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ro-terms

The purpose of this repository is to allow RO-crate users to create their own RO terms without having to create a new namespace, ontologies, etc.

This way, the RO-crate community can ellaborate vocabularies in a collaborative manner. Users may collaborate to a common vocabulary (vocabulary.csv) or create their own terms.

RO-crates use the following namespace:

https://w3id.org/ro/terms/YOUR_NAMESPACE#

The namespace for the common terms is:

https://w3id.org/ro/terms#

To download the terms in CSV you can do:

curl -L https://w3id.org/ro/terms

And if you want them in json-ld:

curl -H "accept:application/ld+json" -L https://w3id.org/ro/terms > context.jsonld

Equivalent content negotiation is available for each of the folders registered under ro-terms, e.g. https://w3id.org/ro/terms/earth-science#

Contribution guidelines

This repository https://github.com/researchobject/ro-terms works in a first-come, first-serve basis. To add your own terms, simply:

  1. Fork this repository
  2. Add a new folder to reserve your own namespace. code Add a vocabulary.csv file with your terms and a short README.md file with your name/project and who the maintainer is. For an example, you can see the example folder. If you just have a few terms, you can add them to the common namespace (just edit the vocabulary.csv file at the root level). When adding your terms, please make sure that each term has a label, type, definition and a domain and range if you are defining a property.
  3. Once done, execute the python script to generate a context.json file for your terms. You can do so by doing python ./gen_context.py ./your-namespace. This writes a context.json into the your-namespace directory.
  4. Open a pull request and a maintainer from ro-terms will assess and merge the changes as soon as possible.

Why are terms collected in a CSV?

We want to quickly allow contributors to be able to understand and explore existing terms and their definitions. From the CSV we can easily create machine-readable versions of the vocabulary, including a JSON-LD context.