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OME

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An Online Mapping Editor to generate R2RML, RML, and YARRRML without writing a single line. It also supports automatic suggestions of the subject and property columns using the APIs of tada_web.

Automatic Suggestions

It uses the APIs oftada_web. To use it, you need to export an environment variable TADA_HOST with the URL of the tada-web host url. For example, you can set it like that export TADA_HOST="http://127.0.0.1:5001/"

Environment Variables

  • SECRET_KEY:
    • A random text
  • TADA_HOST:
    • (Optional)
    • The URL of TADA APIs. If it is missing, the class and properties won't be annotated automatically
    • Default: ""
  • UPLOAD_ONTOLOGY:
    • (Optional)
    • To show/hide an ontology upload page (in the main page) for the autocomplete functionality
    • Default: True
  • github_secret:
    • Github app secret
  • github_appid:
    • Github app ID
  • MORPH_PATH:
    • The local path to morph-rdb jar to generate ttl
  • RMLMAPPER_PATH:
    • The local path to rmlmapper jar to generate the ttl

To activate_this.py

You can add these environment variables to activate_this.py in the virtualenv bin directory.

os.environ['SECRET_KEY']=""
os.environ['github_appid']=""
os.environ['github_secret']=""
os.environ['UPLOAD_ONTOLOGY']="false"
os.environ['RMLMAPPER_PATH']=""
os.environ['TADA_HOST']=""

To a shell

export SECRET_KEY=""
export github_appid=""
export github_secret=""
export UPLOAD_ONTOLOGY="false"
export RMLMAPPER_PATH=""
export TADA_HOST=""

Remarks

  • To run the application on a specific port (e.g. say port 5001) python app.py 5001.
  • To run the application on a specific port (e.g. say port 5001, and any given host 0.0.0.0) python app.py 0.0.0.0 5001.

To cite

@software{alobaid_ahmad_2020_3764202,
  author       = {Alobaid, Ahmad and
                  Corcho, Oscar},
  title        = {OME},
  month        = apr,
  year         = 2020,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.3764202},
  url          = {https://doi.org/10.5281/zenodo.3764202}
}

Funding

This work was funded partially by EIT Digital under the WOODS project.