Traditionally, chemists share experimental data about chemicals as Supporting Information in their journal articles, theses, or other publications. The Supporting Information is often locked in PDF format and usually does not include the original data files for validation and reuse. Making chemical data more findable, accessible, interoperable, and reusable (FAIR) will enhance reproducibility and facilitate computational use of data for machine learning and AI research. In this workshop, we will explore how to prepare chemical data, especially properties and spectral data, for dissemination with publications and via data repositories. A set of workflow charts and check lists will be provided for attendees to guide their practices in documenting, organizing, and sharing chemical data packages. The workshop will be most applicable for students and researchers working on synthesis and characterization of small molecules, but all researchers in chemistry and related fields are welcome to attend.
