Commit ecda21a5 authored by Luke Johnston's avatar Luke Johnston
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remove mit license since only cc-by is needed. Simplify acknowledgements section

parent 033d8ba4
MIT License
Copyright (c) 2020 Luke W. Johnston
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
......@@ -4,6 +4,5 @@ Copyright (c) 2020 Luke W. Johnston
<a rel="license" href="https://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a>
The course material is licensed under the
[Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/)
and the course code is licensed under a [MIT License](https://gitlab.com/rostools/r-cubed-intermediate/-/blob/main/LICENSE-MIT.md).
The course material and code is licensed under the
[Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).
# Reproducible Research in R: An intermediate workshop on modern approaches and workflows to processing data <img src="images/apple-touch-icon.png" align="right" height=100/>
[![Netlify Status](https://api.netlify.com/api/v1/badges/b744cd78-5e3c-4d19-924f-4c249a294e5a/deploy-status)](https://app.netlify.com/sites/r-cubed-intermediate-rostools/deploys)
[![pipeline status](https://gitlab.com/rostools/r-cubed-intermediate/badges/main/pipeline.svg)](https://gitlab.com/rostools/r-cubed-intermediate/-/commits/main)
[![License: CC BY 4.0](https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4061900.svg)](https://doi.org/10.5281/zenodo.4061900)
## Description
......
......@@ -78,9 +78,8 @@ to make comments and give feedback for the material.
<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/80x15.png" /></a>
The course material is licensed under the
The course is licensed under the
[Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/)
and the course code is licensed under a [MIT License](https://gitlab.com/rostools/r-cubed-intermediate/-/blob/main/LICENSE-MIT.md),
so the material can be used, re-used, and modified,
as long as there is attribution to this source.
......@@ -99,19 +98,13 @@ session material.
## Acknowledgements
Some of the material was taken and modified from multiple sources, including:
- [UofTCoders Reproducible Quantitative Methods for EEB](https://uoftcoders.github.io/rcourse/)
- [Software and Data Carpentry](https://carpentries.org/) workshop material
- [UofTCoders material](https://uoftcoders.github.io/studyGroup/lessons/)
and [AU CRU material](https://au-cru.github.io/site/)
- From version 1 of the [*"Reproducible Quantitative Methods: Data analysis workflow using R"*](https://v1--dda-rcourse.netlify.com/) course
The course material also draws inspiration from these excellent resources:
The course material draws inspiration from these excellent resources:
- [R for Data Science](https://r4ds.had.co.nz/)
- [Advanced R](https://adv-r.hadley.nz/)
- [R Packages](https://r-pkgs.org/)
- [UofTCoders Reproducible Quantitative Methods for EEB](https://uoftcoders.github.io/rcourse/)
- [Software and Data Carpentry](https://carpentries.org/) workshop material
The [Danish Diabetes Academy](https://www.danishdiabetesacademy.dk/) hosted,
organized, and sponsored this course. A huge thanks to them
......
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