Visualization schemes for domain novices exploring a topic space: the navigation classification scheme

  • Authors:

  • John E. Leide;Andrew Large;Jamshid Beheshti;Martin Brooks;Charles Cole

  • Affiliations:

  • Graduate School of Library and Information Studies, McGill University, 3459 McTavish Street, Montreal, Que., Canada H3A 1Y1;Graduate School of Library and Information Studies, McGill University, 3459 McTavish Street, Montreal, Que., Canada H3A 1Y1;Graduate School of Library and Information Studies, McGill University, 3459 McTavish Street, Montreal, Que., Canada H3A 1Y1;Institute for Information Technology, National Research Council of Canada, Montreal Road, Building M-50 Ottawa, Ont., Canada K1A 0R6;Graduate School of Library and Information Studies, McGill University, 3459 McTavish Street, Montreal, Que., Canada H3A 1Y1

  • Venue:
  • Information Processing and Management: an International Journal
  • Year:
  • 2003

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Abstract

In this article and two other articles which conceptualize a future stage of the research program (Leide, Cole, Large, & Beheshti, submitted for publication; Cole, Leide, Large, Beheshti, & Brooks, in preparation), we map-out a domain novice user's encounter with an IR system from beginning to end so that appropriate classification-based visualization schemes can be inserted into the encounter process. This article describes the visualization of a navigation classification scheme only. The navigation classification scheme uses the metaphor of a ship and ship's navigator traveling through charted (but unknown to the user) waters, guided by a series of lighthouses. The lighthouses contain mediation interfaces linking the user to the information store through agents created for each. The user's agent is the cognitive, model the user has of the information space, which the system encourages to evolve via interaction with the system's agent. The system's agent is an evolving classification scheme created by professional indexers to represent the structure of the information store. We propose a more systematic, multidimensional approach to creating evolving classification/indexing schemes, based on where the user is and what she is trying to do at that moment during the search session.