Today's DBMS technology faces yet another challenge as researchers attempt to make sense of the immense amount of heterogeneous, fast-evolving data available on the Web. The large number of cooperating databases greatly complicates autonomy and heterogeneity issues and requires a careful scalable approach. We need better models and tools for describing data semantics and specifying metadata. Techniques for automatic data and metadata extraction and classification (ontologies, for example) Are crucial for building tomorrow's Semantic Web. Query languages and query processing should also be extended to exploit semantic information.
Users also need adaptive systems to help them explore the Web and discover interesting data sources and interfaces that support different query and search paradigms. Data dissemination techniques and notification services must be developed to enable effective data delivery services. Web-centric applications such as e-commerce and digital government applications pose stringent organizational, security, and performance requirements that far exceed what is now possible with traditional database techniques. Recent XML-native or extended DBMSs still need to be fine-tuned and evaluated. Finally, we need new methodologies to support the design and development of data-intensive Web sites.