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Harena Semantics: A Framework to Support Semantic Annotation in Citizen Science Systems

We propose a new approach to support human agents to annotate semantic concepts in free-text sentences in the biomedical domain. Using our markdown-derived language called Versum, authors can easily annotate relevant terms while producing content for Citizen Science systems. Besides, an embedded Automatic Annotation Mechanism suggests semantic concepts for the author. It implements a Named Entity Recognition task using a hybrid approach: (1) a Transformer-based Deep Neural Network and (2) an Ontology-based method. We conducted a case study running over content produced in the Harena e-learning system, which intends to teach Clinical Reasoning to students using Clinical Cases. Results of this pilot evaluation suggest the potential of Harena Semantics to engage volunteers in the production of semantic, agent-centered resources on crowdsourcing systems.