The goal of the
dataspice package is to make it easier for researchers to create basic, lightweight, and concise metadata files for their datasets. These basic files can then be used to:
dataspice metadata fields are based on Schema.org and and other, richer metadata standards such as Ecological Metadata Language.
To start the user will have one or more datafiles in a common directory. We currently support rectagular data with headers in a .csv file or spatial data with attributes.
create_spice() reads in the files from that directory and creates a set of template metadata files for the user to populate. These metadata templates will include some data extracted from the user's datafiles, including things like file names and measured variable names to aid the user in populating the metadata files.
Once these are created, the user needs to open each template, fill in the missing metadata (as completely as possible), and read the files back into R.
creators.csv: One row for each creator, and gives their affiliation, contact email, ORCID, etc.
attributes.csv: This is where most of the user data entry will take place. For each variable, its name, units, and a written description are filled in.
biblio.csv: Citation information about the project, as much or as little data as possible can be included, but if things like bounding box coordinates are not included, then when the website is generated there will not be a bounding box map generated.
access.csv: Includes a row for each file that was read in, and documents the name of each file and its format.
Once the populated the metadata files are read back R they can then be fed into
write_JSON(), which converts those tabular metadata files into JSON files.
A dataset README website is an interactive representation of the JSON information about the data. Assuming sufficient information is provided in the JSON it will include a map of the points and a bounding box of the area of study.
The output from
write_JSON() is fed into
build_site() to create the website.