FEDRR: Fast, Exhaustive Detection of Redundant Hierarchical Relations in Large Biomedical Ontologies

Redundant hierarchical relations refer to such patterns as two paths from one concept to another, one with length one (direct) and the other with length greater than one (indirect). This paper introduces a novel and scalable approach, called FEDRR – Fast, Exhaustive Detection of Redundant Relations – for quality assurance work during ontological evolution. FEDRR combines the algorithm ideas of Dynamic Programming with Topological Sort, for exhaustive mining of all redundant hierarchical relations in ontological hierarchies, in O(c · |V | + |E|) time, where |V | is the number of concepts, |E| is the number of the relations, and c is a constant in practice. Using FEDRR, we performed exhaustive search of all redundant is-a relations in two of the largest ontological systems in biomedicine: SNOMED CT and Gene Ontology (GO). 235 and 1609 redundant is-a relations were found in the 2015-03-01 version of SNOMED CT and 2015-05-01 version of GO, respectively. Each redundant relation represents a possibly unintended defect that needs to be corrected in the ontology quality assurance process. FEDRR provides a generally applicable, effective tool for systematic detecting redundant relations in large ontological systems for quality improvement.