SemValidator

Given a seed ontology and a list of concepts to be added to it, OntoValidator provides an easy-to-use interface for semantic validation of the enriched ontology. Validation is crowdsourced, with Twitter expertise of the validator being used for quality control.

The application has been deployed here.

Running the Application (Validator)

• Go to the Heroku web-app
• Sign in with your Twitter account.
• Select one of the ontologies given in the dashboard
• For each of the enriched concepts and relations (highlighted green), select accept or reject options.

Running the Application (Developer)

Directory Structure

• onto_app: Contains all relevant scripts used by the Flask application. Also contains get_verified_ontology.py which is to be used separately after crowdsourcing is complete. It outputs final ontology based on weighted majority voting algorithm of Twitter expertise scores of validators.
• WebVOWL: Code for working of WebVOWL application. For more information on how to modify this check out the corresponding README
• experiments: Contains README files with experimentation details. (Supplementary material to main paper)

Requirements:

• python3 and pip are used to build this application and are therefore prerequisites

Installation:

• Go to src folder
• Run pip3 install -r requirements.txt. In case of any missing modules, please raise an issue.

Initialization:

• Place the seed ontology (.owl file) in src/onto_app/data/input
• Place the file containing new concepts and relations in src/onto_app/data/input as .txt file
• Both the .owl file and .txt file should have same names. For instance, if your seed ontology is pizza.owl, name your text file as pizza.txt

Validating the Ontology (Sample)

This section shows how a developer can validate an ontology, for experimentation purposes. A real survey would obviously take place on a deployed app.

• Navigate to the onto_app directory.
• Run export FLASK_APP=routes.py and export FLASK_ENV=development
• Run flask run to start the server
• Login to the application using your Twitter account
• Accept/reject concepts and relationships, as appropriate.
• Logout and stop the server.
• Multiple users validate the ontology this way through crowdsourcing

Saving the decisions in final ontology

• Remove the files in final if any.
• Pretrained regression models have been provided in the models folder. The path to the model can be changed in get_verified_ontology.py
• Run python3 get_verified_ontology.py <file_name>
• The decisions made by all the ontologists get evaluated based on their Twitter credibilities.
• The decision with a higher score is chosen as the final decision, and written to the final ontology.
• Final ontology is stored in src/data/final as <file_name>.owl