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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.

<!-- # Run with Docker 1. `sh run_docker.sh` 2. In the browser visit `http://127.0.0.1:5000` # How to install it locally 1. Create virtual environment [here](https://docs.python-guide.org/dev/virtualenvs/) (recommended by not required) e.g. ```virtualenv -p /usr/bin/python2.7 .venv``` 1. Access the virtual environment using `source .venv/bin/activate` 1. Install pip [here](https://pip.pypa.io/en/stable/installing/) 1. Install requirements ``` pip install -r requirements.txt ``` 1. Set `TADA_HOST` to the url of the pytada_hdt_entity host. For example (`export TADA_HOST="http://127.0.0.1:5001/`) 1. Run the application ``` python app.py ``` 1. Open the browser to the url [http://127.0.0.1:5000/](http://127.0.0.1:5000/) -->

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

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=""
<!-- # Screenshot ![screenshot](https://github.com/oeg-upm/OME/raw/master/screenshot.png) -->

Remarks

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.