Enhancing Interdisciplinary Human System Risk Research Through Modeling and Network Approaches

NASA's Human Research Program (HRP) supports research to reduce human health and performance risks inherent in future human space exploration missions. Understanding risk outcomes and contributing factors in an integrated manner allows HRP research to support development of efficient and effective mitigations from crossdisciplinary perspectives, and to enable resilient human and engineered systems for spaceflight. The purpose of this work is to support scientific collaborations and research portfolio management by utilizing modeling for analysis and visualization of current and potential future interdisciplinary efforts

ComputableViz: Mathematical Operators as a Formalism for Visualization Processing and Analysis

Data visualizations are created and shared on the web at an unprecedented speed, raising new needs and questions for processing and analyzing visualizations after they have been generated and digitized. However, existing formalisms focus on operating on a single visualization instead of multiple visualizations, making it challenging to perform analysis tasks such as sorting and clustering visualizations. Through a systematic analysis of previous work, we abstract visualization-related tasks into mathematical operators such as union and propose a design space of visualization operations. We realize the design by developing ComputableViz, a library that supports operations on multiple visualization specifications. To demonstrate its usefulness and extensibility, we present multiple usage scenarios concerning processing and analyzing visualization, such as generating visualization embeddings and automatically making visualizations accessible. We conclude by discussing research opportunities and challenges for managing and exploiting the massive visualizations on the web.Comment: 15 pages, 12 figures. In the ACM Conference on Human Factors in Computing Systems (CHI) 202

A Survey on the Role of Individual Differences on Visual Analytics Interactions: Masters Project Report

There is ample evidence in the visualization commu- nity that individual differences matter. These prior works high- light various traits and cognitive abilities that can modulate the use of the visualization systems and demonstrate a measurable influence on speed, accuracy, process, and attention. Perhaps the most important implication of this body of work is that we can use individual differences as a mechanism for estimating people’s potential to effectively leverage visual interfaces or to identify those people who may struggle. As visual literacy and data fluency continue to become essential skills for our everyday lives, we must embrace the growing need to understand the factors that divide our society, and identify concrete steps for bridging this gap. This paper presents the current understanding of how individual differences interact with visualization use and draws from recent research in the Visualization, Human-Computer Interaction, and Psychology communities. We focus on the specific designs and tasks for which there is concrete evidence of performance divergence due to individual characteristics. The purpose of this paper is to underscore the need to consider individual differences when designing and evaluating visualization systems and to call attention to this critical future research direction

Supporting conference attendees with visual decision making interfaces

Recent efforts in recommender systems research focus increasingly on human factors affecting recommendation acceptance, such as transparency and user control. In this paper, we present IntersectionExplorer, a scalable visualization to interleave the output of several recommender engines with user-contributed relevance information, such as bookmarks and tags. Two user studies at conferences indicate that this approach is well suited for technical audiences in smaller venues, and allowed the identification of applicability limitations for less technical audiences attending larger events. Copyright held by the owner/author(s)

Universal Design Manikin: Integrative Simulation and Visualization Techniques

This research demonstrates methods for integrating simulation and visualization techniques with the current tools used in design work-flows. The techniques are applied to human factors with a concentration on disabilities. A tool named Universal Design Manikin is developed. The tool integrates a virtual manikin and wheelchair with a coresponding graphical user interface. The research covers factors from a human scale of reach abilitiy to a large scale of building navigation. The research presents an opportunity for seamless collaboration between scientists and designers by integrating joint analysis tools with design tools. Methods for simulation and visualization of reach, vision, navigation, and spatial zones are presented.Master of ScienceArchitecture and Urban PlanningUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/95705/1/Schwartz_Masters.pd

Data visualization from a feminist perspective - Interview with Catherine D´Ignazio

Catherine D’Ignazio is a scholar, artist/designer and software developer who focuses on data literacy, feminist technology and civic art. She has run breastpump hackathons, created award-winning water quality sculptures that talk and tweet, and led walking data visualizations to envision the future of sea level rise. Her research at the intersection of gender, technology and the humanities has been published in the Journal of Peer Production, the Journal of Community Informatics, and the proceedings of Human Factors in Computing Systems (ACM SIGCHI). D’Ignazio is an Assistant Professor of Civic Media and Data Visualization at Emerson College, a faculty director of the Engagement Lab and a research affiliate at the MIT Center for Civic Media

Reducing Cognitive Load Using Adaptive Uncertainty Visualization

Uncertainty is inherent in many real-world settings; for example, in a combat situation, darkness may prevent a soldier from classifying approaching troops as friendly or hostile. In an environment plagued with uncertainty, decision-support systems, such as sensor-based networks, may make faulty assumptions about field conditions, especially when information is incomplete, or sensor operations are disrupted. Displaying the factors that contribute to uncertainty informs the decision-making process for a human operator, but at the expense of limited cognitive resources, such as attention, memory, and workload. This research applied principles of perceptual cognition to human-computer interface design to introduce uncertainty visualizations in an adaptive approach that improved the operator\u27s decision-making process, without unduly burdening the operator\u27s cognitive load. An adaptive approach to uncertainty visualization considers the cognitive burden of all visualizations, and reduces the visualizations according to relevancy as the user\u27s cognitive load increases. Experiments were performed using 24 volunteer participants using a simulated environment that featured both intrinsic load, and characteristics of uncertainty. The experiments conclusively demonstrated that adaptive uncertainty visualization reduced the cognitive burden on the operator\u27s attention, memory, and workload, resulting in increased accuracy rates, faster response times, and a higher degree of user satisfaction. This research adds to the body of knowledge regarding the use of uncertainty visualization in the context of cognitive load. Existing research has not identified techniques to support uncertainty visualization, without further burdening cognitive load. This research identified principles, such as goal-oriented visualization, and salience, which promote the use of uncertainty visualization for improved decision-making without increasing cognitive load. This research has extensive significance in fields where both uncertainty and cognitive load factors can reduce the effectiveness of decision-makers, such as sensor-based systems used in the military, or in first-responder situations

Visual Perception and Cognition in Image-Guided Intervention

Surgical image visualization and interaction systems can dramatically affect the efficacy and efficiency of surgical training, planning, and interventions. This is even more profound in the case of minimally-invasive surgery where restricted access to the operative field in conjunction with limited field of view necessitate a visualization medium to provide patient-specific information at any given moment. Unfortunately, little research has been devoted to studying human factors associated with medical image displays and the need for a robust, intuitive visualization and interaction interfaces has remained largely unfulfilled to this day. Failure to engineer efficient medical solutions and design intuitive visualization interfaces is argued to be one of the major barriers to the meaningful transfer of innovative technology to the operating room. This thesis was, therefore, motivated by the need to study various cognitive and perceptual aspects of human factors in surgical image visualization systems, to increase the efficiency and effectiveness of medical interfaces, and ultimately to improve patient outcomes. To this end, we chose four different minimally-invasive interventions in the realm of surgical training, planning, training for planning, and navigation: The first chapter involves the use of stereoendoscopes to reduce morbidity in endoscopic third ventriculostomy. The results of this study suggest that, compared with conventional endoscopes, the detection of the basilar artery on the surface of the third ventricle can be facilitated with the use of stereoendoscopes, increasing the safety of targeting in third ventriculostomy procedures. In the second chapter, a contour enhancement technique is described to improve preoperative planning of arteriovenous malformation interventions. The proposed method, particularly when combined with stereopsis, is shown to increase the speed and accuracy of understanding the spatial relationship between vascular structures. In the third chapter, an augmented-reality system is proposed to facilitate the training of planning brain tumour resection. The results of our user study indicate that the proposed system improves subjects\u27 performance, particularly novices\u27, in formulating the optimal point of entry and surgical path independent of the sensorimotor tasks performed. In the last chapter, the role of fully-immersive simulation environments on the surgeons\u27 non-technical skills to perform vertebroplasty procedure is investigated. Our results suggest that while training surgeons may increase their technical skills, the introduction of crisis scenarios significantly disturbs the performance, emphasizing the need of realistic simulation environments as part of training curriculum