Using a human cognition model in the creation of collaborative knowledge visualizations

Green, Tera Marie; Ribarsky, William

doi:10.1117/12.777189

Cited by 9 publications

(11 citation statements)

References 15 publications

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“…Reasoning is much more than a series of delineated tasks; depending on complexity, reasoning can combine any number of heuristics and use top-down and bottom-up thought constructions combinatorially. (For more discussion, please see [1].) Any generally-applicable model of human cognition must deal with this complexity sooner or later.…”

Section: Considering the Pirolli And Card Sensemaking Modelmentioning

confidence: 99%

“…In a previous paper [1], we discussed the value of considering performance characteristics of human reasoning, problem-solving, and decision-making, in addition to the more familiar perceptual processes, to develop information and knowledge visualizations. The driving force behind this program of research is the need to develop applications capable of attacking today's complex and critical problems with the required depth of reasoning and analysis that will support their solution.…”

Section: Introductionmentioning

confidence: 99%

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Building and Applying a Human Cognition Model for Visual Analytics

Green

Ribarsky

Fisher

2009

Information Visualization

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It is well known that visual analytics addresses the difficulty of evaluating and processing large quantities of information. Less often discussed are the increasingly complex analytic and reasoning processes that must be applied in order to accomplish that goal. Success of the visual analytics approach will require us to develop new visualization models that predict how computational processes might facilitate human insight and guide the flow of human reasoning. In this paper, we seek to advance visualization methods by proposing a framework for human "higher cognition" that extends more familiar perceptual models.Based on this approach, we suggest guidelines for the development of visual interfaces that better integrate complementary capabilities of humans and computers. While many of these recommendations are novel, some can be found in existing visual analytics applications. In the latter case, much of the value of our contribution lies in the deeper rationale that the model provides for those principles. We then assess these visual analytics guidelines through the evaluation of several visualization examples. Lastly, we discuss steps that can be taken towards a predictive human cognition model.

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Section: Considering the Pirolli And Card Sensemaking Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Building and Applying a Human Cognition Model for Visual Analytics

Green

Ribarsky

Fisher

2009

Information Visualization

Self Cite

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“…In earlier work ( [12], [13], [14]) we outlined an operational framework, the Human Cognition Model (HCM), whose objective was to inform customization of human-computer cognitive collaboration in mixed-initiative interactive systems. Todays information visualization applications tend to be passive; primary interface processes sit and wait for user initiation.…”

Section: The Human Cognition Modelmentioning

confidence: 99%

“…3. The Human Cognition Model [13] complex. When the task is to find items similar to an exemplar, for example, all the cognitive processes from the simpler search tasks serve to feed more complex processes, such as inferential and deductive reasoning, which utilize more complicated models or rules for comparison and contrast.…”

Section: The Human Cognition Modelmentioning

confidence: 99%

“…[13]) include an interface being aware of and predicting user intent in order to keep pertinent information visible, supporting human working memory, caching data subsets of interest to introduce them in a sequence and timing that will support the flow of reasoning and ongoing discovery, and conducting analyses and providing their findings in a contextual framework, which supports a variety of hypotheses generation. In short, the HCM sketches out an interface that collaborates on cognitive processes per se, informed by a growing understanding of human preferences, abilities and limitations.…”

Section: The Human Cognition Modelmentioning

confidence: 99%

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The Personal Equation of Complex Individual Cognition during Visual Interface Interaction

Green

Fisher

2011

Human Aspects of Visualization

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Abstract. This chapter considers the need for a better understanding of complex human cognition in the design of interactive visual interfaces by surveying the availability of pertinent cognitive models and applicable research in the behavioral sciences, and finds that there are no operational models or useful precedent to effectively guide the design of visually enabled interfaces. Further, this chapter explores the impact of individual differences, and in particular, inherent differences such as personality factors, on complex cognition. Lastly, it outlines how knowledge of human individuality, coupled with what is known about complex cognition, is being used to develop predictive measures for interface interaction design and evaluation, a research program known as the Personal Equation of Interaction. . . .

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Visual Analytics in Environmental Research: A Survey on Challenges, Methods and Available Tools

Komenda

Schwarz

2013

IFIP Advances in Information and Communication Technology

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Abstract. Visual analytics approaches bring an innovative and effective way how to deliver the knowledge from a particular domain to an individual user. With the use of visual analytics methods we can easily discover the unexpected relations and interesting patterns, which are hidden in the huge data warehouses. It builds on the human mind's ability to understand the complex visualization of information. In this paper we introduce the potential usefulness of visual analytics for researchers working in the field of environmental informatics. Current challenges beyond the survey are described here, including the summary of particular well-proven tools and scenarios, which can be applied in many various fields of environmental research.

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Using a human cognition model in the creation of collaborative knowledge visualizations

Cited by 9 publications

References 15 publications

Building and Applying a Human Cognition Model for Visual Analytics

Building and Applying a Human Cognition Model for Visual Analytics

The Personal Equation of Complex Individual Cognition during Visual Interface Interaction

Visual Analytics in Environmental Research: A Survey on Challenges, Methods and Available Tools

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