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Selecting one from many: The development of a scalable visualization tool

Abstract
This paper describes visualisation tools to support the task of selecting one object from a collection of many on the basis of its attribute values. For this frequently encountered task we identify a set of tools appropriate to a spectrum of collection sizes extending from hundreds of thousands to as few as ten or twenty. Although some of the tools have not previously been reported, and some have received only cursory attention in the literature, others are well known. This paper presents the tools in a coherent and consistent manner, showing relationships and progressions between them, identifying their principal attributes and relating them to the problem solver's cognitive task. We conclude with a proposal for integrating techniques within a single tool in order to deal with a continuum of working set sizes.
Type
Conference Contribution
Type of thesis
Series
Citation
Apperley, M., Spence, R., & Wittenburg, K. (2001). Selecting one from many: The development of a scalable visualization tool. In Proceedings IEEE Symposia on Human-Centric Computing Languages and Environments (pp. 366–372). Washington, DC, USA: IEEE. https://doi.org/10.1109/HCC.2001.995293
Date
2001
Publisher
IEEE
Degree
Supervisors
Rights
© 2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.