Cost analysis is essential to enterprises developing plans to deal with product obsolescence. Indeed, cost analysis drives the optimization behind obsolescence mitigation planning and the maintenance of long field life sustainment-dominated systems. There are many different obsolescence mitigation solutions. Determining the optimum plan requires inputs from multiple departments within the enterprise such as maintenance, manufacturing, inventory, marketing, purchasing, etc. Moreover, proper analysis requires system records over a long period. As one might expect, these needs present challenges since proper data comes from different sources across multiple departments. In recent years, ontological models have been shown to be good at relation representation and knowledge management. Ontologies have been used to help with data integration and decision-making. This paper puts forward an ontology-based model and data inquiry method to help locate appropriate departments and related heterogeneous data for current and legacy data sources. The ontology-enabled data inquiry can then more accurately and efficiently improve cost analysis and the planning and management of obsolescence mitigation activities.