Data accessibility in the chemical sciences: an analysis of recent practice in organic chemistry journals.

Abstract

The discoverability and reusability of data is critical for machine learning to drive new discovery in the chemical sciences, and the 'FAIR Guiding Principles for scientific data management and stewardship' provide a measurable set of guidelines that can be used to ensure the accessibility of reusable data. We investigate the data practice of researchers publishing in specialist organic chemistry journals, by analyzing the outputs of 240 randomly selected research papers from 12 top-ranked journals published in early 2023. We investigate compliance with recommended (but not compulsory) data policies, assess the accessibility and reusability of data, and if the existence of specific recommendations for publishing NMR data by some journals supports author compliance. We find that, although authors meet mandated requirements, there is very limited compliance with data sharing policies that are only recommended by journals. Overall, there is little evidence to suggest that authors' publishing practice meets FAIR data guidance. We suggest first steps that researchers can take to move towards a positive culture of data sharing in organic chemistry. Routine actions that we encourage as standard practice include deposition of raw and metadata to open repositories, and inclusion of machine-readable structure identifiers for all reported compounds.