README.Rmd

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# pipedat <a href='https://github.com/Ecosystem-Assessments/pipedat'><img src='man/figures/logo.png' align="right" height="175" /></a>

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*pipedat* is a R package that provides analytical pipelines to access, load, and format a variety of data from multiple sources programatically. The goal of *pipedat* is to enhance the capacity scientists, planners and the wider public to prepare and perform complex and reproducible ecosystem-scale assessments requiring the integration of multiple spatial datasets such as cumulative effects assessments in the context of ecosystem-based management, and Marxan analyses for the establishment of individual and networks of MPAs. In its current format, *pipedat* is strictly experimental and in development. We are however hoping to further develop this initiative in the hopes of greatly enhancing the efficiency, transparency and reproducibility of large-scale environmental assessments. 

## Installation

The easiest way to install `pipedat` is to use [`remotes`](https://cran.r-project.org/package=remotes):

``` r
install.packages("remotes")
remotes::install_github("Environment-Health/pipedat")
```

Then, load it:

```r
library(pipedat)
```

## Main features 

The `pipedat` package is built around function called `pipedat()` that is used to access, load and format a wide variety of data; this function calls on a series of individual scripts built to access data programmatically and reproducibly, which we refer to as *data pipelines*. Individual data pipelines are executed by using their *unique identifier*, which are specific to the `pipedat` package. The full list of data pipelines available can be viewed with the `pipelist()` function: 

```r
# View list of pipelines 
# pipelist()

# Download and format a single dataset 
# pipedat("a3jsd4jh")

# Download and format multiple datasets
# pipedat(c("a3jsd4jh","a8732975y","soif8yiao"))
```

The `pipedat()` function will export the raw and formatted data in the folder 'project-data/pipedat/'.

## List of pipelines 

```{r echo = FALSE}
pipedat::pipelist()
```

## How to contribute

External contributors are welcome to contribute data pipelines to this package. Simply fork the [public repo]() and create your own data pipeline. The `pipenew()` function creates a `dp_#####.R` template for you to use to create a new data pipeline with a unique id. Create a pull request for us to review the data pipeline for inclusion in the package. 

A single pull request per pipeline should be created, and merged pull requests should be squashed into a single commit.