SBDI4R is deprecated; we suggest you use either sbdi4r2 (soon available) or galah instead. Both packages provide an improved interface to ALA data, while providing the same core functionality as SBDI4R. For an introduction to galah, visit the GitHub page.
The Swedish Biodiversity Data Infrastructure (SBDI) provides tools to enable users of biodiversity information to find, access, combine and visualize data on Swedish plants and animals; available through SBDI. The R package SBDI4R provides a subset of the tools, and some extension tools (found previously in Analysportalen.se), to be directly used within R.
SBDI4R enables the R community to directly access data and resources hosted by SBDI. Our goal is to enable observations of species to be queried and output in a range of standard formats. This tool is built on the Atlas of Living Australia ALA4R package which provides similar services for the ALA. Similar to the NBN4R package SBDI4R wraps ALA4R functions but redirects requests to local web servers. All SBDI, NBN and ALA share similar Application Protocol Interface (API) web services.
Use-examples are available in the package vignette
here,
or via (in R): vignette("SBDI4R"). If you have any questions please
get in contact with us via the support center.
In R:
Or the development version from GitHub:
install.packages("remotes")
library(remotes)
install_github("AtlasOfLivingAustralia/ALA4R")
install_github("biodiversitydata-se/SBDI4R")
If you see an error about a missing package, you will need to install it manually, e.g.:
install.packages(c("stringr","sf"))
and then install_github("biodiversitydata-se/SBDI4R") again.
If you see an error about "ERROR: lazy loading failed for package 'SBDI4R'", this may be due to you trying to install on a network location. Try instead to install on a local location: first create the local location you want to use, and then specify this location for installing, and later loading the package:
install_github("biodiversitydata-se/SBDI4R", lib = "C:/pathname/MyLibrary")
library(SBDI4R, lib.loc = "C:/pathname/MyLibrary")
If you wish to use the data.table package for potentially faster
loading of data matrices (optional), also do:
install.packages("data.table")
Follow the instructions for Windows.
If you see an error about a failure to set default locale, you will need to manually set this:
system('defaults write org.R-project.R force.LANG en_US.UTF-8')
and restart R.
More information can be found on the CRAN R for Mac page.
First, ensure that libcurl is installed on your system --- e.g. on
Ubuntu, open a terminal and do:
sudo apt-get install libcurl4-openssl-devor install libcurl4-openssl-dev via the Software Centre.
Then, in R:
Or the development version from GitHub:
install.packages("remotes")
library(remotes)
install_github("AtlasOfLivingAustralia/ALA4R")
install_github("biodiversitydata-se/SBDI4R")
If you see an error about a missing package, you will need to install it manually, e.g.:
install.packages(c("stringr","fp"))
and then try installing SBDI4R again.
If you wish to use the data.table package for potentially faster
loading of data matrices (optional), also do:
install.packages("data.table")
The SBDI4R package must be loaded for each new R session with
library(SBDI4R), or specifying your local location with
library(SBDI4R, lib.loc = "C:/pathname/MyLibrary").
Various aspects of the SBDI4R package can be customized.
SBDI4R can cache most results to local files. This means that if the same code is run multiple times, the second and subsequent iterations will be faster. This will also reduce load on the web servers. By default, this caching is session-based, meaning that the local files are stored in a temporary directory that is automatically deleted when the R session is ended. This behaviour can be altered so that caching is permanent, by setting the caching directory to a non-temporary location. For example, under Windows, use something like:
sbdi_config(cache_directory = file.path("c:","mydata","sbdi_cache")) ## Windows
or for Linux:
sbdi_config(cache_directory = "~/mydata/sbdi_cache") ## Linux
Note that this directory must exist (you need to create it yourself).
All results will be stored in that cache directory and will be used from one session to the next. They won't be re-downloaded from the server unless the user specifically deletes those files or changes the caching setting to "refresh".
If you change the cache_directory to a permanent location, you may wish to add something like this to your .Rprofile file, so that it happens automatically each time the SBDI4R package is loaded:
setHook(packageEvent("SBDI4R", "onLoad"),
function(...) sbdi_config(cache_directory=file.path("~","mydata","sbdi_cache")))
Caching can also be turned off entirely by:
sbdi_config(caching="off")
or set to "refresh", meaning that the cached results will re-downloaded from the SBDI servers and the cache updated. (This will happen for as long as caching is set to "refresh" — so you may wish to switch back to normal "on" caching behaviour once you have updated your cache with the data you are working on).
Each download request to SBDI servers is also accompanied by an "e-mail address" string that identifies the user making the request. You will need to provide an email address registered with the SBDI. You can create an account here. Once an email is registered with the SBDI, it should be stored in the config:
sbdi_config(email="[email protected]")
Else you can provide this e-mail address as a parameter directly to each call of the function occurrences().
Each request to SBDI servers is accompanied by a "user-agent" string that identifies the software making the request. This is a standard behaviour used by web browsers as well. The user-agent identifies the user requests to SBDI, helping SBDI to adapt and enhance the services that it provides. By default, the SBDI4R user-agent string is set to "SBDI4R" plus the SBDI4R version number (e.g. "SBDI4R 1.0").
NO other personal identification information is sent. You can see all configuration settings, including the the user-agent string that is being used, with the command:
sbdi_config()
If things aren't working as expected, more detail (particularly about web requests and caching behaviour) can be obtained by setting the verbose configuration option:
sbdi_config(verbose=TRUE)
SBDI requires that you provide a reason when downloading occurrence data
(via the SBDI4R occurrences() function). You can provide this as a
parameter directly to each call of occurrences(), or you can set it
once per session using:
sbdi_config(download_reason_id=your_reason_id)
(See sbdi_reasons() for valid download reasons, e.g.
download_reason_id=10 for "testing", or 7 for "ecological research", 8
for "systematic research/taxonomy", 3 for "education")
If you make a request that returns an empty result set (e.g. an un-matched name), by default you will simply get an empty data structure returned to you without any special notification. If you would like to be warned about empty result sets, you can use:
sbdi_config(warn_on_empty=TRUE)
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