Rendering knowledge graphs from aerospace dentistry processes for clinical decision support systems

NASA and commercial space flight companies expect to make long-term missions into deep space with the Artemis project and Mars mission. Health care in deep space is a priority as the missions require limited crew and equipment to accommodate astronauts' needs. Analyzing the probable clinical procedures and workflows for this setting is needed to ensure quality care and safety. This paper introduces Business Process Modeling and Notation (BPMN) and OWL2-based modeling to represent aerospace dental workflows for low-earth orbit and potential deep space missions. We developed BPMN process models and created ontology-based knowledge graph representations for individual dental procedures using a semi-automated processing pipeline. The output of this project yielded four OWL2-based knowledge graphs that describe semantic descriptions of a dental abscess, extractions, dislodged restorations, and dental trauma. With computable knowledge graphs of these processes, we can integrate these models for software applications for remote clinical tools, like decision support systems. Future work will involve extending these prototype knowledge graphs and developing knowledge base applications that leverage these process artifacts.