Transforming semi-structured life science diagrams into meaningful domain ontologies with DiDOn.
Bio-ontology development is a resource-consuming task despite the many open source ontologies available for reuse. Various strategies and tools for bottom-up ontology development have been proposed from a computing angle, yet the most obvious one from a domain expert perspective is unexplored: the abundant diagrams in the sciences. To speed up and simplify bio-ontology development, we propose a detailed, micro-level, procedure, DiDOn, to formalise such semi-structured biological diagrams availing also of a foundational ontology for more precise and interoperable subject domain semantics. The approach is illustrated using Pathway Studio as case study.
School of Computer Science, University of KwaZulu-Natal, Private Bag X54001, 4000 Durban, South Africa. keet@ukzn.ac.za
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D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D008954:Models, Biological; D012984:Software