Some scientists use Excel as the main application for data storage and analysis. This approach leads to data dispersion and knowledge segregation in organizations, mainly because Excel files are usually stored in personal computers and data contained in these files cannot be queried. Organizations dealing with constant changes in their knowledge domain, such as the life sciences, have been adopting semantic web technologies to withstand large amounts of data and obtain the flexibility needed to support ontology changes over time with minimal impact on the existing data. By mapping OWL ontologies into the Excel object model, we demonstrate that is possible for end users to still use Excel as front-end and provide organizations with the means to store data in an aggregate manner, allowing a more thorough data analysis.