Abstract: The problem of data semantics is establishing and maintaining a correspondence between a data source (e.g., a database of an XML document) and its intended subject matter. We review the long history of the problem in Databases, and contrast it with current work on the Semantic Web. We then propose two new directions for research and sketch some open questions.

This is joint work with Alex Borgida (Rutgers University), published in Borgida, A., Mylopoulos, J., Data Semantics Revisited, Proceedings VLDB Workshop on the Semantic Web and Databases (SWDB-04), Toronto, August 2004, Springer-Verlag LNCS.

Short Bio: John Mylopoulos holds a PhD degree from Princeton University and is a professor of Computer Science at the University of Toronto. His research interests include semantic data models, requirements engineering, and knowledge management. He is the recipient of the first-ever Outstanding Services Award given by the Canadian AI Society (CSCSI), a co-recipient of the most influential paper award of the 1994 International Conference on Software Engineering, a fellow of the American Association for AI (AAAI) and past president of the VLDB Endowment.