The cost structure of sensemaking

By Daniel M. Russell, M. Stefik, Peter Pirolli, Stuart Card. 1993

Making sense of a body of data is a common activity in any kind of analysis. Sensemaking is the process of searching for a representation and encoding data in that representation to answer task-specific questions. Different operations during sensemaking require different cognitive and external resources. Representations are chosen and changed to reduce the cost of operations in an information processing task. The power of these representational shifts is generally under-appreciated as is the relation between sensemaking and information retrieval. We analyze sensemaking tasks and develop a model of the cost structure of sensemaking. We discuss implications for the integrated design of user interfaces, representational tools, and information retrieval systems.

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Citations in the corpus

Jigsaw: Supporting Investigative Analysis through Interactive Visualization (2007, background): “Two, in particular, that our work addresses involve ( 1 ) the cost structure of scanning and selecting items for further attention and (2) analysts’ span of attention for evidence and hypotheses.”
Introduction to this Special Issue on Sensemaking (2011, methodology): “The power of efficiently working with external knowledge representations was central in Russell et al. (1993), as externalizing representations of knowledge determine which human or machine computations are easy or difficult, and consequently which activities can be performed more or less…”
Cognition (1999, unknown): “In the limiting case, the same theoretical construct appears both in linguistic analysis and psychological models of pragmatic abilities and that construct can become the subject of experimental research.”
The Sensemaking Process and Leverage Points for Analyst Technology as Identified Through Cognitive Task Analysis (2015, background): “Russell et al. (1993) have explicated the inner re-representational sensemaking process for a case in which large amounts of information had to be digested to create a curriculum for printer repairmen.”
Designing Creative AI Partners with COFI: A Framework for Modeling Interaction in Human-AI Co-Creative Systems (2022, background): “Russel et al. discussed the processes involved in sense-making: searching for representations, instantiate representations by encoding the representations, and utilizing the encoding in task-specific information [133].”
Structured labeling for facilitating concept evolution in machine learning (2014, methodology): “Tools for Sensemaking and Data Management Our proposed structured labeling solution to the concept evolution problem is inspired by work in sensemaking [23], the iterative process of organizing and understanding large amounts of data.”
Exploration and Explanation in Computational Notebooks (2018, unknown): “While some techniques, such as the “flashback” can be employed across media, others like split-screen sequences in film, are unique to particular media [30].”
Thinking with external representations (2010, background): “Cognitive processes drift to wherever they are more cost effective (Russell et al. 1993; Pirolli 2007).”
SearchTogether: an interface for collaborative web search (2007, background): “Sensemaking [28] ( i.e. , processing, organizing, and analyzing information) is intricately related to informational and exploratory searches.”
Exploratory Search: Beyond the Query-Response Paradigm (2009, background): “of time spent, resources utilized and opportunities lost when pursuing a search strategy instead of others (Russell et al., 1993).”
Design Considerations for Collaborative Visual Analytics (2007, unknown): “To better understand analytic contributions, we consult the sensemaking model [9, 39], which grounds the use of information visualization in a theory of how people search for, organize, and create new knowledge from source information.”
Investigating behavioral variability in web search (2007, background): “Through the research in areas such as information foraging [27], sensemaking [33], orienteering [25,36] search interface design [8], and information visualization [2], the research community is at the forefront of developing search technology that serves a diverse range of purposes.”
Fluid interaction for information visualization (2011, background): “As all users of such tools know, while we can expect any competent tool to be able to represent abstract data in graphical form, there is a certain class of InfoVis tools that take this a step further through engaging, compelling, and even absorbing user experiences that turn the analytical sensemak”
Collaborative visualization: Definition, challenges, and research agenda (2011, background): “20 With this focus, the design of collaborative visualization systems poses challenges in addition to those encountered during the design of visualization systems that are intended to be used by a single person.”