Mind the Gap: the Importance of Pluralistic Discourse in Computing for Mental Health

A large amount of HCI research leverages studies from psychology to try to understand how humans work. Unfortunately, there is often a disconnect between the tightly- controlled laboratory studies being referenced and the application of this knowledge in practice. At the same time, many mental health practitioners are beginning to turn toward computational tools to help stretch limited resources and support equitable access to mental healthcare. These efforts could be dramatically enhanced by leveraging what the HCI community has learned about promoting active engagement and designing unobtrusive interfaces. By facilitating collaboration between HCI researchers and practitioners in the field of human services, we are working to understand how our historically separate disciplines might better be able to support one another and together reimagine what constitutes a therapeutic intervention in the 21st century

An Affordance-Based Framework for Human Computation and Human-Computer Collaboration

Visual Analytics is “the science of analytical reasoning facilitated by visual interactive interfaces” [70]. The goal of this field is to develop tools and methodologies for approaching problems whose size and complexity render them intractable without the close coupling of both human and machine analysis. Researchers have explored this coupling in many venues: VAST, Vis, InfoVis, CHI, KDD, IUI, and more. While there have been myriad promising examples of human-computer collaboration, there exists no common language for comparing systems or describing the benefits afforded by designing for such collaboration. We argue that this area would benefit significantly from consensus about the design attributes that define and distinguish existing techniques. In this work, we have reviewed 1,271 papers from many of the top-ranking conferences in visual analytics, human-computer interaction, and visualization. From these, we have identified 49 papers that are representative of the study of human-computer collaborative problem-solving, and provide a thorough overview of the current state-of-the-art. Our analysis has uncovered key patterns of design hinging on human- and machine-intelligence affordances, and also indicates unexplored avenues in the study of this area. The results of this analysis provide a common framework for understanding these seemingly disparate branches of inquiry, which we hope will motivate future work in the field

Using the VAST Challenge in Undergraduate CS Research

The Visual Analytics Science and Technology (VAST) Challenge is a yearly competition designed to push forward visual analytics research through synthetic, yet realistic analytic tasks. In this paper, we discuss the challenges and the successes we have experienced incorporating the VAST Challenge and associated datasets into undergraduate research programs at two liberal arts colleges. We advocate for increased undergraduate participation in this and similar competitions, arguing they afford unique opportunities for positive development in early researchers

Scalable Syriac Paleography using Interactive Visualization

Syriac (a dialect of Aramaic) was the primary language spoken in the late ancient Middle East between the second and eighth centuries AD, and continues to be a language of Christian scholarship and liturgy up to the present day. There are approximately 20,000 known surviving Syriac manuscripts. Among early manuscripts, only around 10% include a scribal note that provides information regarding when, where, and by whom a given manuscript was written. For the remaining 90%, close examination of subtle differences in the handwritten script remains the primary tool for determining provenance. Prior to this study, scholars classified early Syriac manuscripts into two divergent script styles: Estrangela and Serto. In this paper, we present a case study of historians’ analysis of this collection of manuscripts supported by visual analytic tools. This approach uncovered major inaccuracies in this dichotomous model, resulting in profound disruption to the dominant understanding of the development of these texts

A Survey of Visual Analytics Tools for Effective Decision-Making

Over the past decade, the visualization for cybersecurity (VizSec) research community has adapted many information visualization techniques to support the critical work of cyber analysts. While these efforts have yielded many specialized tools and platforms, the community lacks a unified approach to the design and implementation of these systems. In this work, we provide a retrospective analysis of the past decade of VizSec publications, with an eye toward developing a more cohesive understanding of the emerging patterns of design: • We identify common thematic groupings among existing work, as well as interesting patterns of design around the utilization of various visual encodings. • We also discuss existing gaps in the adaptation of visualization techniques for cybersecurity applications, and recommend avenues for future exploration

Balancing Human and Machine Contributions in Human Computation Systems

Many interesting and successful human computation systems leverage the complementary computational strengths of both humans and machines to solve these problems. In this chapter, we examine Human Computation as a type of Human-Computer Collaboration—collaboration involving at least one human and at least one computational agent. We discuss recent advances in the open area of function allocation, and explore how to balance the contributions of humans and machines in computational systems. We then explore how human-computer collaborative strategies can be used to solve problems that are difficult or computationally infeasible for computers or humans alone

Survey on Individual Differences in Visualization

Developments in data visualization research have enabled visualization systems to achieve great general usability and application across a variety of domains. These advancements have improved not only people's understanding of data, but also the general understanding of people themselves, and how they interact with visualization systems. In particular, researchers have gradually come to recognize the deficiency of having one-size-fits-all visualization interfaces, as well as the significance of individual differences in the use of data visualization systems. Unfortunately, the absence of comprehensive surveys of the existing literature impedes the development of this research. In this paper, we review the research perspectives, as well as the personality traits and cognitive abilities, visualizations, tasks, and measures investigated in the existing literature. We aim to provide a detailed summary of existing scholarship, produce evidence-based reviews, and spur future inquiry

Retrospective on a Decade of Research in Visualization for Cybersecurity

Over the past decade, the visualization for cybersecurity (VizSec) research community has adapted many information visualization techniques to support the critical work of cyber analysts. While these efforts have yielded many specialized tools and platforms, the community lacks a unified approach to the design and implementation of these systems. In this work, we provide a retrospective analysis of the past decade of VizSec publications, with an eye toward developing a more cohesive understanding of the emerging patterns of design at work in our community. We identify common thematic groupings among existing work, as well as several interesting pat- terns of design around the utilization of various visual encodings. We also discuss existing gaps in the adaptation of information visualization techniques to cybersecurity applications, and recommend avenues for future exploration

Exploring Agent-Based Simulations in Political Science Using Aggregate Temporal Graphs

Agent-based simulation has become a key technique for modeling and simulating dynamic, complicated behaviors in social and behavioral sciences. Lacking the appropriate tools and support, it is difficult for social scientists to thoroughly analyze the results of these simulations. In this work, we capture the complex relationships between discrete simulation states by visualizing the data as a temporal graph. In collaboration with expert analysts, we identify two graph structures which capture important relationships between pivotal states in the simulation and their inevitable outcomes. Finally, we demonstrate the utility of these structures in the interactive analysis of a large-scale social science simulation of political power in present-day Thailand