  One of the major barriers to the training of algorithms on knowledge graph
schemas, such as vocabularies or ontologies, is the difficulty that scientists
have in finding the best input resource to address the target prediction tasks.
In addition to this, a key challenge is to determine how to manipulate (and
embed) these data, which are often in the form of particular triples (i.e.,
subject, predicate, object), to enable the learning process. In this paper, we
describe the LiveSchema initiative, namely a gateway that offers a family of
services to easily access, analyze, transform and exploit knowledge graph
schemas, with the main goal of facilitating the reuse of these resources in
machine learning use cases. As an early implementation of the initiative, we
also advance an online catalog, which relies on more than 800 resources, with
the first set of example services.
