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In a challenging financial climate, there is a growing impetus for businesses to use existing process data to support more intelligent decision making. For large-scale complex systems such as railways, electricity grids, and gas distribution networks, this often means combining information from numerous different condition monitoring systems; however, given the vast amounts of data produced every day and the frequently incompatible data models used to represent it, is it possible to be sure that the information generated is being used correctly? This paper provides an introduction to the field of Ontology, an emerging technology that allows the exact "meaning" of an item of data to be described in a way that can be interpreted by computers. Through this retention of meaning, it becomes possible for computers to perform simple reasoning operations, inferring new information about a system from the existing facts, and enabling exciting new Semantic Web technologies.