository is the creation of a communication channel between laboratory experts and data modelling experts to maximize the understanding, exchange, availability and, ultimately, the reuse of data.…”