RDF Linked Data representation of GC-MS data from the 'Rose Genome' article published in Nature genetics, June, 2018
| Main Authors: | Philippe Rocca-Serra, Susanna Assunta Sansone |
|---|---|
| Format: | info dataset eJournal |
| Bahasa: | eng |
| Terbitan: |
, 2019
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/3560778 |
Daftar Isi:
- This dataset corresponds to the RDF Linked Data representation of 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. Most of the semantics resources belong to the OBO foundry. The transformation to RDF was performed on a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holding the data 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. This supplementary material table was deposited to Zenodo and is identified by the following doi: https://doi.org/10.5281/zenodo.2598799 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.