  Despite improved digital access to scholarly knowledge in recent decades,
scholarly communication remains exclusively document-based. In this form,
scholarly knowledge is hard to process automatically. In this paper, we present
the first steps towards a knowledge graph based infrastructure that acquires
scholarly knowledge in machine actionable form thus enabling new possibilities
for scholarly knowledge curation, publication and processing. The primary
contribution is to present, evaluate and discuss multi-modal scholarly
knowledge acquisition, combining crowdsourced and automated techniques. We
present the results of the first user evaluation of the infrastructure with the
participants of a recent international conference. Results suggest that users
were intrigued by the novelty of the proposed infrastructure and by the
possibilities for innovative scholarly knowledge processing it could enable.
