  Ontologies have been widely used in numerous and varied applications, e.g.,
to support data modeling, information integration, and knowledge management.
With the increasing size of ontologies, ontology understanding, which is
playing an important role in different tasks, is becoming more difficult.
Consequently, ontology summarization, as a way to distill key information from
an ontology and generate an abridged version to facilitate a better
understanding, is getting growing attention. In this survey paper, we review
existing ontology summarization techniques and focus mainly on graph-based
methods, which represent an ontology as a graph and apply centrality-based and
other measures to identify the most important elements of an ontology as its
summary. After analyzing their strengths and weaknesses, we highlight a few
potential directions for future research.
