Addressing archaeology's most compelling substantive challenges requires synthetic research that exploits the large and rapidly expanding corpus of systematically collected archaeological data. That, in turn, requires a means of combining datasets that employ different systematics in their recording while at the same time preserving the semantics of the data. To that end, we have developed a general procedure that we call query-driven, on-the-fly data integration that is deployed within the Digital Archaeological Record digital repository. The integration procedure employs ontologies that are mapped to the original datasets. Integration of the ontology-based dataset representations is done at the time the query is executed, based on the specific content of the query. In this way, the original data are preserved, and data are aggregated only to the extent necessary to obtain semantic comparability. Our presentation draws examples from the largest application to date: an effort by a research community of Southwest US faunal analysts. Using 24 ontologies developed to cover a broad range of observed faunal variables, we integrate faunal data from 33 sites across the late prehistoric northern Southwest, including about 300,000 individually recorded faunal specimens.