) M. Livny, R. Ramakrishnan, K. Beyer, G. Chen, D. Donjerkovic, S. Lawande, J. Myllymaki and K. Wenger Department of Computer Sciences, University of Wisconsin--Madison 1210 W. Dayton St., Madison, Wisconsin 53706 Tel: (608)262-6611, Fax: (608)262-9777 fmiron,raghu,beyer,guangshu,donjerko,ssl,jussi,wengerg@cs.wisc.edu Abstract DEVise is a data exploration system that allows users to easily develop, browse, and share visual presentations of large tabular datasets (possibly containing or referencing multimedia objects) from several sources. The DEVise framework, implemented in a tool that has been already successfully applied to a variety of real applications by a number of user groups, makes several contributions. In particular, it combines support for extended relational queries with powerful data visualization features. Datasets much larger than available main memory can be handled---DEVise is currently being used to visualize datasets well in excess of 100MB--- and data can be in...

The explosion in complex multi-media content makes it crucial for database systems to support such data efficiently. We make the case that the next generation of object-relational database Data Type (E-ADT) technology, rather than on the “blackbox ” ADTs used in current systems. An E-ADT is an abstract data type that exposes the semantics of its methods. Query optimizations are performed using these semantics, resulting in efficient query processing. The added functionality does not compromise the modularity of data types and the extensibility of the type system. Fundamental architectural changes are required to build such a database system; these have been explored through the implementation of E-ADTs in Predutor. Initial performance results demonstrate an order of magnitude in performance improvements. 1

The next generation of database applications will be dominated by rich and complex data types. The ADT technology of today's object-relational database systems cannot provide adequate performance for such applications. The basic stumbling block is the lack of semantic knowledge provided to the database system about the ADT operations. We are developing novel "Enhanced ADT" (E-ADT) technology that overcomes this problem, while retaining the extensibility of the database system. In effect, this "turbo-charges" the complex data types, resulting in dramatically improved performance. E-ADT technology is being demonstrated on several kinds of multi-media data in the PREDAT OR database system at Cornell. 1 Introduction We are witnessing an explosion in the volume and complexity of digital information that people want to access and analyze. Much of this data is "multi-media" like images, video, audio, and documents. Several other kinds of complex data are also important, including geographic...