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Neural Correlates of Multidimensional Visualizations: An fMRI Comparison of Bubble and Three-Dimensional Surface Graphs Using Evolutionary Theory

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Abstract

In this article, an evolutionary argument to explain how people comprehend graphs is put forth. A theory of evolutionary fit, which argues for the correspondence between information presentation and evolutionarily adaptive brain structures, is proposed. This is complementary to cognitive fit, which argues for a correspondence between task and information presentation. In two fMRI experiments, we test this theory by comparing brain activation during a graphic comprehension task using two different graph types: bubble graphs and three-dimensional surface graphs. In accordance with our hypotheses, we find that comprehension of three-dimensional surface graphs results in greater activation of the ventral stream and greater accuracy in graphical comprehension than bubble graphs. We argue that this is because the human visual system is evolutionarily adapted to the comprehension of three-dimensional surfaces. The implication is that choosing graphical representations that match what the brain is evolutionarily specialized to process can enhance graphic comprehension.

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... From this perspective, information representations can possess subjective and temporal bearings, and importantly, each information representation can reflect information scenarios with varying levels of latent information facets. Big data phenomena and the science of data analytics have led to a massive growth in the number, diversity and forms of information representations such as user-generated social media content, machine-generated data from IOT applications and complex 3D visualizations (Kar & Dwivedi, 2020;Walden, Cogo, Lucus, Moradiabadi, & Safi, 2018). Manually mapping such a diverse and expanding set of information representations using extant cognitive fit models would be extremely inefficient. ...
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... From this perspective, information representations can possess subjective and temporal bearings, and importantly, each information representation can reflect information scenarios with varying levels of latent information facets. Big data phenomena and the science of data analytics have led to a massive growth in the number, diversity and forms of information representations such as user-generated social media content, machine-generated data from IOT applications and complex 3D visualizations (Kar & Dwivedi, 2020;Walden, Cogo, Lucus, Moradiabadi, & Safi, 2018). Manually mapping such a diverse and expanding set of information representations using extant cognitive fit models would be extremely inefficient. ...
... Hong, Thong, andTam (2004) compared 'list' with 'matrix' for online shopping andCarte (1998) applied CFT to study how subjects using maps (geographic information systems) performed under different task conditions. Later, the CFT research stream widened to examine domain knowledge influence (Khatri, Vessey, Ramesh, Clay, & Park, 2006), mobile representation of online content (Adipat et al., 2011), self-reported cognitive effort (Bacic & Henry, 2018) and 3D visualizations (Walden et al., 2018). Fig. 1-B is a generalization of traditional cognitive fit models (Vessey, 1991). ...
... We believe that ACF is a significant departure from the long and valuable history of past cognitive fit research which has focused on manual mapping of specific information representations to specific tasks (i.e., Vessey, 1991to Walden et al., 2018. ACF resolves the practical implementation challenges of manual approaches to determine cognitive fit in the context of big data, resulting complexities and an ever-increasing array of information representations. ...
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Article
This article asks whether, and when, participants benefit from seeing each other's faces in computer-mediated communication. Although new technologies make it relatively easy to exchange images over the Internet, our formal understanding of their impacts is not clear. Some theories suggest that the more one can see of one's partners, the better one will like them. Others suggest that long-term virtual team members may like each other better than would those who use face-to-face interaction. The dynamic underlying this latter effect may also pertain to the presentation of realistic images compared with idealized virtual perceptions. A field experiment evaluated the timing of physical image presentations for members of short-term and long-term virtual, international groups. Results indicate that in new, unacquainted teams, seeing one's partner promotes affection and social attraction, but in long-term online groups, the same type of photograph dampens affinity.
Article
In 2 experiments, high- and low-spatial ability students viwed a computer-generated animation and listened simultaneously (concurrent group) or successively (successive group) to a narration that explained the workings either of a bicycle tire pump (Experiment 1) or of the human respiratory system (Experiment 2). The concurrent group generated more creative solutions to subsequent transfer problems than did the successive group; this contiguity effect was strong for high- but not for low-spatial ability students. Consistent with a dual-coding theory, spatial ability allows high-spatial learners to devote more cognitive resources to building referential connections between visual and verbal representations of the presented material, whereas low-spatial ability learners must devote more cognitive resources to building representation connections between visually presented material and its visual representation.
Conference Paper
Visualizations often seek to aid viewers in assessing the big picture in the data, that is, to make judgments about aggregate properties of the data. In this paper, we present an empirical study of a representative aggregate judgment task: finding regions of maximum average in a series. We show how a theory of perceptual averaging suggests a visual design other than the typically-used line graph. We describe an experiment that assesses participants' ability to estimate averages and make judgments based on these averages. The experiment confirms that this color encoding significantly outperforms the standard practice. The experiment also provides evidence for a perceptual averaging theory.
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Graphicacy is described as the educated counterpart of the visual-spatial aspect of human intelligence and communication; it is seen as fundamental in education along with literacy, numeracy, and articulacy. Early investigations of the visual-spatial aspect of human intelligence are described. Since maps, diagrams, photography, and other spatial documents are the tools of graphicacy as well as the basis of geography it is argued that the skill of graphicacy is best imparted at school, college, and university level through geography. An attempt is made to define the content of graphicacy as an intellectual discipline.
Article
A laboratory experiment was conducted to assess the influence of color and information presentation differences on user perceptions and decision making under varying time constraints. Three different information presentations were evaluated: tabular, graphical, and combined tabular-graphical. Tabular reports led to better decision making and graphical reports led to faster decision making when time constraints were low. The combined report, which integrated the advantages associated with both tabular and graphical presentation, was the superior report format in terms of performance ad was rated very highly by decision makers. Color led to improvements in decision making; this was especially pronounced when high time constraints were present.
Article
A review of research carried out during the past decade indicates that the map‐drawing and map‐using abilities of young children had previously been underestimated. Experiments have shown that primary school children are able to draw from memory simple sketch‐maps of the area around their home and to recognise features on aerial photographs and large‐scale plans of the same area. Research undertaken with secondary school pupils has provided a greater understanding of the difficulties they experience in understanding contour patterns as representations of relief, and in correlating Ordnance Survey maps with aerial photographs. Among younger children there is little difference between the mapping abilities of boys and girls, but, as they grow older, boys consistently perform better than girls of the same age in map‐drawing and map‐reading tasks.
Article
An experiment was conducted to relate characteristics of an information system and a decision maker to the resulting decision making performance in a simulated inventory/production environment. One of the six independent variables which were analyzed, four (form of presentation, available of decision aids, availability of exception reporting, amount of information provided) were related to information system characteristics, the other two (decision making style, knowledge of functional area) described decision maker characteristics. The dependent variables, or the decision making quality variables, analyzed were cost performance, time performance, and the number of reports requested for decision making. The experimental setting, findings, and the number of reports requested for decision making. The experimental setting, findings, and the implication of the findings for information system design are discussed.
Article
Decision making, analytical reasoning, learning, and sense making are complex cognitive activities. Nowadays, such activities are typically performed through the mediation of interactive computational tools. Examples include visual analytics, decision support, information visualization, and educational tools. To perform such activities, humans often interact with visual representations (VRs) of information at the visually perceptible interface of these tools. Through interaction, a joint, coordinated cognitive system is formed in which humans and tools work together to perform such aforementioned activities. This partnership results in a number of relational properties—those depending on both humans and tools—that researchers and designers must be aware of if such tools are to effectively support the performance of complex cognitive activities. This paper presents 10 properties of interactive VRs that are essential (i.e., present in all instances), are dependent on both humans and tools, and whose values can be adjusted through interaction. By adjusting the values of these properties, better coordination between humans and tools can be effected, leading to higher-quality performance of complex cognitive activities. This paper examines how the values of these properties affect cognitive processing and visual reasoning, and demonstrates the necessity of making their values adjustable—all of which is situated within a broader theoretical framework concerned with human-information interaction in complex cognitive activities. The framework presented here can function as a support structure for systematic research, design, and evaluation of interactive computational tools that support complex cognitive activities in numerous fields including information visualization, health informatics, visual analytics, and educational technology.
Article
We assessed the ability of the cognitive fit theory to explain the performance of certain display formats on multiattribute judgment tasks. This theory suggests that for most effective and efficient problem solving to occur, the problem representation and any tools or aids employed should all support the strategies (methods or processes) required to perform that task. The theory was tested by assessing performance with schematic faces, graphs, and tables on a bankruptcy prediction task. Bankruptcy prediction involves integrating a large amount of data (a number of financial indicators over a number of years), as well as referring to ranges and/or levels of financial indicators. Schematic faces provide a cognitive fit with such tasks since the information in a face can be processed holistically; however, they do not permit decision makers to refer to the underlying data. Graphs facilitate a different integrating process; further, they preserve characteristics of the underlying data. Tables, on the other hand, do not aid the decision maker in integrating information; they provide only the underlying data values. It was hypothesized that graphs would provide the best cognitive fit for the bankruptcy prediction task since they permit processing both integrated and discrete data. Participants made judgments with two of the three display formats, at two levels of information load, in a fractional factorial design. The information load manipulation was designed to provide meaningful and meaningful plus redundant information to the decision maker in a test of information load “per se.” The research findings provided substantial support for the theory of cognitive fit. The findings also have implications for the study of information load.
Article
Since most interactive systems use either graphical or tabular displays, this experiment contrasts the effectiveness of the two displays in making the production scheduling decision in low and intermediate levels of environmental complexity. The study concludes that tabular aids outperform the graphical aids in environments with low complexity, replicating an earlier study. In intermediate complexity environments, the graphical aids outperform the tabular aids. These findings may resolve many conflicts in the literature on data displays.
Article
A laboratory experiment was conducted to assess the influence of graphical and color-enhanced information presentation on decision quality, decision-making time and user perceptions of information systems attributes. The experimental design examined the main and interaction effects of report format, color, and individual differences (field dependence/independence) among the subjects. The findings indicate that the claims made about the benefits of color-enhanced reports are subject to qualification. Even though color influenced decision-making quality in general, and to some extent color was more beneficial for graphical than tabular reports, its most significant impact was on the performance of field-dependents. The decision-making quality of field-dependents with color-enhanced reports was 73% better than field-dependents who did not have such reports. There were no performance differences between subjects who used tabular and graphical reports. This outcome is explained by taking into consideration the underlying nature of the task given to the subjects and how the reports were organized to support this task. This finding suggests that proponents of graphical presentation must qualify their claims to environments where there is a clearly defined rationale for the potential benefits of graphical report usage.
Article
The use of computer based information-decision systems to support decision making in organizations has increased significantly in the last decade. Very little effort has been devoted, however, to determine what relationships exist between the structure of information presented for decision making and the ensuing effectiveness of the decision. This article summarizes a series of experiments. The Minnesota Experiments, which were conducted to examine the significance of various information system characteristics on decision activity. Several research programs administered in the period 1970-1975 are discussed in this paper. By varying the manner in which information was provided to participants in each experiment, the impact of various information system characteristics and individual differences on decision effectiveness was investigated. Analysis of the results shows that, in many cases, the decisions/decision-making process of the participants was affected by the information system structure and/or attributes of individual decision makers. The results suggest guidelines for the designers of information systems and fruitful avenues for continued research.
Article
Why do our eyes face forward, and why do many mammals have eyes facing sideways? Here, we describe results suggesting that the degree of binocular convergence is selected to maximize how much the mammal can see in its environment. Mammals in non-cluttered environments can see the most around them with panoramic, laterally directed eyes. Mammals in cluttered environments, however, can see best when their eyes face forward, for binocularity has the power of “seeing through” clutter out in the world. Evidence across mammals closely fits the predictions of this “X-ray” hypothesis.
Article
Expertise management systems are being widely adopted in organizations to manage tacit knowledge. These systems have successfully applied many information technologies developed for document management to support collection, processing, and distribution of expertise information. In this paper, we report a study on the potential of applying visualization techniques to support more effective and efficient exploration of the expertise information space. We implemented two widely applied dimensionality reduction visualization techniques, the self-organizing map (SOM) and multidimensional scaling (MDS), to generate compact but distorted (due to the dimensionality reduction) map visualizations for an expertise data set. We tested cognitive fit theory in our context by comparing the SOM and MDS displays with a standard table display for five tasks selected from a low-level, domain-independent visual task taxonomy. The experimental results based on a survey data set of research expertise of the business school professors suggested that using both SOM and MDS visualizations is more efficient than using the table display for the associate, compare, distinguish, and cluster tasks, but not the rank task. Users generally achieved comparable effectiveness for all tasks using the tabular and map displays in our study.
Article
Compensatory adaptation theory makes two key predictions. On one hand, the theory predicts that electronic communication media in general will pose obstacles to complex communication between collaborators, when compared with the face-to-face medium, which will lead to an increase in cognitive effort and communication ambiguity. On the other hand, the theory also predicts that those obstacles will be met with compensatory adaptation, whereby electronic communication users will attempt to make up for the obstacles by modifying their communication behavior. This will in turn lead to a reduction in communication fluency. This study extends compensatory adaptation theory by also predicting that the burden of compensating for electronic communication media obstacles will fall primarily on those who attempt to convey information, as opposed to those who receive it. Those predictions are tested through an experiment involving 230 students, whose data are analyzed through nonparametric tests. All predictions are supported by the data analysis results. The use of a Web-based quasi-synchronous electronic communication medium, when compared with the face-to-face medium, increased perceived cognitive effort by approximately 12% and perceived communication ambiguity by about 19%. Communication fluency was reduced by about 90%. Perceived compensatory encoding effort (i.e., the effort spent by information givers) was increased by approximately 26%, and perceived compensatory decoding effort (i.e., the information receivers' effort) by a statistically insignificant percentage.
Article
The goal of Artificial Intelligence is to identify and solve tractable information processing problems. In so doing, two types of theory arise. Here, they are labelled Types 1 and 2, and their characteristics are outlined. This discussion creates a more than usually rigorous perspective of the subject, from which past work and future prospects are briefly reviewed.
Article
We distinguish diagrammatic from sentential paper-and-pencil representations of information by developing alternative models of information-processing systems that are informationally equivalent and that can be characterized as sentential or diagrammatic. Sentential representations are sequential, like the propositions in a text. Diagrammatic representations are indexed by location in a plane. Diagrammatic representations also typically display information that is only implicit in sentential representations and that therefore has to be computed, sometimes at great cost, to make it explicit for use. We then contrast the computational efficiency of these representations for solving several illustrative problems in mathematics and physics. When two representations are informationally equivalent, their computational efficiency depends on the information-processing operators that act on them. Two sets of operators may differ in their capabilities for recognizing patterns, in the inferences they can carry out directly, and in their control strategies (in particular, the control of search). Diagrammatic and sentential representations support operators that differ in all of these respects. Operators working on one representation may recognize features readily or make inferences directly that are difficult to realize in the other representation. Most important, however, are differences in the efficiency of search for information and in the explicitness of information. In the representations we call diagrammatic, information is organized by location, and often much of the information needed to make an inference is present and explicit at a single location. In addition, cues to the next logical step in the problem may be present at an adjacent location. Therefore problem solving can proceed through a smooth traversal of the diagram, and may require very little search or computation of elements that had been implicit.
Article
This paper explains how visual representations of data enable individual sensemaking in data exploration tasks. We build upon theories of human perception and cognition, including Cognitive Fit Theory, to explain what aspects of visual representations facilitate sensemaking for the viewer. We make three primary contributions. First, we give a general characterization of visual representations that would be used for data exploration tasks. These representations consist of a scene, objects within the scene, and the characteristics of those objects. Second, we extend Cognitive Fit Theory into the data exploration task domain. We explain that the data exploration task has a number of spatial subtasks including observing data points, looking for patterns or outliers, making inferences, comparing observed facts or patterns to one's own knowledge, generating hypotheses about the data, and drawing analogies from the context being observed to another context. Third, we offer a set of theoretical propositions about how visual representations of data can serve the sensemaking goal. Specifically, visual representations best facilitate sensemaking in data exploration tasks when they (1) support the four basic human visual perceptual approaches of association, differentiation, ordered perception, and quantitative perception, (2) have strong Gestalt properties, (3) are consistent with the viewer's stored knowledge, and (4) support analogical reasoning. We propose that visual representations should possess several of these four aspects to make them well-suited for the task of data exploration.
Article
Most of the recent research in data visualization has focused on technical and aesthetic issues involved in the manipulation of graphs, specifically on features that facilitate data exploration to make graphs interactive and dynamic. The present research identifies a gap in the existing knowledge of graph construction, namely potential problems in both 3D and 2D graphs that will impede comprehension of information when three or more variables are used in a graphical representation. Based on theories regarding perceptual issues of graph construction (Bertin 1981; Pinker 1991), we evaluate specific cases where 3D graphs may outperform 2D graphs, and vice-versa. Two experiments have been conducted to test these hypotheses, and 3D graphs have been found to consistently outperform 2D graphs in all of our experimental scenarios. A third experiment has been conducted to identify situations where 2D graphs might perform at least as well as 3D graphs, but its results suggest that 3D graphs outperform 2D graphs even for simple tasks, thus leading to the conclusion that 3D graphs perform better than 2D graphs under all task conditions with more than two variables.
Article
Advances in graphical technology have now made it possible for us to interact with information in innovative ways, most notably by exploring multimedia environments and by manipulating three-dimensional virtual worlds. Many benefits have been claimed for this new kind of interactivity, a general assumption being that learning and cognitive processing are facilitated. We point out, however, that little is known about the cognitive value of any graphical representations, be they good old-fashioned (e.g. diagrams) or more advanced (e.g. animations, multimedia, virtual reality). In our paper, we critique the disparate literature on graphical representations, focusing on four representative studies. Our analysis reveals a fragmented and poorly understood account of how graphical representations work, exposing a number of assumptions and fallacies. As an alternative we propose a new agenda for graphical representation research. This builds on the nascent theoretical approach within cognitive science that analyses the role played by external representations in relation to internal mental ones. We outline some of the central properties of this relationship that are necessary for the processing of graphical representations. Finally, we consider how this analysis can inform the selection and design of both traditional and advanced forms of graphical technology.
Article
As networks of all forms become ubiquitous, the network-based information they generate is increasingly being used in a wide variety of analysis tasks. In organizations, social network analysis techniques are being applied to a number of domains, particularly the understanding of knowledge stocks and flows. Because this information is generated from large data sets, computerized visualizations of it are very helpful for accomplishing these complex tasks. This paper presents a model for evaluating the effectiveness of network visualizations based on theories of cognitive fit, working memory capacity, and information load. The model was empirically tested in two experiments using two types of data visualizations from two different social networks. Results support the theoretical model, illustrating that variations in cognitive fit and working memory interact. Findings suggest that visualizations can enable superior outcomes when they are designed to support this interaction.