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README.Rmd
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README.Rmd
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---
output: github_document
---
# manyenviron <img src="man/figures/manyenviron_hexlogo.png" align="right" width="220"/>
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[](https://www.tidyverse.org/lifecycle/#experimental)
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manyenviron is a data package in the many universe of packages.
It currently includes an ensemble of datasets on international environmental agreements,
and [states](https://github.com/globalgov/manystates)' membership or other relationships to those agreements.
Please also check out [`{manydata}`](https://github.com/globalgov) for more information about the other packages in the many universe.
## How to install
We've made it easier than ever to install and start analysing global governance data in R.
Simply install the core package, [manydata](https://github.com/globalgov/manydata), as follows,
and then you can discover, install and update various "many" packages from the console.
```{r install, eval = FALSE}
remotes::install_github("globalgov/manydata") # this installs our core package, the only one you need to do independently
manydata::call_packages() # this prints a list of the publicly available data packages currently available
manydata::call_packages("manyenviron") # this downloads and installs the named package
```
## Data included
Once you have installed the package, you can see the different datasets included in a specific datacube in the {`manyenviron`} package using the following function.
```{r datasets, eval = FALSE}
manydata::call_sources("manyenviron", "agreements")
```
Working with an ensemble of related data has many advantages for robust analysis.
Just take a look at our vignettes [here](https://globalgov.github.io/manydata/articles/user.html).
## Many packages
The development of [many packages](https://github.com/globalgov/manydata) is aimed
at collecting, connecting, and correcting network data across issue-domains of
global governance.
While some many packages can and do include novel data,
much of what they offer involves standing on the shoulders of giants.
Many packages endeavour to be as transparent as possible about where data comes from,
how it has been coded and/or relabeled, and who has done the work.
As such, we make it easy to cite both the particular datasets you use
by listing the official references in the function above,
as well as the package providers for their work assembling the data
by using the function below.
```{r cites}
citation("manyenviron")
```
## Contributing
[`{manypkgs}`](https://github.com/globalgov/manypkgs) also makes it easy to contribute in lots of different ways.
If you have already developed a dataset salient to this package,
please reach out by flagging this as an [issue](https://github.com/globalgov/manyenviron/issues) for us,
or by forking, further developing the package yourself, and opening a [pull request](https://github.com/globalgov/manyenviron/pulls)
so that your data can be used easily.
If you have collected or developed other data that may not be best for this package,
but could be useful within the wider universe,
[`{manypkgs}`](https://github.com/globalgov/manypkgs) includes a number of functions that make it easy
to create a new "many" package and populate with clean, consistent global governance data.
If you have any other ideas about how this package or the manydata universe more broadly
might better facilitate your empirical analysis, we'd be very happy to hear from you.