DevLan/vispubs huggingface dataset:
DataToon: Drawing Dynamic Network Comics With Pen + Touch Interaction
Authors: Nam Wook Kim, Nathalie Henry Riche, Benjamin Bach, Guanpeng Xu, Matthew Brehmer, Ken Hinckley, Michel Pahud, Haijun Xia, Michael J. McGuffin, Hanspeter Pfister
Published at CHI, 2019

Comics are an entertaining and familiar medium for presenting compelling stories about data. However, existing visualization authoring tools do not leverage this expressive medium. In this paper, we seek to incorporate elements of comics into the construction of data-driven stories about dynamic networks. We contribute DataToon, a flexible data comic storyboarding tool that blends analysis and presentation with pen and touch interactions. A storyteller can use DataToon rapidly generate visualization panels, annotate them, and position them within a canvas to produce a visually compelling narrative. In a user study, participants quickly learned to use DataToon for producing data comics.
Effect of Orientation on Unistroke Touch Gestures
Authors: Sven Mayer, Valentin Schwind, Huy Viet Le, Dominik Weber, Jonas Vogelsang, Johannes Wolf, Niels Henze
Published at CHI, 2019

As touchscreens are the most successful input method of current mobile devices, touch gestures became a widely used input technique. While gestures provide users with advantages to express themselves, they also introduce challenges regarding accuracy and memorability. In this paper, we investigate the effect of a gesture's orientation on how well the gesture can be performed. We conducted a study in which participants performed systematically rotated unistroke gestures. For straight lines as well as for compound lines, we found that users tend to align gestures with the primary axes. We show that the error can be described by a Clausen function with R² = .93. Based on our findings, we suggest design implications and highlight the potential for recognizing flick gestures, visualizing gestures and improving recognition of compound gestures.
Embodied Imagination: An Approach to Stroke Recovery Combining Participatory Performance and Interactive Technology
Authors: Rosella P. Galindo Esparza, Patrick G. T. Healey, Lois Weaver, Matthew Delbridge
Published at CHI, 2019

Participatory performance provides methods for exploring social identities and situations in ways that can help people to imagine new ways of being. Digital technologies provide tools that can help people envision these possibilities. We explore this combination through a performance workshop process designed to help stroke survivors imagine new physical and social possibilities by enacting fantasies of "things they always wanted to do". This process uses performance methods combined with specially designed real-time movement visualisations to progressively build fantasy narratives that are enacted with and for other workshop participants. Qualitative evaluations suggest this process successfully stimulates participant's embodied imagination and generates a diverse range of fantasies. The interactive and communal aspects of the workshop process appear to be especially important in achieving these effects. This work highlights how the combination of performance methods and interactive tools can bring a rich, prospective and political understanding of people's lived experience to design.
Ethical Dimensions of Visualization Research
Authors: Michael Correll
Published at CHI, 2019

Visualizations have a potentially enormous influence on how data are used to make decisions across all areas of human endeavor. However, it is not clear how this power connects to ethical duties: what obligations do we have when it comes to visualizations and visual analytics systems, beyond our duties as scientists and engineers? Drawing on historical and contemporary examples, I address the moral components of the design and use of visualizations, identify some ongoing areas of visualization research with ethical dilemmas, and propose a set of additional moral obligations that we have as designers, builders, and researchers of visualizations.
Evaluating the Impact of Pseudo-Colour and Coordinate System on the Detection of Medication-induced ECG Changes
Authors: Alaa Alahmadi, Alan Davies, Jennifer Royle, Markel Vigo, Caroline Jay
Published at CHI, 2019

The electrocardiogram (ECG), a graphical representation of the heart's electrical activity, is used for detecting cardiac pathologies. Certain medications can produce a complication known as 'long QT syndrome', shown on the ECG as an increased gap between two parts of the waveform. Self-monitoring for this could be lifesaving, as the syndrome can result in sudden death, but detecting it on the ECG is difficult. Here we evaluate whether using pseudo-colour to highlight wave length and changing the coordinate system can support lay people in identifying increases in the QT interval. The results show that introducing colour significantly improves accuracy, and that whilst it is easier to detect a difference without colour with Cartesian coordinates, the greatest accuracy is achieved when Polar coordinates are combined with colour. The results show that applying simple visualisation techniques has the potential to improve ECG interpretation accuracy, and support people in monitoring their own ECG.
Examining and Enhancing the Illusory Touch Perception in Virtual Reality Using Non-Invasive Brain Stimulation
Authors: Filip Skola, Fotis Liarokapis
Published at CHI, 2019

Virtual reality (VR) can be immersive to such a degree that users sometimes report feeling tactile sensations based on visualization of the touch, without any actual physical contact. This effect is not only interesting for studies of human perception, but can also be leveraged to improve the quality of VR by evoking tactile sensations without usage of specialized equipment. The aim of this paper is to study brain processing of the illusory touch and its enhancement for purposes of exploitation in VR scene design. To amplify the illusory touch, transcranial direct current stimulation (tDCS) was used. Participants attended two sessions with blinded stimulation and interacted with a virtual ball using tracked hands in VR. The effects were studied using electroencephalography (EEG), that allowed us to examine stimulation-induced changes in processing of the illusory touch in the brain, as well as to identify its neural correlates. Results confirm enhanced processing of the illusory touch after the stimulation, and some of these changes were correlated to subjective rating of its magnitude.
Exploring Sound Awareness in the Home for People who are Deaf or Hard of Hearing
Authors: Dhruv Jain, Angela Lin, Rose Guttman, Marcus Amalachandran, Aileen Zeng, Leah Findlater, Jon Froehlich
Published at CHI, 2019

The home is filled with a rich diversity of sounds from mundane beeps and whirs to dog barks and children's shouts. In this paper, we examine how deaf and hard of hearing (DHH) people think about and relate to sounds in the home, solicit feedback and reactions to initial domestic sound awareness systems, and explore potential concerns. We present findings from two qualitative studies: in Study 1, 12 DHH participants discussed their perceptions of and experiences with sound in the home and provided feedback on initial sound awareness mockups. Informed by Study 1, we designed three tablet-based sound awareness prototypes, which we evaluated with 10 DHH participants using a Wizard-of-Oz approach. Together, our findings suggest a general interest in smarthome-based sound awareness systems particularly for displaying contextually aware, personalized and glanceable visualizations but key concerns arose related to privacy, activity tracking, cognitive overload, and trust.
Eye-Write: Gaze Sharing for Collaborative Writing
Authors: Grete Helena Kütt, Kevin Lee, Ethan Hardacre, Alexandra Papoutsaki
Published at CHI, 2019

Online collaborative writing is an increasingly common practice. Despite its positive effect on productivity and quality of work, it poses challenges to co-authors in remote settings because of limitations in conversational grounding and activity awareness. This paper presents Eye-Write, a novel system which allows two co-authors to see at will the location of their partner's gaze within a text editor. To investigate the effect of shared gaze on collaboration, we conducted a study on synchronous remote collaborative writing in academic settings with 20 dyads. Gaze sharing improved five aspects of perceived collaboration quality: mutual understanding, level of joint attention, flow of communication, level of negotiation, and awareness of the co-author's activity. Furthermore, dyads whose participants deactivated the gaze visualization showed a smaller degree of collaboration. Our findings offer insights for future text editors by outlining the benefits of at-will gaze sharing in collaborative writing.
Falcon: Balancing Interactive Latency and Resolution Sensitivity for Scalable Linked Visualizations
Authors: Dominik Moritz, Bill Howe, Jeffrey Heer
Published at CHI, 2019

We contribute user-centered prefetching and indexing methods that provide low-latency interactions across linked visualizations, enabling cold-start exploration of billion-record datasets. We implement our methods in Falcon, a web-based system that makes principled trade-offs between latency and resolution to optimize brushing and view switching times. To optimize latency-sensitive brushing actions, Falcon reindexes data upon changes to the active view a user is brushing in. To limit view switching times, Falcon initially loads reduced interactive resolutions, then progressively improves them. Benchmarks show that Falcon sustains real-time interactivity of 50fps for pixel-level brushing and linking across multiple visualizations with no costly precomputation. We show constant brushing performance regardless of data size on datasets ranging from millions of records in the browser to billions when connected to a backing database system.
Frequency-Based Design of Smart Textiles
Authors: Jussi Mikkonen, Riikka Townsend
Published at CHI, 2019

Despite the increasing amount of smart textile design practitioners, the methods and tools commonly available have not progressed to the same scale. Most smart textile interaction designs today rely on detecting changes in resistance. The tools and sensors for this are generally limited to DC-voltage-divider based sensors and multimeters. Furthermore, the textiles and the materials used in smart textile design can exhibit behaviour making it difficult to identify even simple interactions using those means. For instance, steel-based textiles exhibit intrinsic semiconductive properties that are difficult to identify with current methods. In this paper, we show an alternative way to measure interaction with smart textiles. By relying on visualisation known as Lissajous-figures and frequency-based signals, we can detect even subtle and varied forms of interaction with smart textiles. We also show an approach to measuring frequency-based signals and present an Arduino-based system called Teksig to support this type of textile practice.
Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models
Authors: Fred Hohman, Andrew Head, Rich Caruana, Robert DeLine, Steven Mark Drucker
Published at CHI, 2019

Without good models and the right tools to interpret them, data scientists risk making decisions based on hidden biases, spurious correlations, and false generalizations. This has led to a rallying cry for model interpretability. Yet the concept of interpretability remains nebulous, such that researchers and tool designers lack actionable guidelines for how to incorporate interpretability into models and accompanying tools. Through an iterative design process with expert machine learning researchers and practitioners, we designed a visual analytics system, Gamut, to explore how interactive interfaces could better support model interpretation. Using Gamut as a probe, we investigated why and how professional data scientists interpret models, and how interface affordances can support data scientists in answering questions about model interpretability. Our investigation showed that interpretability is not a monolithic concept: data scientists have different reasons to interpret models and tailor explanations for specific audiences, often balancing competing concerns of simplicity and completeness. Participants also asked to use Gamut in their work, highlighting its potential to help data scientists understand their own data.
GymSoles: Improving Squats and Dead-Lifts by Visualizing the User's Center of Pressure
Authors: Don Samitha Elvitigala, Denys J. C. Matthies, Löic David, Chamod Weerasinghe, Suranga Nanayakkara
Published at CHI, 2019

The correct execution of exercises, such as squats and dead-lifts, is essential to prevent various bodily injuries. Existing solutions either rely on expensive motion tracking or multiple Inertial Measurement Units (IMU) systems require an extensive set-up and individual calibration. This paper introduces a proof of concept, GymSoles, an insole prototype that provides feedback on the Centre of Pressure (CoP) at the feet to assist users with maintaining the correct body posture, while performing squats and dead-lifts. GymSoles was evaluated with 13 users in three conditions: 1) no feedback, 2) vibrotactile feedback, and 3) visual feedback. It has shown that solely providing feedback on the current CoP, results in a significantly improved body posture.
Haptipedia: Accelerating Haptic Device Discovery to Support Interaction & Engineering Design
Authors: Hasti Seifi, Farimah Fazlollahi, Michael Oppermann, John Andrew Sastrillo, Jessica Ip, Ashutosh Agrawal, Gunhyuk Park, Katherine J. Kuchenbecker, Karon E. MacLean
Published at CHI, 2019

Creating haptic experiences often entails inventing, modifying, or selecting specialized hardware. However, interaction designers are rarely engineers, and 30 years of haptic inventions are buried in a fragmented literature that describes devices mechanically rather than by potential purpose. We conceived of Haptipedia to unlock this trove of examples: Haptipedia presents a device corpus for exploration through metadata that matter to both device and interaction designers. It is a taxonomy of device attributes that go beyond physical description to capture potential utility, applied to a growing database of 105 grounded force-feedback devices, and accessed through a public visualization that links utility to morphology. Haptipedia's design was driven by both systematic review of the haptic device literature and rich input from diverse haptic designers. We describe Haptipedia's reception (including hopes it will redefine device reporting standards) and our plans for its sustainability through community participation.
In a Silent Way: Communication Between AI and Improvising Musicians Beyond Sound
Authors: Jon McCormack, Toby Gifford, Patrick Hutchings, Maria Teresa Llano Rodriguez, Matthew Yee-King, Mark d'Inverno
Published at CHI, 2019

Collaboration is built on trust, and establishing trust with a creative Artificial Intelligence is difficult when the decision process or internal state driving its behaviour isn't exposed. When human musicians improvise together, a number of extra-musical cues are used to augment musical communication and expose mental or emotional states which affect musical decisions and the effectiveness of the collaboration. We developed a collaborative improvising AI drummer that communicates its confidence through an emoticon-based visualisation. The AI was trained on musical performance data, as well as real-time skin conductance, of musicians improvising with professional drummers, exposing both musical and extra-musical cues to inform its generative process. Uni- and bi-directional extra-musical communication with real and false values were tested by experienced improvising musicians. Each condition was evaluated using the FSS-2 questionnaire, as a proxy for musical engagement. The results show a positive correlation between extra-musical communication of machine internal state and human musical engagement.
Making Sense of Human-Food Interaction
Authors: Ferran Altarriba Bertran, Samvid Niravbhai Jhaveri, Rosa Lutz, Katherine Isbister, Danielle Wilde
Published at CHI, 2019

Activity in Human-Food Interaction (HFI) research is skyrocketing across a broad range of disciplinary interests and concerns. The dynamic and heterogeneous nature of this emerging field presents a challenge to scholars wishing to critically engage with prior work, identify gaps and ensure impact. It also challenges the formation of community. We present a Systematic Mapping Study of HFI research and an online data visualisation tool developed to respond to these issues. The tool allows researchers to engage in new ways with the HFI literature, propose modifications and additions to the review, and thereby actively engage in community-making. Our contribution is threefold: (1) we characterize the state of HFI, reporting trends, challenges and opportunities; (2) we provide a taxonomy and tool for diffractive reading of the literature; and (3) we offer our approach for adaptation by research fields facing similar challenges, positing value of the tool and approach beyond HFI.
Managing Messes in Computational Notebooks
Authors: Andrew Head, Fred Hohman, Titus Barik, Steven Mark Drucker, Robert DeLine
Published at CHI, 2019

Data analysts use computational notebooks to write code for analyzing and visualizing data. Notebooks help analysts iteratively write analysis code by letting them interleave code with output, and selectively execute cells. However, as analysis progresses, analysts leave behind old code and outputs, and overwrite important code, producing cluttered and inconsistent notebooks. This paper introduces code gathering tools, extensions to computational notebooks that help analysts find, clean, recover, and compare versions of code in cluttered, inconsistent notebooks. The tools archive all versions of code outputs, allowing analysts to review these versions and recover the subsets of code that produced them. These subsets can serve as succinct summaries of analysis activity or starting points for new analyses. In a qualitative usability study, 12 professional analysts found the tools useful for cleaning notebooks and writing analysis code, and discovered new ways to use them, like generating personal documentation and lightweight versioning.
Measuring the Separability of Shape, Size, and Color in Scatterplots
Authors: Stephen Smart, Danielle Albers Szafir
Published at CHI, 2019

Scatterplots commonly use multiple visual channels to encode multivariate datasets. Such visualizations often use size, shape, and color as these dimensions are considered separable--dimensions represented by one channel do not significantly interfere with viewers' abilities to perceive data in another. However, recent work shows the size of marks significantly impacts color difference perceptions, leading to broader questions about the separability of these channels. In this paper, we present a series of crowdsourced experiments measuring how mark shape, size, and color influence data interpretation in multiclass scatterplots. Our results indicate that mark shape significantly influences color and size perception, and that separability among these channels functions asymmetrically: shape more strongly influences size and color perceptions in scatterplots than size and color influence shape. Models constructed from the resulting data can help designers anticipate viewer perceptions to build more effective visualizations.
MindDot: Supporting Effective Cognitive Behaviors in Concept Map-Based Learning Environments
Authors: Shang Wang 0001, Deniz Sonmez Unal, Erin Walker
Published at CHI, 2019

While prior research has revealed the promising impact of concept mapping on learning, few have comprehensively modeled different cognitive behaviors during concept mapping. In addition, existing concept mapping tools lack effective feedback to support better learning behaviors. This work presents MindDot, a concept map-based learning environment that facilitates the cognitive process of comparing and integrating related concepts via two forms of support. A hyperlink support and an expert template. Study results suggested that both types of support had positive impact on the development of comparative strategies and that hyperlink support enhanced learning. We further evaluated the cognitive learning progress at a fine-grained level with two forms of visualizations. We then extracted several behavioral patterns that provided insights about the cognitive progress in learning. Lastly, we derive design recommendations that we hope will inspire future intelligent tutoring systems that automatically evaluate students' learning behaviors and foster them in developing effective learning behaviors
On the Shoulder of the Giant: A Multi-Scale Mixed Reality Collaboration with 360 Video Sharing and Tangible Interaction
Authors: Thammathip Piumsomboon, Gun A. Lee, Andrew Irlitti, Barrett Ens, Bruce H. Thomas, Mark Billinghurst
Published at CHI, 2019

We propose a multi-scale Mixed Reality (MR) collaboration between the Giant, a local Augmented Reality user, and the Miniature, a remote Virtual Reality user, in Giant-Miniature Collaboration (GMC). The Miniature is immersed in a 360-video shared by the Giant who can physically manipulate the Miniature through a tangible interface, a combined 360-camera with a 6 DOF tracker. We implemented a prototype system as a proof of concept and conducted a user study (n=24) comprising of four parts comparing: A) two types of virtual representations, B) three levels of Miniature control, C) three levels of 360-video view dependencies, and D) four 360-camera placement positions on the Giant. The results show users prefer a shoulder mounted camera view, while a view frustum with a complimentary avatar is a good visualization for the Miniature virtual representation. From the results, we give design recommendations and demonstrate an example Giant-Miniature Interaction.
PeerLens: Peer-inspired Interactive Learning Path Planning in Online Question Pool
Authors: Meng Xia, Mingfei Sun, Huan Wei, Qing Chen 0001, Yong Wang 0021, Lei Shi 0002, Huamin Qu, Xiaojuan Ma
Published at CHI, 2019

Online question pools like LeetCode provide hands-on exercises of skills and knowledge. However, due to the large volume of questions and the intent of hiding the tested knowledge behind them, many users find it hard to decide where to start or how to proceed based on their goals and performance. To overcome these limitations, we present PeerLens, an interactive visual analysis system that enables peer-inspired learning path planning. PeerLens can recommend a customized, adaptable sequence of practice questions to individual learners, based on the exercise history of other users in a similar learning scenario. We propose a new way to model the learning path by submission types and a novel visual design to facilitate the understanding and planning of the learning path. We conducted a within-subject experiment to assess the efficacy and usefulness of PeerLens in comparison with two baseline systems. Experiment results show that users are more confident in arranging their learning path via PeerLens and find it more informative and intuitive.