AMView - Visualize AMU Data

This dashboard is an RShiny application, developed as an R package, that visualizes antimicrobial use (AMU) data in animals. The application was developed as part of the DigiVet project.

This repository is a fork of the source code as delivered to the funders at the end of the project via Zenodo. The repository found at https://github.com/SVA-SE/AMView (from which this repo is forked) will see continued development after the project is concluded. The DOI for the release is: DOI: 10.5281/zenodo.10400887

The package also has functionality to randomly generate artificial to use for app showcasing. The parameters for the data generation are currently set so that the generated data will loosely imitate official AMU statistics from the Swedish cattle sector. The data format follows a common AMU data structure which has been developed within the DigiVet project. An instruction and template for the common data structure can be downloaded within the application, or viewed in this repository under inst/extdata/content_mapping_AMU.xlsx.

Installing and running AMView

Artificial data

If you want to run the app with the pre-loaded artificial data, the easiest installation method is directly through R:

remotes::install_github("digivet-consortium/AMView")

You can then run the Shiny app like this:

AMView::run_app()

which should launch a local Shiny server and automatically open a browser window with the app.

With your own data

Currently, AMView only supports reading data which is "baked into" the R package itself. Therefore, if you want to run the app with your own data you will need to make modifications to the source code. To do so, follow these steps:

Clone this repository. Or, if you want to save your modifications, create a fork of this repo and clone that fork.
In your local copy, replace the CSV file under inst/extdata/amu.csv with one that contains the data you want to visualize. Follow the specification in inst/extdata/content_mapping_AMU.xlsx to make sure the columns of the CSV are named and formatted correctly.
- Note that while the original CSV is semicolon-separated, the replacement can have any delimited text format that is guessable by the data.table R package as long as the file has the name amu.csv.
Install the package. The easiest way is to navigate to the root of the repo, and run the following in R:
```
devtools::install_local(force = TRUE)
```
or, if you have GNU make (or Make for Windows), you can open a terminal/command line and type:
```
make install
```
Run the application from R in the same way as above:
```
AMView::run_app()
```