A critical aspect of formal help-giving tasks in the enterprise is finding the right expert. We built and evaluated a tool, Find an Expert, to examine what the most important expert selection criteria are for help-seekers and how to represent them in expert selection interfaces for formal help-giving tasks. We observed users' expert selection decisions and found that the diversity of topic expertise and the amount of related experience were significantly important in helping users decide which expert to contact. Through self-reported data from users, we found that in addition to expertise and experience, expert accessibility indicators, like online availability and language proficiency, were considered important criteria for selecting experts. Finally, publicly-displayed crowdsourced ratings of experts, while deemed useful indicators of expert quality by help-seekers, raised concerns for experts. We conclude with suggestions regarding the design of expert selection interfaces for formal help-giving tasks.

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.

Sensemaking is an important aspect of information-seeking tasks but has mostly been studied at the individual level. We conducted a study of sensemaking in collaborative Web search using SearchTogether and found that collaborators face several challenges in making sense of information during collaborative search tasks. We built and evaluated a new tool, CoSense, which enhanced sensemaking in SearchTogether. The evaluation of CoSense provided insights into how collaborative sensemaking differed from individual sensemaking in terms of the different kinds of information that collaborators needed to make sense of. In this article we discuss findings about how sensemaking occurs in synchronous and asynchronous collaboration and the challenges participants face in handling handoffs. We found that participants had two different strategies of handling handoffs—search-lead and sensemaking-lead—and that participants with these two strategies exhibited different procedural knowledge of sensemaking. We also discuss how complex and varied the products of sensemaking are during a collaborative search task. Through our evaluation of CoSense we provide insights into the design of tools that can enhance sensemaking in collaborative search tasks.

An important aspect of collaborative information seeking (CIS) is making sense of the information found, i.e., collaborative sensemaking. We conducted an ethnographic study of the CIS practices of healthcare providers in a hospital emergency department to gain a conceptual understanding of when and how collaborative sensemaking occurs during CIS activities. We present occasions and characteristics of collaborative sensemaking and design implications for collaborative information retrieval tools to support sensemaking.

Making sense of the information found during an investigational Web search task can be daunting. With the recent emergence of tools to support collaborative Web search, the associated sensemaking task has become even more complex, requiring sense to be made not only of the products of a search (i.e., results found) but of the process, as well (i.e., group division of labor and decision-making).