DevLan/vispubs huggingface dataset:
Can Eye Help You?: Effects of Visualizing Eye Fixations on Remote Collaboration Scenarios for Physical Tasks
Authors: Keita Higuchi, Ryo Yonetani, Yoichi Sato
Published at CHI, 2016

In this work, we investigate how remote collaboration between a local worker and a remote collaborator will change if eye fixations of the collaborator are presented to the worker. We track the collaborator's points of gaze on a monitor screen displaying a physical workspace and visualize them onto the space by a projector or through an optical see-through head-mounted display. Through a series of user studies, we have found the followings: 1) Eye fixations can serve as a fast and precise pointer to objects of the collaborator's interest. 2) Eyes and other modalities, such as hand gestures and speech, are used differently for object identification and manipulation. 3) Eyes are used for explicit instructions only when they are combined with speech. 4) The worker can predict some intentions of the collaborator such as his/her current interest and next instruction.
Chronicler: Interactive Exploration of Source Code History
Authors: Moritz Wittenhagen, Christian Cherek, Jan O. Borchers
Published at CHI, 2016

Exploring source code history is an important task for software maintenance. Traditionally, source code history is navigated on the granularity of individual files. This is not fine-grained enough to support users in exploring the evolution of individual code elements. We suggest to consider the history of individual elements within the tree structure inherent to source code. A history graph created from these trees then enables new ways to explore events of interest defined by structural changes in the source code. We present Tree Flow, a visualization of these structural changes designed to enable users to choose the appropriate level of detail for the task at hand. In a user study, we show that both Chronicler and the history aware timeline, two prototype systems combining history graph navigation with a traditional source code view, outperform the more traditional history navigation on a file basis and users strongly prefer Chronicler for the exploration of source code.
ChronoFab: Fabricating Motion
Authors: Rubaiat Habib Kazi, Tovi Grossman, Cory Mogk, Ryan M. Schmidt, George W. Fitzmaurice
Published at CHI, 2016

We present ChronoFab, a 3D modeling tool to craft motion sculptures, tangible representations of 3D animated models, visualizing an object's motion with static, transient, ephemeral visuals that are left behind. Our tool casts 3D modeling as a dynamic art-form by employing 3D animation and dynamic simulation for the modeling of motion sculptures. Our work is inspired by the rich history of stylized motion depiction techniques in existing 3D motion sculptures and 2D comic art. Based on a survey of such techniques, we present an interface that enables users to rapidly explore and craft a variety of static 3D motion depiction techniques, including motion lines, multiple stroboscopic stamps, sweeps and particle systems, using a 3D animated object as input. In a set of professional and non-professional usage sessions, ChronoFab was found to be a superior tool for the authoring of motion sculptures, compared to traditional 3D modeling workflows, reducing task completion times by 79%.
Egocentric Analysis of Dynamic Networks with EgoLines
Authors: Jian Zhao 0010, Michael Glueck, Fanny Chevalier, Yanhong Wu, Azam Khan
Published at CHI, 2016

The egocentric analysis of dynamic networks focuses on discovering the temporal patterns of a subnetwork around a specific central actor (i.e., an ego-network). These types of analyses are useful in many application domains, such as social science and business intelligence, providing insights about how the central actor interacts with the outside world. We present EgoLines, an interactive visualization to support the egocentric analysis of dynamic networks. Using a "subway map" metaphor, a user can trace an individual actor over the evolution of the ego-network. The design of EgoLines is grounded in a set of key analytical questions pertinent to egocentric analysis, derived from our interviews with three domain experts and general network analysis tasks. We demonstrate the effectiveness of EgoLines in egocentric analysis tasks through a controlled experiment with 18 participants and a use-case developed with a domain expert.
Enhancing Cross-Device Interaction Scripting with Interactive Illustrations
Authors: Pei-Yu (Peggy) Chi, Yang Li 0058, Björn Hartmann
Published at CHI, 2016

Cross-device interactions involve input and output on multiple computing devices. Implementing and reasoning about interactions that cover multiple devices with a diversity of form factors and capabilities can be complex. To assist developers in programming cross-device interactions, we created DemoScript, a technique that automatically analyzes a cross-device interaction program while it is being written. DemoScript visually illustrates the step-by-step execution of a selected portion or the entire program with a novel, automatically generated cross-device storyboard visualization. In addition to helping developers understand the behavior of the program, DemoScript also allows developers to revise their program by interactively manipulating the cross-device storyboard. We evaluated DemoScript with 8 professional programmers and found that DemoScript significantly improved development efficiency by helping developers interpret and manage cross-device interaction; it also encourages testing to think through the script in a development process.
Evaluating Information Visualization via the Interplay of Heuristic Evaluation and Question-Based Scoring
Authors: Marti A. Hearst, Paul Laskowski, Luis Silva
Published at CHI, 2016

In an instructional setting it can be difficult to accurately assess the quality of information visualizations of several variables. Instead of a standard design critique, an alternative is to ask potential readers of the chart to answer questions about it. A controlled study with 47 participants shows a good correlation between aggregated novice heuristic evaluation scores and results of answering questions about the data, suggesting that the two forms of assessment can be complementary. Using both metrics in parallel can yield further benefits; discrepancies between them may reveal incorrect application of heuristics or other issues.
Evaluating the Paper-to-Screen Translation of Participant-Aided Sociograms with High-Risk Participants
Authors: Bernie Hogan, Joshua R. Melville, Gregory Lee Phillips II, Patrick Janulis, Noshir Contractor, Brian S. Mustanski, Michelle Birkett
Published at CHI, 2016

While much social network data exists online, key network metrics for high-risk populations must still be captured through self-report. This practice has suffered from numerous limitations in workflow and response burden. However, advances in technology, network drawing libraries and databases are making interactive network drawing increasingly feasible. We describe the translation of an analog-based technique for capturing personal networks into a digital framework termed netCanvas that addresses many existing shortcomings such as: 1) complex data entry; 2) extensive interviewer intervention and field setup; 3) difficulties in data reuse; and 4) a lack of dynamic visualizations. We test this implementation within a health behavior study of a high-risk and difficult-to-reach population. We provide a within--subjects comparison between paper and touchscreens. We assert that touchscreen-based social network capture is now a viable alternative for highly sensitive data and social network data entry tasks.
Fast, Cheap, and Good: Why Animated GIFs Engage Us
Authors: Saeideh Bakhshi, David A. Shamma, Lyndon Kennedy, Yale Song, Paloma de Juan, Joseph Jofish Kaye
Published at CHI, 2016

Animated GIFs have been around since 1987 and recently gained more popularity on social networking sites. Tumblr, a large social networking and micro blogging platform, is a popular venue to share animated GIFs. Tumblr users follow blogs, generating a feed or posts, and choose to "like' or to "reblog' favored posts. In this paper, we use these actions as signals to analyze the engagement of over 3.9 million posts, and conclude that animated GIFs are significantly more engaging than other kinds of media. We follow this finding with deeper visual analysis of nearly 100k animated GIFs and pair our results with interviews with 13 Tumblr users to find out what makes animated GIFs engaging. We found that the animation, lack of sound, immediacy of consumption, low bandwidth and minimal time demands, the storytelling capabilities and utility for expressing emotions were significant factors in making GIFs the most engaging content on Tumblr. We also found that engaging GIFs contained faces and had higher motion energy, uniformity, resolution and frame rate. Our findings connect to media theories and have implications in design of effective content dashboards, video summarization tools and ranking algorithms to enhance engagement.
Gaze Augmentation in Egocentric Video Improves Awareness of Intention
Authors: Deepak Akkil, Poika Isokoski
Published at CHI, 2016

Video communication using head-mounted cameras could be useful to mediate shared activities and support collaboration. Growing popularity of wearable gaze trackers presents an opportunity to add gaze information on the egocentric video. We hypothesized three potential benefits of gaze-augmented egocentric video to support collaborative scenarios: support deictic referencing, enable grounding in communication, and enable better awareness of the collaborator's intentions. Previous research on using egocentric videos for real-world collaborative tasks has failed to show clear benefits of gaze point visualization. We designed a study, deconstructing a collaborative car navigation scenario, to specifically target the value of gaze-augmented video for intention prediction. Our results show that viewers of gaze-augmented video could predict the direction taken by a driver at a four-way intersection more accurately and more confidently than a viewer of the same video without the superimposed gaze point. Our study demonstrates that gaze augmentation can be useful and encourages further study in real-world collaborative scenarios.
Glowworms and Fireflies: Ambient Light on Large Interactive Surfaces
Authors: Florian Perteneder, Eva-Maria Beatrix Grossauer, Joanne Leong, Wolfgang Stuerzlinger, Michael Haller
Published at CHI, 2016

Ambient light is starting to be commercially used to enhance the viewing experience for watching TV. We believe that ambient light can add value in meeting and control rooms that use large vertical interactive surfaces. Therefore, we equipped a large interactive whiteboard with a peripheral ambient light display and explored its utility for different scenarios by conducting two controlled experiments. In the first experiment, we investigated how ambient light can be used for peripheral notifications, and how perception is influenced by the user's position and the type of work they are engaged in. The second experiment investigated the utility of ambient light for off-screen visualization. We condense our findings into several design recommendations that we then applied to application scenarios to show the versatility and usefulness of ambient light for large surfaces.
HapTurk: Crowdsourcing Affective Ratings of Vibrotactile Icons
Authors: Oliver S. Schneider, Hasti Seifi, Salma Kashani, Matthew Chun, Karon E. MacLean
Published at CHI, 2016

Vibrotactile (VT) display is becoming a standard component of informative user experience, where notifications and feedback must convey information eyes-free. However, effective design is hindered by incomplete understanding of relevant perceptual qualities, together with the need for user feedback to be accessed in-situ. To access evaluation streamlining now common in visual design, we introduce proxy modalities as a way to crowdsource VT sensations by reliably communicating high-level features through a crowd-accessible channel. We investigate two proxy modalities to represent a high-fidelity tactor: a new VT visualization, and low-fidelity vibratory translations playable on commodity smartphones. We translated 10 high-fidelity vibrations into both modalities, and in two user studies found that both proxy modalities can communicate affective features, and are consistent when deployed remotely over Mechanical Turk. We analyze fit of features to modalities, and suggest future improvements.
I Know Where You Live: Inferring Details of People's Lives by Visualizing Publicly Shared Location Data
Authors: Ilaria Liccardi, Alfie Abdul-Rahman, Min Chen 0001
Published at CHI, 2016

This research measures human performance in inferring the functional types (i.e., home, work, leisure and transport) of locations in geo-location data using different visual representations of the data (textual, static and animated visualizations) along with different amounts of data (1, 3 or 5 day(s)). We first collected real life geo-location data from tweets. We then asked the data owners to tag their location points, resulting in ground truth data. Using this dataset we conducted an empirical study involving 45 participants to analyze how accurately they could infer the functional location of the original data owners under different conditions, i.e., three data representations, three data densities and four location types. The study results indicate that while visual techniques perform better than textual ones, the functional locations of human activities can be inferred with a relatively high accuracy even using only textual representations and a low density of location points. Workplace was more easily inferred than home while transport was the functional location with the highest accuracy. Our results also showed that it was easier to infer functional locations from data exhibiting more stable and consistent mobility patterns, which are thus more vulnerable to privacy disclosures. We discuss the implications of our findings in the context of privacy preservation and provide guidelines to users and companies to help preserve and safeguard people's privacy.
Infrastructure in the Wild: What Mapping in Post-Earthquake Nepal Reveals about Infrastructural Emergence
Authors: Robert Soden, Leysia Palen
Published at CHI, 2016

Disasters and their impacts have unavoidable spatial characteristics. As such, maps are necessary and omnipresent features of the information landscapes that surround and support disaster response. Professional and volunteer GIS services are increasingly in demand to support map-based information visualization during crises. This paper investigates the work of mapmakers working on the response to the 2015 Nepal earthquakes. In comparison to prior events, we found significantly more collaboration and spatial data sharing took place between map producers working across humanitarian organizations and parts of the Nepal government. Collaboration between mapping practitioners was supported by a complex and emergent information infrastructure composed of social and technical elements, some of which were brought through experience with prior disaster events, and some which were shaped anew by the availability and acceptance of open data sources. Our research investigates these elements of the spatial information infrastructure in post-earthquake Nepal to consider infrastructural emergence.
Integrating the Smart Home into the Digital Calendar
Authors: Sarah Mennicken, David Kim, Elaine May Huang
Published at CHI, 2016

With the growing adoption of smart home technologies, inhabitants are faced with the challenge of making sense of the data that their homes can collect to configure automated behaviors that benefit their routines. Current commercial smart home interfaces usually provide information on individual devices instead of a more comprehensive overview of a home's behavior. To reduce the complexity of smart home data and integrate it better into inhabitants' lives, we turned to the familiar metaphor of a calendar and developed our smart home interface Casalendar. In order to investigate the concept and evaluate our goals to facilitate the understanding of smart home data, we created a prototype that we installed in two commercial smart homes for a month. The results we present in this paper are based on our analysis of user data from questionnaires, semi-structured interviews, participant-driven audio and screenshot feedback as well as logged interactions with our system. Our findings exposed advantages and disadvantages of this metaphor, emerging usage patterns, privacy concerns and challenges for information visualization. We further report on implications for design and open challenges we revealed through this work.
Interacting with Predictions: Visual Inspection of Black-box Machine Learning Models
Authors: Josua Krause, Adam Perer, Kenney Ng
Published at CHI, 2016

Understanding predictive models, in terms of interpreting and identifying actionable insights, is a challenging task. Often the importance of a feature in a model is only a rough estimate condensed into one number. However, our research goes beyond these naïve estimates through the design and implementation of an interactive visual analytics system, Prospector. By providing interactive partial dependence diagnostics, data scientists can understand how features affect the prediction overall. In addition, our support for localized inspection allows data scientists to understand how and why specific datapoints are predicted as they are, as well as support for tweaking feature values and seeing how the prediction responds. Our system is then evaluated using a case study involving a team of data scientists improving predictive models for detecting the onset of diabetes from electronic medical records.
Investigating Effects of Post-Selection Feedback for Acquiring Ultra-Small Targets on Touchscreen
Authors: Chun Yu, Hongyi Wen, Wei Xiong, Xiaojun Bi 0001, Yuanchun Shi
Published at CHI, 2016

In this paper, we investigate the effects of post-selection feedback for acquiring ultra-small (2-4mm) targets on touchscreens. Post-selection feedback shows the contact point on touchscreen after a user lifts his/her fingers to increase users' awareness of touching. Three experiments are conducted progressively using a single crosshair target, two reciprocally acquired targets and 2D random targets. Results show that in average post-selection feedback can reduce touch error rates by 78.4%, with a compromise of target acquisition time no more than 10%. In addition, we investigate participants' adjustment behavior based on correlation between successive trials. We conclude that the benefit of post-selection feedback is the outcome of both improved understanding about finger/point mapping and the dynamic adjustment of finger movement enabled by the visualization of the touch point.
Investigating Time Series Visualisations to Improve the User Experience
Authors: Muhammad Adnan 0001, Mike Just, Lynne Baillie
Published at CHI, 2016

Research on graphical perception of time series visualisations has focused on visual representation, and not on interaction. Even for visual representation, there has been limited study of the impact on users of visual encodings and the strengths and weaknesses of Cartesian and Polar coordinate systems. In order to address this research gap, we performed a comprehensive graphical perception study that measured the effectiveness of time series visualisations with different interactions, visual encodings and coordinate systems for several tasks. Our results show that, while positional and colour visual encodings were better for most tasks, area visual encoding performed better for data comparison. Most importantly, we identified that introducing interactivity within time series visualisations considerably enhances the user experience, without any loss of efficiency or accuracy. We believe that our findings can greatly improve the development of visual analytics tools using time series visualisations in a variety of domains.
iVoLVER: Interactive Visual Language for Visualization Extraction and Reconstruction
Authors: Gonzalo Gabriel Méndez, Miguel A. Nacenta, Sebastien Vandenheste
Published at CHI, 2016

We present the design and implementation of iVoLVER, a tool that allows users to create visualizations without textual programming. iVoLVER is designed to enable flexible acquisition of many types of data (text, colors, shapes, quantities, dates) from multiple source types (bitmap charts, webpages, photographs, SVGs, CSV files) and, within the same canvas, supports transformation of that data through simple widgets to construct interactive animated visuals. Aside from the tool, which is web-based and designed for pen and touch, we contribute the design of the interactive visual language and widgets for extraction, transformation, and representation of data. We demonstrate the flexibility and expressive power of the tool through a set of scenarios, and discuss some of the challenges encountered and how the tool fits within the current infovis tool landscape.
Look Before You Leap: Improving the Users' Ability to Detect Fraud in Electronic Marketplaces
Authors: Johannes Sänger, Norman Hänsch, Brian Glass, Zinaida Benenson, Robert Landwirth, M. Angela Sasse
Published at CHI, 2016

Reputation systems in current electronic marketplaces can easily be manipulated by malicious sellers in order to appear more reputable than appropriate. We conducted a controlled experiment with 40 UK and 41 German participants on their ability to detect malicious behavior by means of an eBay-like feedback profile versus a novel interface involving an interactive visualization of reputation data. The results show that participants using the new interface could better detect and understand malicious behavior in three out of four attacks (the overall detection accuracy 77% in the new vs. 56% in the old interface). Moreover, with the new interface, only 7% of the users decided to buy from the malicious seller (the options being to buy from one of the available sellers or to abstain from buying), as opposed to 30% in the old interface condition.
Making Sense of Temporal Queries with Interactive Visualization
Authors: Leilani Battle, Danyel Fisher, Robert DeLine, Mike Barnett 0001, Badrish Chandramouli, Jonathan Goldstein
Published at CHI, 2016

As real-time monitoring and analysis become increasingly important, researchers and developers turn to data stream management systems (DSMS's) for fast, efficient ways to pose temporal queries over their datasets. However, these systems are inherently complex, and even database experts find it difficult to understand the behavior of DSMS queries. To help analysts better understand these temporal queries, we developed StreamTrace, an interactive visualization tool that breaks down how a temporal query processes a given dataset, step-by-step. The design of StreamTrace is based on input from expert DSMS users; we evaluated the system with a lab study of programmers who were new to streaming queries. Results from the study demonstrate that StreamTrace can help users to verify that queries behave as expected and to isolate the regions of a query that may be causing unexpected results.