  There is a large number of online documents data sources available nowadays.
The lack of structure and the differences between formats are the main
difficulties to automatically extract information from them, which also has a
negative impact on its use and reuse. In the biomedical domain, the DISNET
platform emerged to provide researchers with a resource to obtain information
in the scope of human disease networks by means of large-scale heterogeneous
sources. Specifically in this domain, it is critical to offer not only the
information extracted from different sources, but also the evidence that
supports it. This paper proposes EBOCA, an ontology that describes (i)
biomedical domain concepts and associations between them, and (ii) evidences
supporting these associations; with the objective of providing an schema to
improve the publication and description of evidences and biomedical
associations in this domain. The ontology has been successfully evaluated to
ensure there are no errors, modelling pitfalls and that it meets the previously
defined functional requirements. Test data coming from a subset of DISNET and
automatic association extractions from texts has been transformed according to
the proposed ontology to create a Knowledge Graph that can be used in real
scenarios, and which has also been used for the evaluation of the presented
ontology.
