Orchidokie uses the ORCID API (version 2.0) to list the datasets associated with a journal article, conference paper, or other publication.
The tool requires the dataset's ORCID record to contain (in the Work Identifiers
section of the metadata):
- The DOI of the dataset itself, marked as
Self
. - The DOI of the associated publication, marked as
Part of
.
This is so far only a prototype aimed at highlighting how good metadata practices can help with data discovery.
The tool relies heavily on a Python implementation of the ORCID API, which can be obtained from GitHub and installed using the following commands:
git clone https://github.com/ORCID/python-orcid.git
cd python-orcid
git checkout 2.0update
sudo python setup.py install
Note the switch to the 2.0update
branch.
A "Client ID" and a "Client Secret" are required. These can be obtained by creating a new application in the Developer Tools section of the ORCID website. They should be passed in at the command line, along with the DOI of the publication:
python orchidokie.py client_id_here client_secret_here 10.000/doi.123.here
~/orchidokie $ python orchidokie.py CLIENT_ID_HIDDEN CLIENT_SECRET_HIDDEN 10.1016/j.jocs.2016.11.001
Datasets of 10.1016/j.jocs.2016.11.001:
* Enstrophy and kinetic energy data from 3D Taylor-Green vortex simulations (https://doi.org/10.5258/SOTON/401892)
Orchidokie is released under the MIT license. See the LICENSE
file for more information.