Rationale

This repository contains the functionality to standardize the occurrences data of RATO vzw to a Darwin Core Archive that can be harvested by a GBIF IPT.

Workflow

fetch data from WFS → save them as local source data → Darwin Core mapping script → generated Darwin Core files

Published dataset

• Dataset on the IPT
• Dataset on GBIF

Repo structure

The repository structure is based on Cookiecutter Data Science and the Checklist recipe. Files and directories indicated with GENERATED should not be edited manually.

├── README.md              : Description of this repository
├── LICENSE                : Repository license
├── rato-occurrences.Rproj : RStudio project file
├── .gitignore             : Files and directories to be ignored by git
│
├── .github                
│   ├── PULL_REQUEST_TEMPLATE.md : Pull request template
│   └── workflows
│   │   ├── fetch-data.yaml    : GitHub action to fetch raw data
│   │   └── mapping_and_testing.yaml : GitHub action to map data to DwC and perform some tests on the Dwc output
|
├── src
│   ├── fetch_data.Rmd     : Fetching data script
│   ├── dwc_mapping.Rmd    : Darwin Core mapping script
│   ├── run_fetch_data.R   : R script to run code in fetch_data.Rmd in an automatic way within a GitHub action
│   ├── run_dwc_mapping.R  : R script to run code in dcw_mapping.Rmd in an automatic way within a GitHub action
│   └── install_packages.R : R script to install all needed packages
|
└── data
│   └── processed          : Darwin Core output of mapping script GENERATED

Installation

1. Clone this repository to your computer
2. Open the RStudio project file
3. Run install_packages.R to install any required packages
4. Open fetch_data.Rmd R Markdown file in RStudio to fetch data manually
5. Open the dwc_mapping.Rmd R Markdown file in RStudio to map data to DwC manually
6. Click Run > Run All to generate the processed data

License

MIT License for the code and documentation in this repository. The included data is released under another license.