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Human-information interaction in epistemic activities

Published: 26 May 2010 Publication History

Abstract

We use, work, and think with information to be able to make decisions, solve problems, plan, analyze, forecast, and learn. These information-based activities can be classified as epistemic activities (EAs), as they all involve or are related to knowing. Often, we use computational tools in the form of Visual Cognitive Tools (VCTs) to help us carry out these EAs. VCTs maintain and display information in a digital, visual form to mediate our EAs. They sit at the interface between the mind and an information space and participate in the 'interplay' between the two. This paper presents a framework for a systematic exploration of the anatomical structure of the space between the mind and a given information space---that is, the space in which the interplay between the mind and information takes place. The motivation behind the creation of this framework is to facilitate the analysis and design of VCTs that can effectively support our EAs.

References

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Gotz, D. and Zhou, M. 2008 Characterizing users' visual analytic activity for insight provenance. In Proceedings of the IEEE Symposium on Visual Analytics Science and Technology, Columbus, Ohio, USA, Oct 21--23, pp. 123--130.
[2]
Spence, R. 1999 A framework for navigation. International Journal for Human-Computer Studies 51, 919--945.
[3]
Sedig, K. 2009 Interactive mathematical visualizations: Frameworks, tools, and studies. In Trends in Interactive Visualization: A State-of-the-Art Survey, 112--132. Springer.
[4]
Shrinivasan, Y. B. & van Wijk, J. J. 2008 Supporting the analytical reasoning process in information visualization. Proceedings of CHI'08, 1237--1246.
  1. Human-information interaction in epistemic activities

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    AVI '10: Proceedings of the International Conference on Advanced Visual Interfaces
    May 2010
    427 pages
    ISBN:9781450300766
    DOI:10.1145/1842993
    • Editor:
    • Giuseppe Santucci
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 26 May 2010

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