Making Electronic Supplementary Information (ESI) Machine-Readable Case Study

This case study explores the challenges of losing valuable raw data when it is embedded within PDFs as part of supplementary information (ESIs). To address this, data was extracted from the supplementary information of the paper titled "Towards the Prediction of Antimicrobial Efficacy for Hydrogen Bonded, Self-Associating Amphiphiles" (http://doi.org/10.1002/cmdc.202000533) and converted into JSON format. The process was carefully documented to showcase how such data can be transformed into a more machine-readable format, improving accessibility and usability for further analysis.