Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

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Subject: search.filters.subject.direct manipulation

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Now showing 1 - 4 of 4
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    Interface and Data Architecture for Query Preview in Network Information Systems
    (1997) Doan, Khoa; Plaisant, Catherine; Shneiderman, Ben; Bruns, Tom; ISR
    There are numerous problems associated with formulating queries on networked information systems. These include data diversity, data complexity, network growth, varied user base, and slow network access. This paper proposes a new approach to a network query user interface which 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 datasets, reducing the data volume to manageable size, and refining queries locally before submission over a network. Examples of 2 applications are given: a Restaurant Finder and prototype with NASA's Earth Observing Systems -- Data Information Systems (EOSDIS). Data architecture is discussed and user's feedback is presented. Dynamic queries and query previews provide solutions to many existing problems in querying networked information systems.
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    Design and Evaluation of Incremental Data Structures and Algorithms for Dynamic Query Interfaces
    (1997) Tanin, Egemen; Beigel, Richard; Shneiderman, Ben; ISR
    Dynamic query interfaces (DQI) are a recently developed database access mechanism that provides continuous real-time feedback to the user during query formulation. Previous work shows that DQI are an elegant and powerful interface to small databases. Unfortunately, when applied to large databases, previous DQI algorithms slow to a crawl. We present a new incremental approach to DQI algorithms that works well with large databases, both in theory and in practice.
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    Query Previews in Networked Information Systems
    (1995) Doan, Khoa; Plaisant, C.; Shneiderman, B.; ISR; CSHCN
    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 of dynamic query formulation by volume preview. The two phases are the Query Preview andQuery 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 Query 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.
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    Alpha Slider: Searching Textual Lists with Sliders
    (1993) Osada, M.; Liao, Holmes; Shneiderman, B.; ISR
    AlphaSlider is a query interface that uses a direct manipulation slider to select words, phrases, or names from an existing list. This paper introduces a prototype of AlphaSlider, describes the design issues, reports on an experimental evaluation, and offers directions for further research. The experiment tested 24 subjects selecting items from lists of 40, 80, 160, and 320 entries. Mean selection times only doubled with the 8-fold increase in list length. Users quickly accommodated to this selection method.