https://github.com/ajpelu/gbifexplorer

https://github.com/ajpelu/gbifexplorer

Repository

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# gbifexploreR


[![R-CMD-check](https://github.com/ajpelu/gbifexplorer/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/ajpelu/gbifexplorer/actions/workflows/R-CMD-check.yaml)
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The goal of gbifexplorer is provide some tools to explore the different types of 
[gfbif dataset classes](https://www.gbif.org/dataset-classes): Occurrence, Sampling-event 
or Checklist. `gbifexplorer` allows to explore the taxonomic, temporal and/or spatial 
coverages of the gbif datasets. 


## Installation

You can install the development version of gbifexplorer from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("ajpelu/gbifexplorer")
```

## Usage 

The `gbifexplorer` package provides several functions for exploring and analyzing 
occurrence data from the Global Biodiversity Information Facility (GBIF). Here is an
example of the usage of three key functions: `cov_temporal`, `taxonomic_cov`, and 
`report_taxonomy`.

We will use a dataset contains information about the phenology of flora in 
Mediterranean high-mountains meadows in the Sierra Nevada region (Spain). This dataset
is deposited in [GBIF](https://doi.org/10.15468/qhqzub) and also published as [Data Paper](https://doi.org/10.3897/phytokeys.46.9116). It also is included as 
example data in the `gbifexplorer` pkg. 

### Calculate the Temporal Coverage of an Ocurrence Dataset
The `gbifexplorer::cov_temporal()` function calculates the temporal coverage of a dataset based 
on a specified date variable provided by the user. It determines the minimum and 
maximum dates from the date variable and returns them in a data frame.

```{r}
library(gbifexplorer)
data("borreguiles")

# Calculate temporal coverage
temporal_coverage <- cov_temporal(borreguiles, date_var = "eventDate", 
                                  date_format = "%Y-%m-%d")

```

It returns a data frame (`temporal_coverage`) that contains the minimum and maximum 
dates from the dataset. This function also prints the temporal coverage as text
and could be used to document the metadata of the dataset. 

## Get the Taxonomic Coverage of an Ocurrence Dataset and report it. 
The `gbifexplorer::taxonomic_cov()` function generates the taxonomic coverage of 
a dataframe. It calculates the record numbers and relative frequencies of each 
taxonomic category specified, allowing to compute the taxonomic coverage of an 
occurence dataset. The function returns a named list of tibbles summarizing 
the taxonomic coverage for each category. 

```{r}
# Calculate taxonomic coverage for scientificName and genus
d <- taxonomic_cov(borreguiles, category = c("class", "order"))
d
```

The result is a list contains tibbles summarizing the taxonomic coverage for each 
taxonomic category.

Then, it is possible to generate a Report for different taxa categories by using 
the `gbifexplorer::report_taxonomy()` function. It generates a summary report of 
the taxonomy of a specified taxa rank, and provides information about the most 
represented taxa based on the frequency information of the taxa rank. The default 
is the top 5 most represented taxa but is could be change using the argument `top`

For instance, if you are interested in the 5 most frequent order: 

```{r}
report_taxonomy(d$order, top = 5)
```

The user might also be interested in calculate the taxonomic coverage for all 
taxonomic categories present in an occurrence dataset. For this, we also used the 
`purrr` package 

```{r}
library(purrr)
all_taxa <- taxonomic_cov(borreguiles, category = "all")

all_taxa |> 
  purrr::map(~report_taxonomy(., top=10)) |> 
  purrr::list_transpose()

```

## Interctive app 
We also have developed a shiny app to allow the user to generate the taxonomic coverage
of an occurence data. To run the app: 

```{r, eval=FALSE, message=FALSE, warning=FALSE}
library("gbifexplorer")
gbifexplorer::taxo_reportApp()
```

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