You can download the bib entry (here)
OnToology in maintained by the Ahmad Alobaid, María Poveda, Daniel Garijo, Idafen Santana and Oscar Corcho of the Ontology Engineering Group at Universidad Politécnica de Madrid
VICINITY is an European project that contains a network of ontologies in the domain of Internet of Things. The project has a GitHub repository for each ontology in the network, which is used to store the ontology and to track all the issues related to it. In order to propose changes, the ontology development team has to create a branch where all the proposed changes are made. Once OnToology generates all the resources for this new branch, the developers create a pull request to the master branch to discuss the modifications done to the ontology. If the ontology development team agrees on the changes the pull request is accepted and the changes are merged to the master branch. Users also propose changes through the GitHub issue tracker. The ontologies are published under the domain http://vicinity.iot.linkeddata.es and, therefore, the publication is not done with OnToology. However, the documentation generated by OnToology is used for the publication of the ontologies.
ETSI Specialist Task Force 513 is a project endorsed by ETSI and European Commission in which context the SAREF4BLDG and SAREF4ENVI ontologies were developed. These two ontologies are stored in the same repository, and the ontology developers contribute to their implementation collaboratively. Both ontologies have been published with OnToology, which automatically publish the ontologies with persistent URI using w3id.
In SPRINT, OnToology was extended in order to support ontology development efforts in the context of the Shift2Rail Interoperability Framework, and has been used for the documentation of ontologies being developed in this context.
During the European project easyTV, OnToology was used to document, evaluate an published under w3id the ontology developed to represent sing language information. The easyTV ontology reuses well-known linguistic models as lemon and lexinfo among others.
The DRUGS4COVID project aims at creating a catalogue of medicines that are being used to combat COVID-19 by using Artificial Intelligence techniques and Citizen Science in order to exploit the existing scientific literature about coronavirus (more than 60,000 papers). The extracted data is annotated with the DRUGS4COVID vocabulary that has been documented, evaluated and published using OnToology.