ASIS&T 2006 START Conference Manager    

Interaction: Beyond Retrieval

Karl Fast, Xia Lin, Yan Qu, Huahai Yang, Xiaolong Zhang

ASIS&T Annual Meeting - 2006 (ASIS&T 2006)
Austin, Texas, November 3-9, 2006


Abstract

What is the role of interaction in the next generation of information systems? In classical information retrieval systems, interaction enables and facilitates the search for relevant documents. Typically, the interface is based on a three-pronged interaction paradigm: formulating keyword queries, scanning results lists, and browsing hypertext structures. This paradigm has been enormously successful. It is the basis for almost every modern, mainstream, large-scale information system, from digital libraries to web search engines and corporate intranets. But is this retrieval-centric approach to interaction a suitable foundation for the next generation of information systems? Is it a satisfactory basis for supporting the full cycle of knowledge discovery, creation, and use?

When compared with the physical world, interaction in digital environments is sparse. This is especially true in the realm of cognitive and knowledge work activities. In the physical world, these activities usually involve paper documents. Paper supports a number of simple yet invaluable interactions. It can be cut, folded, rearranged, sorted, and annotated. With paper documents these interactions are easy and obvious, but with digital documents these interactions are often complex and cumbersome, if they are at all possible (Sellen & Harper, 2002). What is more, and critical, is that even simple interactions are an integral part of cognitive and knowledge work activities (Fast & Sedig, 2005; Kirsh, 1997; Marshall, 2003). Interacting with the world is more than a mechanism for accomplishing goals—it is crucial to how we formulate our goals, shape our thoughts, and understand the world. As a result, interaction is an integral part of many cognitively complex activities, such as wayfinding, sense making, decision making, interpreting, modeling, and problem solving (Dourish, 2001; Fast & Sedig, 2005; Mirel, 2005). Designing for these kind of activities requires interaction mechanisms that go beyond the familiar query-search-browse paradigm.

This panel will re-examine the concept of interaction, viewing it as an essential ingredient in the next-generation of information systems. In this view, interaction is connected to all the elements of internal and external cognition (including physical artifacts and digital representations), as well as all the modalities, such as vision, sound, and haptics. This approach offers explanations to long-standing questions, such as why information visualization has succeeded in niche markets but not in mainstream applications. More importantly, it advocates a holistic view of the information life cycle, where retrieval is one part of a chain that includes creation and use of information as well.

This panel brings together interested researchers to discuss their views on the theoretical and practical issues of interaction in next-generation digital knowledge environments, and share their recent research findings. Of particular interest to the panel is interaction with visual representations, which is of central concern for information visualization and 3D virtual environments. The panel consists of five researchers: Karl Fast will present a descriptive taxonomy of interactions with visual representations for digital library environments; Yan Qu will introduce sense-making as a theoretical framework that may guide the development of interactive systems in knowledge environment; Xia Lin will stress the significance of content representation, and argue for a tight coupling between content representation and interaction; Xiaolong Zhang will summarize the role 3D virtual environments may play in support of integrated information environments. Huahai Yang will discuss the possibility of combining visual representation with other modalities in interacting with information environment, and demonstrate its integration with natural language based retrieval.


  
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