dynamic query, query preview, network information system, visualization, direct manipulation, earth science Dynamic 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]). We 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. In 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. A 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.html The 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 records in the query refinement [4]. ACKNOWLEDGEMENTS
Meanwhile, in IVEA, we use the query previews REF .