Major update

Author: jdberson

.gitignore

@@ -3,3 +3,5 @@
 .Rdata
 .httr-oauth
 .DS_Store
+data-raw/dungfauna_occurrence.csv
+data-raw/dungfauna_event.csv

DESCRIPTION

@@ -12,7 +12,8 @@ Authors@R:
              role = "aut",
              email = "jake.manger@uwa.edu.au",
              comment = c(ORCID = "0000-0002-0686-4788")))
-Description: What the package does (one paragraph).
+Description: This is a data package with data on occurrence and abundance 
+             records for deliberately introduced dung beetles in Australia.
 License: CC BY 4.0
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
@@ -26,19 +27,20 @@ Depends:
 LazyData: true
 Imports:
     directlabels (>= 2021.1.13),
-    dplyr (>= 1.1.0),
-    ggplot2 (>= 3.4.1),
+    dplyr (>= 1.1.2),
+    ggplot2 (>= 3.4.3),
     ggtext (>= 0.1.2),
-    htmlwidgets (>= 1.5.4),
+    htmlwidgets (>= 1.6.2),
     leafem (>= 0.2.0),
-    leaflet (>= 2.1.1),
+    leaflet (>= 2.1.2),
     leaflet.extras (>= 1.0.0),
     lubridate (>= 1.9.2),
     RColorBrewer (>= 1.1.3),
-    scales (>= 1.2.0),
+    scales (>= 1.2.1),
+    sf (>= 1.0.14),
     shinyalert (>= 3.0.0),
     shinyjs (>= 2.1.0),
-    shinyWidgets (>= 0.7.1),
-    stringr (>= 1.5.0)
-Remotes: 
-    jakemanger/leaflet.extras
+    shinyWidgets (>= 0.7.6),
+    stars (>= 0.6.3),
+    stringr (>= 1.5.0),
+    tidyr (>= 1.3.0)

R/data.R

@@ -2,67 +2,89 @@
 #'
 #' Within Australia, the next smaller administrative unit after country is
 #' State / Territory, after which comes a 'Local Government Area'. These are
-#' equivalent to the Darwin Core terms stateProvince and county.
+#' equivalent to the Darwin Core terms stateProvince and county respectively.
+#' We have included these data within the package to aid with assigning the
+#' county, stateProvince, country and countryCode fields to the dung fauna data.
 #'
 #' The Australian Bureau of Statistics (ABS) provides shapefile data for local
 #' government areas in Australia which also includes the associated higher
 #' level geographies (State / Territory and Country). More information is here:
 #' \url{https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files}.
 #'
-#' The download link for the raw data is (Local Government Areas - 2022 -
-#' Shapefile in GDA2020):
-#' https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files/LGA_2022_AUST_GDA2020_SHP.zip
-"county_stateProvince_aus"
-
-
 #' The data downloaded from ABS has been slightly modified with empty geometries
 #' removed, terms renamed to Darwin Core terms, and not needed fields removed.
-#' @format An \code{sf} POLYGON object with 547 features and 4 fields:
+#'
+#' @format An \code{sf} MULTIPOLYGON object with 547 features and 4 fields:
 #' \describe{
-#'   \item{datasetID}{\url{http://rs.tdwg.org/dwc/terms/datasetID}}
-#'   \item{locationID}{\url{http://rs.tdwg.org/dwc/terms/locationID} The
-#'   location identifier given in the data set.}
-#'   \item{basisOfRecord}{\url{http://rs.tdwg.org/dwc/terms/basisOfRecord} We
-#'   have included two values. "PreservedSpecimen" has been used where the
-#'   record came from a trap collection. "HumanObservation" has been used where
-#'   the record came from the supplementary survey.}
-#'   \item{recordedBy}{\url{http://rs.tdwg.org/dwc/iri/recordedBy} All records
-#'   were recorded by the Department of Primary Industries and Regional
-#'   Development ("DPIRD")}
-#'   \item{occurrenceStatus}{\url{http://rs.tdwg.org/dwc/iri/occurrenceStatus}
-#'   Either "Present" or "Absent".}
-#'   \item{samplingProtocol}{\url{http://rs.tdwg.org/dwc/terms/samplingProtocol}
-#'   "CSIRO pitfall trap baited with 1kg dung" describes records from a trap
-#'   collection. "Dung pads in paddock searched for dung beetles" describes
-#'   records from the supplementary survey.}
-#'   \item{scientificName}{\url{http://rs.tdwg.org/dwc/terms/scientificName}
-#'   Sixteen levels, including 13 species level identifications (Bubas bison,
-#'   Copris hispanus, Coelostoma australe, Euoniticellus fulvus, E. intermedius,
-#'   E. pallipes, Heteronychus arator, Onitis alexis, Onitis aygulus,
-#'   Onthophagus binodis, O. ferox, O. taurus, O. vermiculatus), two genus level
-#'   identifications (Aphodius and Hister) and one subfamily level
-#'   identification (Aphodiinae)}
-#'   \item{identifiedBy}{\url{http://rs.tdwg.org/dwc/terms/identifiedBy} All
-#'   specimens were identified by DPIRD staff or DPIRD contracted consultants}
-#'   \item{verbatimEventDate}{
-#'   \url{http://rs.tdwg.org/dwc/terms/verbatimEventDate} Date or date-time
-#'   recorded by DPIRD. This is the date/date-time that the traps were collected
-#'   or the human observation conducted. Note that not all records include the
-#'   time. Times shown are in the local time zone (Australia/Perth)}
-#'   \item{verbatimLatitude}{\url{http://rs.tdwg.org/dwc/terms/verbatimLatitude}
-#'   The Latitude recorded by DPIRD. Note that at all trapping sites two traps
-#'   were placed 10-20 m apart. For some locations/records the coordinates of
-#'   the individual trap have been recorded, otherwise just one value for both
-#'   traps is given.}
-#'   \item{verbatimLongitude}{
-#'   \url{http://rs.tdwg.org/dwc/terms/verbatimLongitude}
-#'   The Longitude recorded by DPIRD.}
-#'   \item{individualCount}{\url{http://rs.tdwg.org/dwc/terms/individualCount}
-#'   Note that records from the supplementary survey have been assigned a
-#'   count value of NA.}
-#'    \item{occurrenceRemarks}{
-#'    \url{http://rs.tdwg.org/dwc/terms/occurrenceRemarks} All NAs. Included
-#'    here to match other data sets.}
+#'   \item{county}{\url{http://rs.tdwg.org/dwc/terms/county} Local government
+#'   areas in Australia, nested within stateProvince. The geometry provides the
+#'   boundaries of these areas.}
+#'   \item{stateProvince}{\url{http://rs.tdwg.org/dwc/terms/stateProvince} The
+#'   State or Territory within which the county / local government area is
+#'   located.}
+#'   \item{country}{\url{http://rs.tdwg.org/dwc/terms/country} All features are
+#'   within Australia}
+#'   \item{countryCode}{\url{http://rs.tdwg.org/dwc/terms/countryCode} The code
+#'   used for Australia}
+#'   \item{geometry}{\url{http://rs.tdwg.org/dwc/terms/geometry} Multipolygons
+#'   providing the boundaries for county / local government area.}
+#' }
+#' @source <https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files/LGA_2022_AUST_GDA2020_SHP.zip>
+"county_stateProvince_aus"
+
+
+#' A dataset of deliberately introduced dung beetle records (long format)
+#'
+#' These data provide counts of deliberately introduced dung beetles in
+#' Australia for 23 species and 10,272 sampling events with each row
+#' representing the data for one species from one sampling event. Column
+#' headings use the Darwin Core terms, except for column headings that include
+#' an underscore (_). In the latter case, the underscore has been included to
+#' indicate that a non Darwin Core term has been used.
 #'
+#' The data are fully documented in Berson et al (submitted).
+#'
+#' @format A data frame with 58 variables and 232,599 rows
+"dungfauna_occurrence"
+
+
+
+#' A dataset of deliberately introduced dung beetle records (wide format)
+#'
+#' These data provide counts of deliberately introduced dung beetles in
+#' Australia for 10,272 sampling events with each row representing one
+#' sampling event. Column headings use the Darwin Core terms, except for columns
+#' showing species counts (columns from "Bubas bison" to "Sisyphus spinipes")
+#' and column headings that include an underscore (_). In the latter case, the
+#' underscore has been included to indicate that a non Darwin Core term has been
+#' used. The variables are as documented in Berson et al (submitted) except for
+#' the variables "Bubas bison" to "Sisyphus spinipes". See below under
+#' **Format**.
+#'
+#' The values in the columns "Bubas bison" to "Sisyphus spinipes"
+#' represent the number of individuals of the species collected by the method
+#' described in the column samplingProtocol, except where the value in
+#' eventRemarks is "Species counts are visual activity ratings". In the latter
+#' case the values range from 0 to 5, with 0 indicating the species was not
+#' found, and 5 indicating that the species was found in almost every dung pad
+#' searched.
+#'
+#' @format A data frame with 64 variables and 10,113 rows:
+#' \describe{
+#'   \item{`Bubas bison`, `Copris elphenor`, `Copris hispanus`,
+#'   `Digitonthophagus gazella`, `Euoniticellus africanus`,
+#'   `Euoniticellus fulvus`, `Euoniticellus intermedius`,
+#'   `Euoniticellus pallipes`, `Geotrupes spiniger`, `Liatongus militaris`,
+#'   `Onitis alexis`, `Onitis aygulus`, `Onitis caffer`, `Onitis pecuarius`,
+#'   `Onitis vanderkelleni`, `Onitis viridulus`, `Onthophagus binodis`,
+#'   `Onthophagus nigriventris`, `Onthophagus obliquus`,
+#'   `Onthophagus sagittarius`, `Onthophagus taurus`, `Sisyphus rubrus`,
+#'   `Sisyphus spinipes`}{Either the number of individual specimens collected,
+#'   or the activity level observed, for the given species during the sampling
+#'   event. See **Details**}
 #' }
-"dpird_2012_2014"
+"dungfauna_event"
+
+
+
+

R/runShinyApp.R

@@ -2,21 +2,21 @@
 #' Run the shiny app visualisation
 #'
 #' Starts a visualisation of the dataset in a shiny app that can be
-#' viewed locally in the browser. After calling this function,
-#' If the app window doesn't start automatically,
-#' navigate to the port printed to your console
+#' viewed locally in the browser. If the app window doesn't start automatically,
+#' after calling this function, navigate to the port printed to your console
 #' (usually [localhost:5197](localhost:5197)) in your web browser.
 #'
 #' @export
 #'
 #' @examples
 #' # start the visualisation with:
-#' dungfaunaR::runShinyApp()
+#' # dungfaunaR::runShinyApp()
 runShinyApp <- function() {
   appDir <- system.file("shiny-visualisation", "app", package = "dungfaunaR")
 
   if (appDir == "") {
-    stop("Could not find shiny app directory. Try re-installing `dungfaunaR`.", call. = FALSE)
+    stop("Could not find shiny app directory. Try re-installing `dungfaunaR`.",
+         call. = FALSE)
   }
 
   shiny::runApp(appDir, display.mode = "normal")

README.Rmd

@@ -13,53 +13,19 @@ knitr::opts_chunk$set(
 )
 ```
 
-# Quick guide
-
-Once you have cloned the repository to your computer, open the project and run:
-
-devtools::install()
-
-This will install the package to your local library.
-
-The data to use for the dashboard is:
-
-data("dungfauna_aus")
-
-These data contain records from DBEE, QLD and a WA project. Not for public release just yet.
-
-There will be some further refinements to these data but I think we are at a stage to include a dashboard in the package.
-
-So, the aim is to:
-
-- 1. incorporate a copy of the dashboard into the package so that when a user installs the package they can run the dashboard locally.
-
-- 2. update the dashboard so that it includes 
-
-* all species found in the scientificName column (there are now new species from the QLD and WA projects that will need to be added to the 'Select a species' menu)
-
-* A new menu item allowing for data to be filtered by datasetName (i.e. project)
-
-* Remove the prediction tab
-
-* Put back in the data tab
-
-* Turn off the jittering of points
-
-* Any other minor changes we think of
+# dungfaunaR
 
-**Note: this is not a replacement of the existing dashboard but a copy.**
 
+## Overview
 
+This is a data package with data on occurrence and abundance records for deliberately introduced dung beetles in Australia. Currently, the data contain `r (dungfaunaR::dungfauna_occurrence |> dplyr::summarise(sum(individualCount, na.rm = TRUE)) |> dplyr::pull() + dungfaunaR::dungfauna_occurrence |>  dplyr::filter(occurrenceStatus == "present" & base::is.na(individualCount)) |>  dplyr::count() |> dplyr::pull()) |> base::format(big.mark = ",")` species identifications from `r dungfaunaR::dungfauna_occurrence |> dplyr::filter(occurrenceStatus == "present") |> dplyr::count() |> dplyr::pull() |> base::format(big.mark = ",")` occurrence records, taken from `r dungfaunaR::dungfauna_event |> dplyr::count() |> dplyr::pull() |> base::format(big.mark = ",")` sampling events at `r dungfaunaR::dungfauna_event |> dplyr::distinct(locationID_site) |> dplyr::count() |> dplyr::pull() |> base::format(big.mark = ",")` locations. The data also contain `r dungfaunaR::dungfauna_occurrence |> dplyr::filter(occurrenceStatus == "absent") |> dplyr::count() |> dplyr::pull() |> base::format(big.mark = ",")` absence records. The data are explained in detail in Berson et al (submitted).
 
+Code used to format the data can be found in the `data-raw folder` in the [dungfaunaR gihub repository](link here). Note that we formatted and performed checks on data from different projects separately (see `data-raw/qld_2001_2010.R`, `data-raw/dafwa_wa_2012_2014.R` and `data-raw/dbee_2019_2022.R`), before combining these data into one dataset (see `data-raw/dungfauna_aus.R`). 
 
-# dungfaunaR
+Code used to generate the summary statistics, figures and tables in Berson et al (submitted) can by found in the `data-paper` folder within the `data-raw` folder.
 
-<!-- badges: start -->
-[![CRAN status](https://www.r-pkg.org/badges/version/dungfaunaR)](https://CRAN.R-project.org/package=dungfaunaR)
-[![Codecov test coverage](https://codecov.io/gh/jdberson/dungfaunaR/branch/master/graph/badge.svg)](https://app.codecov.io/gh/jdberson/dungfaunaR?branch=master)
-<!-- badges: end -->
+The data are provided in both wide (`dungfauna_event`) and long (`dungfauna_occurrence`) format. Running `dungfaunaR::runShinyApp()` will launch a shiny app for visually exploring the data.
 
-The goal of dungfaunaR is to ...
 
 ## Installation
 
@@ -70,27 +36,27 @@ You can install the development version of dungfaunaR from [GitHub](https://gith
 devtools::install_github("jdberson/dungfaunaR")
 ```
 
-## Example
+## Getting started
 
-This is a basic example which shows you how to solve a common problem:
+After installing the package, the following code load the data into your R session:
 
-```{r example}
+``` r
 library(dungfaunaR)
-## basic example code
-```
 
-What is special about using `README.Rmd` instead of just `README.md`? You can include R chunks like so:
+# To load the data in wide format:
+data("dungfauna_event")
+
+# To load the data in long format:
+data("dungfauna_occurrence")
 
-```{r cars}
-summary(cars)
 ```
 
-You'll still need to render `README.Rmd` regularly, to keep `README.md` up-to-date. `devtools::build_readme()` is handy for this. You could also use GitHub Actions to re-render `README.Rmd` every time you push. An example workflow can be found here: <https://github.com/r-lib/actions/tree/v1/examples>.
+After installing and loading the package, you can explore the data with the built-in shiny app using `dungfaunaR::runShinyApp()`
 
-You can also embed plots, for example:
+## Citation
 
-```{r pressure, echo = FALSE}
-plot(pressure)
-```
+The paper detailing the data is currently submitted as a data paper. Please check back here for the correct citation to use when using the data.
+
+## Issues
 
-In that case, don't forget to commit and push the resulting figure files, so they display on GitHub and CRAN.
+If you find an error or a bug we would love to hear from you! Please let us know what you have found by creating an issue at https://github.com/jdberson/dungfaunaR/issues.