There are numerous problems associated with formulating queries on networked information systems. These include increased data volume and complexity, accompanied by slow network access. This article proposes a new approach to a network query user interfaces that consists of two phases: query preview and query refinement. This new approach is based on the concepts of dynamic queries and query previews, which guides users in rapidly and dynamically eliminating undesired records, reducing the data volume to a manageable size, and refining queries locally before submission over a network. Examples of two applications are given: a Restaurant Finder and a prototype for NASA's Earth Observing Systems Data Information Systems (EOSDIS). Data architecture is discussed, and user feedback is presented.
In a networked information system, 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 dynamic query formulation by volume preview. The two phases are the Query Preview and Query Refinement. In the Query Preview phase, users formulate an initial query by selecting desired attribute values. The volume of matching data sets is shown graphically on preview bars which aid users to rapidly eliminate undesired data sets, and 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 prefer the exploratory method to discover data patterns and exceptions during the query formulation process. Using this approach, we have developed dynamic query user interfaces to allow users to formulate their queries across a networked environment.
The Human-Computer Interaction Lab worked with a team for the Library of Congress (LC) to develop and test interface designs for LC's National Digital Library Program. Three iterations are described and illustrate the progression of the project toward a compact design that minimizes scrolling and jumping and anchors users in a screen space that tightly couples search and results. Issues and resolutions are discussed for each iteration and reflect the challenges of incomplete metadata, data visualization, and the rapidly changing web environment.
KEYWORDSdynamic query, query preview, network information system, visualization, direct manipulation, earth science INTRODUCTIONDynamic queries have been shown to be an effective technique to browse information, and to find patterns and exceptions. Dynamic queries involve the interactive control by a user of visual query parameters that generate rapid (100 ms update), animated, and visual displays of database search results. The data of early implementations was stored in local memory to guarantee optimal speed. Problems arise when the data is very large and distributed over a network.To overcome the problems of slow networks and data volume we propose a two-phase approach to query formulation using query previews and query refinements [1]. Preview mechanisms have been used in the past [2] and we believe that their use will be a major component of successful networked information systems interfaces (e.g. [3]). EOSDIS SCIENCE DATAWe use the example of NASA's Earth Observing System Data and Information System (EOSDIS) to illustrate our approach. Soon users will be able to retrieve earth science data from hundreds of thousands of datasets from centers around the country. Classic form fill-in interfaces for EOSDIS exist, but zero-hit queries are a problem and it is difficult to estimate how much data is available on a given topic. PREVIEW AND REFINEMENTIn our prototype interface users first select rough ranges for a few attributes (time, location and parameter) in the query previewer ( Figure 1). The impact of their selections is shown on the preview bars which are dynamically updated to reflect the number of datasets available: e.g. when a user selects North America, the preview bars reflect the distribution of datasets for North America. The query preview interface makes use of dataset counts maintained by providers about their holdings, and downloaded when users initiate an EOSDIS session. When the number of dataset is small enough, the metadata (i.e standardized data about the data) corresponding to the query refinement phase. © 1997. Copyright held by the authors 202A second dynamic query interface allows users to specify precise values for more attributes and further filter the result set. The timeline shows the coverage of the datasets, already zoomed on the years selected in the query preview. Large datasets appear at the top, small ones at the bottom, color coded by processing level. An active cursor highlights the corresponding attribute values: location, sensors, campaign, data center etc.The prototype shown in the video was implemented in Tcl/Tk but a partial Java implementation is also available (Figure 1 and 2) at: http://www.cs.umd.edu/projects/hcil/ Research/1995/dq-for-eosdis.htmlThe 2-step approach extends the use of dynamic queries to network environments. It was well received by test users from the scientific community and is being considered for prototyping in the operational EOSDIS system. We are now gathering real data for the prototype and working on data structures capable of handling 100,000...
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