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This paper proposes an approach to leverage upon existing ontologies in order to automate the annotation of time series medical data. The annotation is achieved by an abductive reasoner using parsimonious covering theorem in order to determine the best explanation or annotation for specific user defined events in the data. The novelty of this approach resides in part by the system's flexibility in how events are defined by users and later detected by the system. This is achieved via the use ofdoi:10.1186/2041-1480-5-35 fatcat:5vz2bjfg3vfmng6lbfjjvhee2a