[ Project Lead ] @annakrystalli
[ GitHub Repo ] https://github.com/annakrystalli/rmacroRDM
[ Track ] Tools: you are building a tool others can help you build
[ Level ] Intermediate
[ Timezone ] BST
Description
The rmacroRDM R package contains functions to help with the compilation of macroecological datasets. It compiles datasets into a master database of individual observations and checks, separates and stores taxonomic and metadata information on observations, variables and datasets. It therefore aims to ensure full traceability of data points and robust quality control, all the way through to extracted analytical datasets.
Want to Contribute?
Join us at the Global Sprint June 2-3. Leave a comment in this issue to let the project lead know you're interested in contributing during #mozsprint 2016!
Note to the Project Lead
Congrats, @annakrystalli! This is your official project listing for the Mozilla Science Global Sprint 2016. To confirm your submission, please complete the following:
Do you want to become a featured project? 🎉
Here are some exercises that will help your project be more inviting to new contributors. We hope you'll try to complete some of these as you prepare for #mozsprint.
If you complete all the exercises, your project will be eligible to be featured in our collection of open source science projects! Once you've finished this list, contact @acabunoc to submit your project for review.
[ Project Lead ] @annakrystalli
[ GitHub Repo ] https://github.com/annakrystalli/rmacroRDM
[ Track ] Tools: you are building a tool others can help you build
[ Level ] Intermediate
[ Timezone ] BST
Description
The rmacroRDM R package contains functions to help with the compilation of macroecological datasets. It compiles datasets into a master database of individual observations and checks, separates and stores taxonomic and metadata information on observations, variables and datasets. It therefore aims to ensure full traceability of data points and robust quality control, all the way through to extracted analytical datasets.
Want to Contribute?
Join us at the Global Sprint June 2-3. Leave a comment in this issue to let the project lead know you're interested in contributing during #mozsprint 2016!
Note to the Project Lead
Congrats, @annakrystalli! This is your official project listing for the Mozilla Science Global Sprint 2016. To confirm your submission, please complete the following:
Do you want to become a featured project? 🎉
Here are some exercises that will help your project be more inviting to new contributors. We hope you'll try to complete some of these as you prepare for #mozsprint.
If you complete all the exercises, your project will be eligible to be featured in our collection of open source science projects! Once you've finished this list, contact @acabunoc to submit your project for review.