-
Notifications
You must be signed in to change notification settings - Fork 0
/
README.Rmd
73 lines (56 loc) · 3.47 KB
/
README.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
---
output: github_document
---
# manyhealth <img src="man/figures/manyhealthLogo.png" align="right" width="220"/>
<!-- badges: start -->
[](https://www.tidyverse.org/lifecycle/#experimental)
<!-- badges: end -->
manyhealth is a data package in the [many packages](https://github.com/globalgov/) universe.
It currently includes an ensemble of datasets on international health instruments
and actors in global health governance (states, IGOs, NGOs, and other private actors).
Please also check out [`{manydata}`](https://github.com/globalgov/manydata) for more about the other packages in the 'many packages' 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, eval = FALSE}
# install.packages(remotes)
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("manyhealth") # this downloads and installs the named package
```
## Data included
Once you have installed the package, you can see the different datasets included in the specific datacube in the package using the following function.
```{r datasets, eval = FALSE}
manydata::call_sources("manyhealth", "agreements")
```
Working with ensembles 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).
While some packages in the many universe can and do include novel data,
much of what they offer involves standing on the shoulders of giants. Packages from the
many universe 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 using the function below.
``` {r cites}
citation("manyhealth")
```
## 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/manyhealth/issues) for us, or by
forking, further developing the package yourself, and opening a [pull
request](https://github.com/globalgov/manyhealth/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 ecosystem,
[manypkgs](https://github.com/globalgov/manypkgs) includes a number of
functions that make it easy to create a new package from the many universe
and populate with clean, consistent global governance data.
If you have any other ideas about how this package or the manydata
ecosystem more broadly might better facilitate your empirical analysis,
we’d be very happy to hear from you.