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README.Rmd
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README.Rmd
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---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# RMAVIS
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[]()
[](https://www.repostatus.org/#active)
[](https://zenodo.org/badge/latestdoi/722095560)
[](https://joss.theoj.org/papers/460c6f934a108fcf5a16d0f2ab77492e)
[](https://opensource.org/license/lgpl-3-0)
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## Overview
The **R** **M**odular **A**nalysis of **V**egetation **I**nformation **S**ystem
(`RMAVIS`) R Shiny web application is a tool to assist in the assignment of
vegetation plot sample data to GB National Vegetation Classification units,
with additional exploratory analyses.
We will update and improve `RMAVIS` over time in response to user feedback and hope it acts as a useful
tool for the GB ecology and conservation community.
## Structure
There are 5 main sections in `RMAVIS` at present.
**Home** - Provides outlining information.
**Application** - The core of `RMAVIS`, containing the actual application.
**NVC Lookup** - Contains a searchable table of NVC codes and names, which can be used to retrieve the full name of an NVC community using an NVC community or sub-community code.
**Documentation** - Provides a more detailed overview of the underlying methods, data sources, and usage instructions.
**Privacy** - A privacy notice.
## Installation
In addition to accessing `RMAVIS` via the web `RMAVIS` can be run on your personal device and installed as an R package.
### Running Locally
To run RMAVIS locally take the following steps.
1. Ensure R >= 4.4 is installed.
2. Clone the repository from https://github.com/NERC-CEH/RMAVIS.
3. Navigate to the RMAVIS folder.
4. From the R terminal:
a. Install `{renv}` with `install.packages("renv")`.
b. Run `renv::activate()` then `renv::restore()` to install the required dependencies.
d. Run `shiny::runApp("app.R")` to start the app.
### Package Installation
To install `RMAVIS` as a package run `remotes::install_github("NERC-CEH/RMAVIS")`.
## Reccomended Citation
To reference `RMAVIS` please cite the JOSS paper (in prep)...
```
```
Alternatively, use either the Zenodo DOI for all versions as follows:
Marshall, Z., Smart, S. M., Harrower, C., & Marrs, R. (2024). RMAVIS. Zenodo.
https://zenodo.org/doi/10.5281/zenodo.10818640
or the DOI associated with a particular release.
## Feedback
To report a bug please submit a Github issue [here](https://github.com/NERC-CEH/RMAVIS/issues),
fill out the feedback form [here](https://forms.office.com/e/ByLgRPjT8J),
or send an email to [Zeke Marshall](mailto:zekmar@ceh.ac.uk?subject=RMAVIS).
## Acknowledgements
The development of this app was partly supported by the UK‐SCAPE
programme delivering National Capability (NE/R016429/1) funded by the
Natural Environment Research Council.
We would like to thank Lindsay Maskell, Lucy Ridding, Barry Jobson,
Colin Conroy, Andy McMullen, John Handley, Michael Tso, Simon Rolph,
Cristina Martin Hernandez, and George Linney for testing RMAVIS.
We would also like to thank Rob Marrs for his ongoing collaboration
with the development of NVC assignment methodologies and the
University of Liverpool for their ongoing support.