Fire debris is often recovered as part of a fire scene investigation to determine whether an ignitable liquid might be present which may be evidence of a deliberate fire. The analysis of fire debris produces chromatograms that a forensic chemist uses to determine whether or not an ignitable liquid may be present. Currently there are very few publicly available data sets that can be used for training and statistical modelling in this area. The data set in this paper has been prepared with these two applications in mind and covers a wide range of ignitable liquids available in the UK. We created a data set of 35 ignitable liquids including petrol (gasoline), light, medium and heavy petroleum distillates (i.e diesel) from several retailers. Each ignitable liquid was systematically evaporated to produce six additional samples. Each sample was repetitively analysed to provide an overall data set of 751 analytical outputs (including chromatograms). Each data sample is expressed in multiple formats and the metadata containing any data used in the production of the samples is included. The folder and file names are designed to avoid misplacements and to manipulate folders and files systematically using computer code.
Keywords: GCMS; Ignitable Liquids; Machine learning data; Statistical modelling data.
© 2022 The Author(s).