Advanced graphic user interfaces: elastic and tightly coupled windows
ACM Computing Surveys (CSUR) - Special issue: position statements on strategic directions in computing research
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Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Sorting out searching: a user-interface framework for text searches
Communications of the ACM
Information visualization advanced interface and Web design
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A scrollbar-based visualization for document navigation
Proceedings of the fourth ACM conference on Digital libraries
Interface and data architecture for query preview in networked information systems
ACM Transactions on Information Systems (TOIS)
Parallel bargrams for consumer-based information exploration and choice
Proceedings of the 14th annual ACM symposium on User interface software and technology
Design and Evaluation of Incremental Data Structures and Algorithms for Dynamic Query Interfaces
INFOVIS '97 Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97)
Efficient Multi-Object Dynamic Query Histograms
INFOVIS '99 Proceedings of the 1999 IEEE Symposium on Information Visualization
My digital photos: where and when?
Proceedings of the 13th annual ACM international conference on Multimedia
Query previews in networked information systems: the case of EOSDIS
CHI EA '97 CHI '97 Extended Abstracts on Human Factors in Computing Systems
FaThumb: a facet-based interface for mobile search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Browsing large online data tables using generalized query previews
Information Systems
From Keyword Search to Exploration: Designing Future Search Interfaces for the Web
Foundations and Trends in Web Science
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In a networked information system (such as the NASA Earth Observing System--Data Information System (EOSDIS)), 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 low 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.