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https://github.com/ropensci/dataaimsr

Australian Institute of Marine Science (AIMS) Data Platform API Client which provides easy access to AIMS Data Platform scientific data and information.
https://github.com/ropensci/dataaimsr

aims australia data marine monitoring sst weather

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Australian Institute of Marine Science (AIMS) Data Platform API Client which provides easy access to AIMS Data Platform scientific data and information.

Host: GitHub
URL: https://github.com/ropensci/dataaimsr
Owner: ropensci
License: other
Created: 2019-08-05T01:10:45.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2023-05-31T05:35:34.000Z (over 1 year ago)
Last Synced: 2024-05-19T14:20:27.722Z (7 months ago)
Topics: aims, australia, data, marine, monitoring, sst, weather
Language: R
Homepage: https://docs.ropensci.org/dataaimsr/
Size: 24.4 MB
Stars: 4
Watchers: 6
Forks: 3
Open Issues: 1
Metadata Files:
- Readme: README.Rmd
- Contributing: CONTRIBUTING.md
- License: LICENSE

Awesome Lists containing this project

open-sustainable-technology - dataaimsr - Australian Institute of Marine Science (AIMS) Data Platform API Client which provides easy access to AIMS Data Platform scientific data and information. (Biosphere / Marine Life and Fishery)

README

        ---

output: github_document

---

```{r, include = FALSE}

stopifnot(require(knitr))

options(width = 90)

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/",

  out.width = "100%"

)

```

```{r, echo = FALSE}

version <- as.vector(read.dcf("DESCRIPTION")[, "Version"])

version <- gsub("-", ".", version)

```

# dataaimsr 

[![](https://badges.ropensci.org/428_status.svg)](https://github.com/ropensci/software-review/issues/428)

[![DOI](https://joss.theoj.org/papers/10.21105/joss.03282/status.svg)](https://doi.org/10.21105/joss.03282)

[![Lifecycle: maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html)

[![R build status](https://github.com/ropensci/dataaimsr/workflows/R-CMD-check/badge.svg)](https://github.com/ropensci/dataaimsr/actions)

[![Codecov test coverage](https://codecov.io/gh/ropensci/dataaimsr/branch/master/graph/badge.svg)](https://app.codecov.io/gh/ropensci/dataaimsr?branch=master)

![pkgdown](https://github.com/ropensci/dataaimsr/workflows/pkgdown/badge.svg)

[![license](https://img.shields.io/badge/license-MIT + file LICENSE-lightgrey.svg)](https://choosealicense.com/)

[![packageversion](https://img.shields.io/badge/Package%20version-`r version`-orange.svg)](commits/master)

[![Ask Us Anything

\!](https://img.shields.io/badge/Ask%20us-anything-1abc9c.svg)](https://github.com/ropensci/dataaimsr/issues/new)

![Open Source

Love](https://badges.frapsoft.com/os/v2/open-source.svg?v=103)

**Barneche DR, Coleman G, Fermor D, Klein E, Robinson T, Smith J, Sheehan JL, Dowley S, Ditton D, Gunn K, Ericson G, Logan M, Rehbein M** (2021). dataaimsr: An R Client for the Australian Institute of Marine Science Data Platform API which provides easy access to AIMS Data Platform. *Journal of Open Source Software*, **6:** 3282. doi: [10.21105/joss.03282](https://doi.org/10.21105/joss.03282).

## Overview 

The Australian Institute of Marine Science (AIMS) has a long tradition in

measuring and monitoring a series of environmental parameters along the

tropical coast of Australia. These parameters include long-term record of sea

surface temperature, wind characteristics, atmospheric temperature, pressure,

chlorophyll-a data, among many others. The AIMS Data Centre team has recently

developed the [AIMS Data Platform API][1] which is a *REST API* providing

JSON-formatted data to users. `dataaimsr` is an **R package** written to

allow users to communicate with the AIMS Data Platform API using an API key

and a few convenience functions to interrogate and understand the datasets

that are available to download. In doing so, it allows the user to

fully explore these datasets in R in whichever capacity they want (e.g.

data visualisation, statistical analyses, etc). The package itself contains

a `plot` method which allows the user to plot summaries of the different types

of dataset made available by the API. Below we provide a brief context about

the existing [Datasets](#datasets) that can be explored through `dataaimsr`.

[1]: https://open-aims.github.io/data-platform/

## Installation

### Requesting an AIMS Data Platform API Key

**AIMS Data Platform** requires an API Key for data requests, [get a key here](https://open-AIMS.github.io/data-platform/key-request).

The API Key can be passed to the package functions as an additional

`api_key = "XXXX"` argument. **However**, we strongly encourage users to

maintain their API key as a private locally hidden environment variable

(`AIMS_DATAPLATFORM_API_KEY`) in the `.Renviron` file for

automatic loading at the start of an R session. Please read this

[article](https://CRAN.R-project.org/package=httr/vignettes/secrets.html)

which details why keeping your API private is extremely important.

Users can modify their `.Renviron` file by adding the following line:

```

AIMS_DATAPLATFORM_API_KEY=XXXXXXXXXXXXX

```

The `.Renviron` file is usually stored in each users home directory:

System        | .Renviron file locations

--------------|-------------------------

MS Windows    | C:\Users\‹username›\.Renviron  or C:\Users\‹username›\Documents\.Renviron

Linux / MacOs | /home/‹username›/.Renviron

### Package

Type | Source | Command

---|---|---

Release | CRAN | Not yet available

Development | GitHub | `remotes::install_github("ropensci/dataaimsr")`

Development | rOpenSci | `install.packages("dataaimsr", repos = "https://dev.ropensci.org")`

## Usage

```{r, eval = FALSE}

# assumes that user already has API key saved to

# .Renviron

library(dataaimsr)

# summarised by series

# for all sites that contain data

# within a defined date range

sdf_b <- aims_data("temp_loggers", api_key = NULL,

                   summary = "summary-by-series",

                   filters = list("from_date" = "2018-01-01",

                                  "thru_date" = "2018-12-31"))

# downloads weather data from site Yongala

# within a defined date range

wdf_a <- aims_data("weather", api_key = NULL,

                   filters = list(site = "Yongala",

                                  from_date = "2018-01-01",

                                  thru_date = "2018-01-02"))

```

More comprehensive examples about how to navigate `dataaimsr` and interrogate

the datasets can be found on our [online vignettes][4].

[4]: https://ropensci.github.io/dataaimsr/articles/

## Datasets

Currently, there are two AIMS long-term monitoring datasets available to be

downloaded through `dataaimsr`:

### Northern Australia Automated Marine Weather And Oceanographic Stations

Automatic weather stations have been deployed by AIMS since 1980. Most of the

stations are along the Great Barrier Reef (GBR) including the Torres Strait in

North-Eastern Australia but there is also a station in Darwin and one at

Ningaloo Reef in Western Australia. Many of the stations are located on the

reef itself either on poles located in the reef lagoon or on tourist pontoons

or other structures. A list of the weather stations which have been deployed

by AIMS and the period of time for which data may be available can be

found on the [metadata][2] webpage. **NB:** Records may not be continuous for

the time spans given.

[2]: https://apps.aims.gov.au/metadata/view/0887cb5b-b443-4e08-a169-038208109466

### AIMS Sea Water Temperature Observing System (AIMS Temperature Logger Program)

The data provided here are from a number of sea water temperature monitoring

programs conducted in tropical and subtropical coral reefs environments around

Australia. Data are available from approximately 80 GBR sites, 16 Coral Sea

sites, 7 sites in North West Western Australia (WA), 8 Queensland regional

ports, 13 sites in the Solitary Islands, 4 sites in Papua New Guinea and 10

sites in the Cocos (Keeling) Islands. Data are obtained from in-situ data

loggers deployed on the reef. Temperature instruments sample water

temperatures every 5-10 minutes (typically) and are exchanged and downloaded

approximately every 12 months. Temperature loggers on the reef-flat are

generally placed just below Lowest Astronomical Tide level. Reef-slope (or

where specified as Upper reef-slope) generally refers to depths 5--9 m while

Deep reef-slope refers to depths of ~20 m. For more information on the dataset

and its usage, please visit the [metadata][3] webpage.

[3]: https://apps.aims.gov.au/metadata/view/4a12a8c0-c573-11dc-b99b-00008a07204e 

## License

`dataaimsr` is provided by the [Australian Institute of Marine Science](https://www.aims.gov.au) under the MIT License ([MIT](https://opensource.org/license/mit/)).

## Code of Conduct

Please note that this package is released with a

[Contributor Code of Conduct](https://ropensci.org/code-of-conduct/).

By contributing to this project, you agree to abide by its terms.

## AIMS R package logos

Our R package logos use a watercolour map of Australia, obtained with the [ggmap](https://CRAN.R-project.org/package=ggmap) R package, which downloads original map tiles provided by [Stamen Design](https://stamen.com/), under [CC BY 3.0](https://creativecommons.org/licenses/by/3.0), with data from [OpenStreetMap](https://www.openstreetmap.org/), under [CC BY SA](https://creativecommons.org/licenses/by-sa/3.0).