The main purpose of this repo is to build
AusTraits, a curated database of traits for the Australian flora. It contains code and data to build the harmonised AusTraits database outputs. So, the intended audiences are those who are interested in building AusTraits from scratch, or contributing data to AusTraits.
Those interested in simply using data from AusTraits, should visit and download the compiled resource from the versioned releases archived on Zenodo at doi: 10.5281/zenodo.3568417.
The repo is partway between a compendium and an R package. It is structured like an R package, and contains code that can be installed as a package. This allows us to use some of R’s package management tools:
It also contains data for rebuilding AusTraits. A key goal for us was to make the process for harmonising different datasets as transparent as possible. Our workflow is therefore fully-reproducible and open, meaning it exposes the decisions made in the processing of data into a harmonised and curated dataset (Figure 1); and can also be rerun by others.
We envision AusTraits as an ongoing collaborative community resource that:
Below are some of the ways you can contribute.
*Please note that the AusTraits project is released with a Contributor Code of Conduct. By contributing to this project you agree to abide by its terms.
We gladly accept new data contributions to AusTraits. If you would like to contribute data, the requirements are:
If you want to contribute data, please review the instructions here on how to contribute data.
Data contributors and data users who are less familiar with the AusTraits format and code than the custodians may determine that important descriptions or steps are omitted from this documentation file. We welcome additions and edits that make using the existing data or adding new data easier for the community.
If you notice a possible error in AusTraits, please post an issue on GitHub. If you can, please provide code illustrating the problem.
If you would like to value-add to AusTraits in some other way, please get in contact with an idea or offer of time.
A core initiative of AusTraits from 2021-2023 is to refine and better document the trait names, definitions, and values that are the direct link from each contributor’s dataset to the harmonised database. This effort is funded by an Australian Research Data Commons (ARDC) grant through their Australian Data Partnerships program. It includes both a review of definitions by the core AusTraits team and a series of workshops to discuss clusters of related trait definitions.
The goal is to link as many trait names as possible to established, published definitions (e.g. in traits handbook, review paper on a method, manuscripts regularly cited as the standard for a specific trait). In addition, the list of allowable values for each categorical trait will be reviewed and revised.
If you are interested in contributing expertise to the revision of a given trait (or cluster of related traits), please contact us.
In this section we describe how to build the harmonised dataset. By “compiling” we mean transforming data from all the different studies into a harmonised common format. As described above and depicted in Figure 1, AusTraits is built so that you can rebuild the database from its parts at any time. This means that decisions made along the way, in how data are transformed or encoded, can be inspected and modified. And new data is easily incorporated.
The first step to compile AusTraits is to download a copy of the austraits.build repository from Github. Then open up the Rstudio project, or open R into the right repo directory.
To check you have the right packages installed, you can use the
devtools package to run:
# install.packages("devtools) # install devtools if needed devtools::install_deps()
This command checks that the required packages, listed in the file
DESCRIPTION, are available in your local machine.
One of the packages that will be installed with the above is
remake. This package manages the compiling, and also helps streamline the amount of recompiling needed when new sources are added.
Running the following command will rebuild AusTraits and save the assembled database into an RDS file located in
Remake can also load the compiled dataset directly into R by calling:
austraits <- remake::make("austraits")