Query previews in networked information systems

TitleQuery previews in networked information systems
Publication TypeConference Papers
Year of Publication1996
AuthorsDonn K, Plaisant C, Shneiderman B
Conference NameProceedings of the Third Forum on Research and Technology Advances in Digital Libraries, 1996. ADL '96
Date Published1996/05/13/15
ISBN Number0-8186-7403-2
KeywordsComputer networks, data complexity, data mining, data patterns, data volume, dynamic query user interfaces, Educational institutions, EOS-DIS, exploratory method, Information retrieval, Information services, Information systems, Intelligent networks, interactive systems, Laboratories, Manipulator dynamics, matching data sets, NASA Earth Observing System-Data Information System, Network performance, networked environment, networked information systems, query formulation, query preview, query refinement, querying process, rough attribute values, User interfaces, visual databases, zero hit queries

In a networked information system (such as the NASA Earth Observing System-Data Information System (EOS-DIS)), there are three major obstacles facing users in a querying process: network performance, data volume and data complexity. In order to overcome these obstacles, we propose a two phase approach to query formulation. The two phases are the Query Preview and the Query Refinement. In the Query Preview phase, users formulate an initial query by selecting rough attribute values. The estimated number of matching data sets is shown, graphically on preview bars which allows users to rapidly focus on a manageable number of relevant data sets. Query previews also prevent wasted steps by eliminating zero hit queries. When the estimated number of data sets is long enough, the initial query is submitted to the network which returns the metadata of the data sets for further refinement in the Query Refinement phase. The two phase approach to query formulation overcomes slow network performance, and reduces the data volume and data complexity, problems. This approach is especially appropriate for users who do not have extensive knowledge about the data and who prefer an exploratory method to discover data patterns and exceptions. Using this approach, we have developed dynamic query user interfaces to allow users to formulate their queries across a networked environment