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This vignette aims to showcase a use case using the 2 main functions
of metajam
- download_d1_data
and
read_d1_files
to download one dataset from the Arctic Data Center data
repository.
As example, we are using permafrost data from the Polaris Project 2017: Sarah Ludwig, Robert M Holmes, Susan Natali, Paul Mann, John Schade, et al. 2018. Polaris Project 2017: Permafrost carbon and nitrogen, Yukon-Kuskokwim Delta, Alaska. Arctic Data Center. doi:10.18739/A2KK3F.
# Create the local directory to download the datasets
dir.create(path_folder, showWarnings = FALSE)
# Download the dataset and associated metdata
data_folder <- metajam::download_d1_data(data_url, path_folder)
# data_folder
# "Data_polaris/doi_10.18739_A2KK3F__Polaris_2017_Permafrost"
At this point, you should have the data and the metadata downloaded
inside your main directory; Data_polaris
in this example.
metajam
organize the files as follow:
my_data.csv
__full_metadata.xml
:
my_data__full_metadata.xml
__summary_metadata.csv
:
my_data__summary_metadata.csv
__attribute_metadata.csv
:
my_data__attribute_metadata.csv
__attribute_factor_metadata.csv
:
my_data__attribute_factor_metadata.csv
You have now loaded in your R environment one named list object that
contains the data polaris17_permafrost$data
, the general
(summary) metadata polaris17_permafrost$summary_metadata
-
such as title, creators, dates, locations - and the attribute level
metadata information
polaris17_permafrost$attribute_metadata
, allowing user to
get more information, such as units and definitions of your
attributes.
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.
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