The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
The original accessions for the data sets included within
datamuseum are also available on GitHub. These are from the
Global Biodiversity Information Facility (GBIF), Invert-E-Base
(InvBase), the Biological Information System for Marine Life (BISMAL),
Ocean Biodiversity Information System (OBIS), and one data set obtained
by direct request from the National Museum of Nature and Science, Japan
(NSMT).
In this workflow, accessing the GBIF-sourced data directly from the
GitHub repository for datamuseum will be demonstrated.
Due to the size of the data, the files are stored within a .zip folder. Luckily, R is capable of downloading and unzipping the files directly from a GitHub link!
rawzip <- tempfile()
download.file("https://github.com/btorgovitsky00/datamuseum/raw/master/data-raw.zip", rawzip,
mode = "wb")
temp <- tempdir()
unzip(rawzip, exdir = temp)Each data set in datamuseum has two associated parent
files: the actual original accession from the respective repository
(denoted as “raw”), and a version with some columns removed for improved
visibility (“trim”).
#Raw Original Data
GBIF_clean <- read.csv(file.path(temp, "data-raw", "GBIF_Octopodoidea_raw.csv")) #88256 Observations
#Trimmed Original Data
GBIF_clean <- read.csv(file.path(temp, "data-raw", "GBIF_Octopodoidea_trim.csv")) #88256 ObservationsThe GBIF data sets were obtained and refined from the following occurrence download:
Global Biodiversity Information Facility (GBIF). GBIF.org (30 March 2026) GBIF Occurrence Download. https://www.gbif.org. doi: 10.15468/dl.2379hj
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.