The Information Visualization community has begun to pay attention to visualization literacy; however, researchers still lack instruments for measuring the visualization literacy of users. In order to address this gap, we systematically developed a visualization literacy assessment test (VLAT), especially for non-expert users in data visualization, by following the established procedure of test development in Psychological and Educational Measurement: (1) Test Blueprint Construction, (2) Test Item Generation, (3) Content Validity Evaluation, (4) Test Tryout and Item Analysis, (5) Test Item Selection, and (6) Reliability Evaluation. The VLAT consists of 12 data visualizations and 53 multiple-choice test items that cover eight data visualization tasks. The test items in the VLAT were evaluated with respect to their essentialness by five domain experts in Information Visualization and Visual Analytics (average content validity ratio = 0.66). The VLAT was also tried out on a sample of 191 test takers and showed high reliability (reliability coefficient omega = 0.76). In addition, we demonstrated the relationship between users' visualization literacy and aptitude for learning an unfamiliar visualization and showed that they had a fairly high positive relationship (correlation coefficient = 0.64). Finally, we discuss evidence for the validity of the VLAT and potential research areas that are related to the instrument.

Through online health communities (OHCs), patients and caregivers exchange their illness experiences and strategies for overcoming the illness, and provide emotional support. To facilitate healthy and lively conversations in these communities, their members should be continuously monitored and nurtured by OHC administrators. The main challenge of OHC administrators' tasks lies in understanding the diverse dimensions of conversation threads that lead to productive discussions in their communities. In this paper, we present a design study in which three domain expert groups participated, an OHC researcher and two OHC administrators of online health communities, which was conducted to find with a visual analytic solution. Through our design study, we characterized the domain goals of OHC administrators and derived tasks to achieve these goals. As a result of this study, we propose a system called VisOHC, which visualizes individual OHC conversation threads as collapsed boxes-a visual metaphor of conversation threads. In addition, we augmented the posters' reply authorship network with marks and/or beams to show conversation dynamics within threads. We also developed unique measures tailored to the characteristics of OHCs, which can be encoded for thread visualizations at the users' requests. Our observation of the two administrators while using VisOHC showed that it supports their tasks and reveals interesting insights into online health communities. Finally, we share our methodological lessons on probing visual designs together with domain experts by allowing them to freely encode measurements into visual variables.

In this paper, we would like to investigate how people make sense of unfamiliar information visualizations. In order to achieve the research goal, we conducted a qualitative study by observing 13 participants when they endeavored to make sense of three unfamiliar visualizations (i.e., a parallel-coordinates plot, a chord diagram, and a treemap) that they encountered for the first time. We collected data including audio/video record of think-aloud sessions and semi-structured interview; and analyzed the data using the grounded theory method. The primary result of this study is a grounded model of NOvice's information Vlsualization Sensemaking (NOVIS model), which consists of the five major cognitive activities: 1 encountering visualization, 2 constructing a frame, 3 exploring visualization, 4 questioning the frame, and 5 floundering on visualization. We introduce the NOVIS model by explaining the five activities with representative quotes from our participants. We also explore the dynamics in the model. Lastly, we compare with other existing models and share further research directions that arose from our observations.

Online consumer reviews have become a substantial component of e-commerce and provide online shoppers with abundant information about products. However, previous studies provided mixed results about whether consumers experience information overload from such a vast volume of reviews. Thus, this study investigates how users perceive products depending on various numbers of reviews (from 0 to 3,000 reviews) and different review valences (generally positive, generally negative, and divided). Two crowdsourced studies with 1,783 participants were conducted. The study found no clear evidence to suggest that information overload increases as the number of reviews increases. Instead, the participants relied on a very limited number of reviews in making purchase decisions. In addition, it was observed that the review valence affected how the participants used different information sources from the interface. Based on the results, this article provides a set of interesting implications and design guidelines.

This study investigated the impacts of three sorting techniques on various cognitive tasks performed on a tabular representation. The tasks under study were a multiattribute object selection task and selected low-level analytic tasks. Three sorting techniques, including sorting by a column (Typical Sort), sorting by all columns simultaneously (SimulSort), and sorting by all columns with faithful vertical locations (ParallelTable), were compared with a static table without the sorting feature (Baseline). An incentivized controlled laboratory study with 80 participants and a preliminary eye-tracker study were conducted to better understand the strengths and weaknesses of the four different approaches. SimulSort and ParallelTable were found to significantly improve the performance of multiattribute object selection. ParallelTable, however, suffers from an occlusion problem, so it is not an appropriate support for some low-level analytic tasks. The findings were used to propose appropriate sorting techniques for specific tasks performed on a table.

For information visualization researchers, eye tracking has been a useful tool to investigate research participants' underlying cognitive processes by tracking their eye movements while they interact with visual techniques. We used an eye tracker to better understand why participants with a variant of a tabular visualization called `SimulSort' outperformed ones with a conventional table and typical one-column sorting feature (i.e., Typical Sorting). The collected eye-tracking data certainly shed light on the detailed cognitive processes of the participants; SimulSort helped with decision-making tasks by promoting efficient browsing behavior and compensatory decision-making strategies. However, more interestingly, we also found unexpected eye-tracking patterns with SimulSort. We investigated the cause of the unexpected patterns through a crowdsourcing-based study (i.e., Experiment 2), which elicited an important limitation of the eye tracking method: incapability of capturing peripheral vision. This particular result would be a caveat for other visualization researchers who plan to use an eye tracker in their studies. In addition, the method to use a testing stimulus (i.e., influential column) in Experiment 2 to verify the existence of such limitations would be useful for researchers who would like to verify their eye tracking results.

We present a concurrency control scheme using dynamic versioning for index-based data access in main memory database systems. This scheme enables read-only transactions read correct version without holding any locks or latches, while update transactions only obtain a few locks or latches without deadlocks. Efficient version management is designed to support high concurrency level and low space overhead. The interaction between dynamic versioning and indexing is considered so that all available versions can be accessed through indexing. Experiment results show that dynamic versioning can improve the performance in concurrent environment significantly.