) 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...

An emerging area of database system research is to investigate techniques that ensure a continuous display of video objects. As compared to the traditional data types, e.g., text, a video object must be retrieved at a prespecified rate. If it is retrieved at a lower rate then its display may suffer from frequent disruptions and delays, termed hiccups. This paper describes two alternative approaches to representing video objects (stream-based and structured) and the issues involved in supporting their hiccup-free display. For each approach, we describe the existing solutions and the future research directions from a database systems perspective. I want to thank Martha Escobar-Molano, Seon Ho Kim, Cyrus Shahabi, and Roger Zimmermann for contributing to the presented material. This paper is to appear as a book chapter in Multimedia Database Systems: Issues and Research Directions, Editors: S. Jajodia and V.S. Subrahmanian, Springer Verlag, 1995. This research was supported in part by th...

DEVise is a data visualization and exploration system capable of handling large data sets using off-theshelf hardware with minimal memory requirements. Data can be large in volume, complex in structure (multidimensional and/or hierarchical), and may be imported from different sources such as database servers, external programs, and World Wide Web resources. Commercial and scientific databases can also be linked to DEVise to allow the user to visualize and analyze related information from heterogeneous sources. Associations between data sources are developed interactively as the user gains more knowledge of the data being explored. To assist in handling large data sets, DEVise allows a user to logically split the data into more manageable units at different levels. The user selects a data source, a data stream within a data source (e.g. a time series), attributes of a stream, and a mapping of attributes to graphical objects. At each step, the selections made by the user reduce the data...

We present the DEVise toolkit designed for visual exploration of stream data. Data of this type are collected continuously from sources such as remote sensors, program traces, and the stock market. A typical application involves looking for correlations, which may not be precisely defined, by experimenting with graphical representations. This includes selectively comparing data from multiple sources, selective viewing by zooming and scrolling at various resolutions, and querying the underlying data from the graphics. DEVise is designed to provide greater support than packages such as AVS or Khoros for this type of application. First, by abandoning the network flow model of AVS and Khoros in favor of a database query model, we are able to incorporate many performance improvements for visualizing large amounts of data. To our knowledge, this is the first attempt to eliminate data size limitations in a visualization package. Second, by structuring the stand-alone graphics module of mos...