Using ontologies to represent and drive knowledge infrastructure of software projects is the Semantic Web answer to the paradigm of Model-Driven Architecture. Advocates of this approach argue that using ontologies in this capacity provides separation of the declarative and procedural knowledge and enables easier evolution of the declarative knowledge. We have validated these conjectures in the context of BioPortal, a repository of biomedical ontologies, which was developed in our group. We are using the BioPortal Metadata Ontology to represent details about all the ontologies in the repository, including internal system information and the information that we collect from the community such as mappings between classes in different ontologies, ontology reviews, and so on. To the best of our knowledge, BioPortal is the ﬁrst large-scale application that uses ontologies to represent essentially all of its internal infrastructure.
The BioPortal Metadata Ontology extends several other ontologies for representing metadata, such as the Ontology Metadata Vocabulary and the Protégé Changes and Annotations Ontology. In this paper, we show that it is feasible to describe the structure of the data that drives an application using ontologies rather than database schemas, which are used traditionally to store the infrastructure data. We also show that such approach provides critical advantages in terms of ﬂexibility and adaptability of the tool itself. We demonstrate the extensibility of the approach by enabling representation of views on ontologies and their corresponding metadata in the same framework.