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The ability to regulate our emotions plays an important role in our psychological and physical health. Regulating emotions influences how and when emotions are expressed. We performed a large scale, longitudinal observational study to investigate the effect of emotion regulation ability on expressed affect. We found that expression of negative affect increased throughout the day. For people who suppress emotion this increase is slower that for those who do not. For those with stronger cognitive reappraisal abilities, though not significant, there was a trend for higher positive affect and negative affect increased significantly less steeply, suggesting that they might experience more positive and less negative affect. These results reflect some of the first results based on large scale, continuous tracking of behavioral expression of emotion longitudinally. Our results demonstrate the need to carefully consider the time of day and emotion regulation ability, in addition to gender and age, when attempting to automatically infer affective states for facial behavior. [ABSTRACT FROM AUTHOR]

The dominant paradigm for searching and browsing large data stores is text-based: presenting a scrollable list of search results in response to textual search term input. While this works well for the Web, there is opportunity for improvement in the domain of personal information stores, which tend to have more heterogeneous data and richer metadata. In this paper, we introduce FacetMap, an interactive, query-driven visualization, generalizable to a wide range of metadata-rich data stores. FacetMap uses a visual metaphor for both input (selection of metadata facets as filters) and output. Results of a user study provide insight into tradeoffs between FacetMap's graphical approach and the traditional text-oriented approach. [ABSTRACT FROM AUTHOR]

This special issue turns the spotlight on business intelligence (BI) as an area of inquiry and explores beyond the current standard practices. The articles in the issue describe the processes that practitioners currently follow in this area and how new BI techniques and capabilities will help users understand and act on widely disparate types of data. The articles also report on how organizations make decisions around datasets, what purposes visualizations are used for, and what different representations people use to show and explore data. [ABSTRACT FROM PUBLISHER]

Co-located collaboration can be extremely valuable during complex visual analytics tasks. We present an exploratory study of a system designed to support collaborative visual analysis tasks on a digital tabletop display. Fifteen participant pairs employed Cambiera, a visual analytics system, to solve a problem involving 240 digital documents. Our analysis, supported by observations, system logs, questionnaires, and interview data, explores how pairs approached the problem around the table. We contribute a unique, rich understanding of how users worked together around the table and identify eight types of collaboration styles that can be used to identify how closely people work together while problem solving. We show how the closeness of teams' collaboration and communication influenced how they performed on the task overall. We further discuss the role of the tabletop for visual analytics tasks and derive design implications for future co-located collaborative tabletop problem solving systems. [ABSTRACT FROM AUTHOR]

Computing and visualizing sets of elements and their relationships is one of the most common tasks one performs when analyzing and organizing large amounts of data. Common representations of sets such as convex or concave geometries can become cluttered and difficult to parse when these sets overlap in multiple or complex ways, e.g., when multiple elements belong to multiple sets. In this paper, we present a design study of a novel set visual representation, LineSets, consisting of a curve connecting all of the set's elements. Our approach to design the visualization differs from traditional methodology used by the InfoVis community. We first explored the potential of the visualization concept by running a controlled experiment comparing our design sketches to results from the state-of-the-art technique. Our results demonstrated that LineSets are advantageous for certain tasks when compared to concave shapes. We discuss an implementation of LineSets based on simple heuristics and present a study demonstrating that our generated curves do as well as human-drawn ones. Finally, we present two applications of our technique in the context of search tasks on a map and community analysis tasks in social networks. [ABSTRACT FROM AUTHOR]