HOnEst will achieve scalable human-centric ontology evaluation. To that end it has the following aims:
We contribute to a comprehensive characterization of the human-centric ontology evaluation problem with a systematically classified catalogue of HETs.
We explore the solution space of Human Computation (HC) techniques and provide an HC-based method for ontology evaluation which advances work on the generic problem of conceptual model evaluation. We also derive evidence-based HC-configuration guidelines and establish the first ontology evaluation benchmark dataset to compare HC-based evaluation approaches.
We investigate scalable human-centric evaluation through hybrid human-machine systems (HHMS) which combine computational elements and HC systems. We explore the concept of HHMS in use cases where automatically created, very large ontologies are verified.
