Abstract
Gas chromatography hyphenated with ion mobility spectrometry (GC-IMS) is an emerging benchtop technique for sensitive and selective detection of volatile organic compounds. It is commonly used for non-target screening (NTS) of complex sample materials, such as food products. Resulting spectra are used as "fingerprints" for multivariate chemometric data analysis to extract information. This has been successfully applied in the field of food fraud detection in several published studies. The presented dataset contains GC-IMS measurements of extra virgin olive oil samples from Spain, Italy, and Greece. It allows classification and class modelling to differentiate geographic origins and was used in the associated publication gc-ims-tools, a new Python package for chemometric analysis of GC-IMS data (https://doi.org/10.1016/j.foodchem.2022.133476) as an example to demonstrate the functionality.