Frictionless Tabular Data Package for GC-MS Rose scent profile data for Data published in Nature genetics, June, 2018 & Science, July 2015

This dataset, in the form of a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holds the measurements of 61 known metabolites (all annotated with resolvable CHEBI identifiers and InChi strings), measured by gas chromatography mass-spectrometry (GC-MS) in 6 different Rose cultivars (all annotated with resolvable NCBITaxonomy Identifiers) and 3 organism parts (all annotated with resolvable Plant Ontology identifiers). The quantitation types are annotated with resolvable STATO terms.  

The data were extracted from:

• a supplementary material table, available from https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip  and published alongside the Nature Genetics manuscript identified by the following doi: https://doi.org/10.1038/s41588-018-0110-3, published in June 2018
• a supplementary material table available as a pdf from "Biosynthesis of monoterpene scent compounds in roses" by Magnard et al, Science  03 Jul 2015 identified by the following doi: https://doi.org/10.1126/science.aab0696

This dataset is used to demonstrate how to make data Findable, Accessible, Discoverable and Interoperable (FAIR) and how Frictionless Tabular Data Package representations can be easily mobilised for reanalysis and data science.

It is associated to the following project: https://github.com/proccaserra/rose2018ng-notebook with all the necessary information, executable code and tutorials in the form of Jupyter notebooks.