DevLan/vispubs huggingface dataset:
Visualizing Validation of Protein Surface Classifiers
Authors: Alper Sarikaya, Danielle Albers, Jake Mitchell, Michael Gleicher
Published at EuroVis, 2014

Many bioinformatics applications construct classifiers that are validated in experiments that compare their results to known ground truth over a corpus. In this paper, we introduce an approach for exploring the results of such classifier validation experiments, focusing on classifiers for regions of molecular surfaces. We provide a tool that allows for examining classification performance patterns over a test corpus. The approach combines a summary view that provides information about an entire corpus of molecules with a detail view that visualizes classifier results directly on protein surfaces. Rather than displaying miniature 3D views of each molecule, the summary provides 2D glyphs of each protein surface arranged in a reorderable, small‐multiples grid. Each summary is specifically designed to support visual aggregation to allow the viewer to both get a sense of aggregate properties as well as the details that form them. The detail view provides a 3D visualization of each protein surface coupled with interaction techniques designed to support key tasks, including spatial aggregation and automated camera touring. A prototype implementation of our approach is demonstrated on protein surface classifier experiments.
Volumetric Data Reduction in a Compressed Sensing Framework
Authors: Xie Xu, Elham Sakhaee, Alireza Entezari
Published at EuroVis, 2014

In this paper, we investigate compressed sensing principles to devise an in‐situ data reduction framework for visualization of volumetric datasets. We exploit the universality of the compressed sensing framework and show that the proposed method offers a refinable data reduction approach for volumetric datasets. The accurate reconstruction is obtained from partial Fourier measurements of the original data that are sensed without any prior knowledge of specific feature domains for the data. Our experiments demonstrate the superiority of surfacelets for efficient representation of volumetric data. Moreover, we establish that the accuracy of reconstruction can further improve once a more effective basis for a sparser representation of the data becomes available.
A novel knee rehabilitation system for the home
Authors: Mobolaji Ayoade, Lynne Baillie
Published at CHI, 2014

In this paper, we describe the design and evaluation of an interactive home-based rehabilitation visualisation system used by a wide variety of ages (users in our studies were aged from 47-89) to undertake rehabilitation in the home following knee replacement surgery. We present the rehabilitation visualization system and the results of a randomized controlled study in which we investigated the usability and feasibility of the system in the home. We found that our users were able to use the system successfully for their rehabilitation with improved rehabilitation outcomes after 6 weeks when compared to the current rehabilitation care. Finally we highlight the lessons learned which will benefit prospective designers of home rehabilitation technology in ensuring successful home evaluations in clinical rehabilitation.
A user study of different gameplay visualizations
Authors: Simone Kriglstein, Günter Wallner, Margit Pohl
Published at CHI, 2014

With the rising interest in multiplayer gaming, gameplay statistics have become an increasingly important aspect of the overall game experience for many players. As a part of this trend, visualizations have gained great popularity among players, in particular heatmaps since they allow them to reenact the course of a game and to develop new strategies. In this paper we report results of a user study conducted with 29 players (i) to investigate how players use heatmaps and two further graphical representations that use clustering algorithms to interpret gameplay and (ii) to assess the three representations in regard to time efficiency, correctness, suitability, and player preference. Our results show that heatmaps were mainly used to detect hot spots while the cluster representations proved useful to compare variables, allowing the players to uncover relationships between them and in turn allowing a deeper insight into the gameplay data.
Addressing misconceptions about code with always-on programming visualizations
Authors: Thomas Lieber, Joel R. Brandt, Robert C. Miller
Published at CHI, 2014

We present Theseus, an IDE extension that visualizes run-time behavior within a JavaScript code editor. By displaying real-time information about how code actually behaves during execution, Theseus proactively addresses misconceptions by drawing attention to similarities and differences between the programmer's idea of what code does and what it actually does. To understand how programmers would respond to this kind of an always-on visualization, we ran a lab study with graduate students, and interviewed 9 professional programmers who were asked to use Theseus in their day-to-day work. We found that users quickly adopted strategies that are unique to always-on, real-time visualizations, and used the additional information to guide their navigation through their code.
Automatic generation of semantic icon encodings for visualizations
Authors: Vidya Setlur, Jock D. Mackinlay
Published at CHI, 2014

Authors use icon encodings to indicate the semantics of categorical information in visualizations. The default icon libraries found in visualization tools often do not match the semantics of the data. Users often manually search for or create icons that are more semantically meaningful. This process can hinder the flow of visual analysis, especially when the amount of data is large, leading to a suboptimal user experience. We propose a technique for automatically generating semantically relevant icon encodings for categorical dimensions of data points. The algorithm employs natural language processing in order to find relevant imagery from the Internet. We evaluate our approach on Mechanical Turk by generating large libraries of icons using Tableau Public workbooks that represent real analytical effort by people out in the world. Our results show that the automatic algorithm does nearly as well as the manually created icons, and particularly has higher user satisfaction for larger cardinalities of data.
Coding livecoding
Authors: Ben Swift, Andrew Sorensen, Michael A. Martin, Henry J. Gardner
Published at CHI, 2014

Livecoding is an artistic programming practice in which an artist's low-level interaction can be observed with sufficiently high fidelity to allow for transcription and analysis. This paper presents the first reported "coding" of livecoding videos. From an identified corpus of videos available on the web, we coded performances of two different livecoding artists, recording both the (textual) programming edit events and the musical effect of these edits. Our analysis includes a novel, transition-matrix visualisation of the textual and musical dimensions of this data to create a "performer fingerprint". We show how detailed transcriptions of livecoding videos can be made which, we hope, will provide a foundation for further research into describing and understanding livecoding.
Crowdsourcing step-by-step information extraction to enhance existing how-to videos
Authors: Juho Kim, Phu Tran Nguyen, Sarah A. Weir, Philip J. Guo, Robert C. Miller, Krzysztof Z. Gajos
Published at CHI, 2014

Millions of learners today use how-to videos to master new skills in a variety of domains. But browsing such videos is often tedious and inefficient because video player interfaces are not optimized for the unique step-by-step structure of such videos. This research aims to improve the learning experience of existing how-to videos with step-by-step annotations. We first performed a formative study to verify that annotations are actually useful to learners. We created ToolScape, an interactive video player that displays step descriptions and intermediate result thumbnails in the video timeline. Learners in our study performed better and gained more self-efficacy using ToolScape versus a traditional video player. To add the needed step annotations to existing how-to videos at scale, we introduce a novel crowdsourcing workflow. It extracts step-by-step structure from an existing video, including step times, descriptions, and before and after images. We introduce the Find-Verify-Expand design pattern for temporal and visual annotation, which applies clustering, text processing, and visual analysis algorithms to merge crowd output. The workflow does not rely on domain-specific customization, works on top of existing videos, and recruits untrained crowd workers. We evaluated the workflow with Mechanical Turk, using 75 cooking, makeup, and Photoshop videos on YouTube. Results show that our workflow can extract steps with a quality comparable to that of trained annotators across all three domains with 77% precision and 81% recall.
DemoWiz: re-performing software demonstrations for a live presentation
Authors: Pei-Yu Chi, Bongshin Lee, Steven Mark Drucker
Published at CHI, 2014

Showing a live software demonstration during a talk can be engaging, but it is often not easy: presenters may struggle with (or worry about) unexpected software crashes and encounter issues such as mismatched screen resolutions or faulty network connectivity. Furthermore, it can be difficult to recall the steps to show while talking and operating the system all at the same time. An alternative is to present with pre-recorded screencast videos. It is, however, challenging to precisely match the narration to the video when using existing video players. We introduce DemoWiz, a video presentation system that provides an increased awareness of upcoming actions through glanceable visualizations. DemoWiz supports better control of timing by overlaying visual cues and enabling lightweight editing. A user study shows that our design significantly improves the presenters' perceived ease of narration and timing compared to a system without visualizations that was similar to a standard playback control. Furthermore, nine (out of ten) participants preferred DemoWiz over the standard playback control with the last expressing no preference.
Dive in!: enabling progressive loading for real-time navigation of data visualizations
Authors: Michael Glueck, Azam Khan, Daniel J. Wigdor
Published at CHI, 2014

We introduce Splash, a framework reducing development overhead for both data curators and visualization developers of client-server visualization systems. Splash streamlines the process of creating a multiple level-of-detail version of the data and facilitates progressive data download, thereby enabling real-time, on-demand navigation with existing visualization toolkits. As a result, system responsiveness is increased and the user experience is improved. We demonstrate the benefit of progressive loading for user interaction on slower networks. Additionally, case study evaluations of Splash with real-world data curators suggest that Splash supports iterative refinement of visualizations and promotes the use of exploratory data analysis.
Effects of display size and navigation type on a classification task
Authors: Can Liu 0003, Olivier Chapuis, Michel Beaudouin-Lafon, Eric Lecolinet, Wendy E. Mackay
Published at CHI, 2014

The advent of ultra-high resolution wall-size displays and their use for complex tasks require a more systematic analysis and deeper understanding of their advantages and drawbacks compared with desktop monitors. While previous work has mostly addressed search, visualization and sense-making tasks, we have designed an abstract classification task that involves explicit data manipulation. Based on our observations of real uses of a wall display, this task represents a large category of applications. We report on a controlled experiment that uses this task to compare physical navigation in front of a wall-size display with virtual navigation using pan-and-zoom on the desktop. Our main finding is a robust interaction effect between display type and task difficulty: while the desktop can be faster than the wall for simple tasks, the wall gains a sizable advantage as the task becomes more difficult. A follow-up study shows that other desktop techniques (overview+detail, lens) do not perform better than pan-and-zoom and are therefore slower than the wall for difficult tasks.
End-users publishing structured information on the web: an observational study of what, why, and how
Authors: Edward Benson, David R. Karger
Published at CHI, 2014

End-users are accustomed to filtering and browsing styled collections of data on professional web sites, but they have few ways to create and publish such information architectures for themselves. This paper presents a full-lifecycle analysis of the Exhibit framework - an end-user tool which provides such functionality - to understand the needs, capabilities, and practices of this class of users. We include interviews, as well as analysis of over 1,800 visualizations and 200,000 web interactions with these visualizations. Our analysis reveals important findings about this user population which generalize to the task of providing better end-user structured content publication tools.
Faces engage us: photos with faces attract more likes and comments on Instagram
Authors: Saeideh Bakhshi, David A. Shamma, Eric Gilbert
Published at CHI, 2014

Photos are becoming prominent means of communication online. Despite photos' pervasive presence in social media and online world, we know little about how people interact and engage with their content. Understanding how photo content might signify engagement, can impact both science and design, influencing production and distribution. One common type of photo content that is shared on social media, is the photos of people. From studies of offline behavior, we know that human faces are powerful channels of non-verbal communication. In this paper, we study this behavioral phenomena online. We ask how presence of a face, it's age and gender might impact social engagement on the photo. We use a corpus of 1 million Instagram images and organize our study around two social engagement feedback factors, likes and comments. Our results show that photos with faces are 38% more likely to receive likes and 32% more likely to receive comments, even after controlling for social network reach and activity. We find, however, that the number of faces, their age and gender do not have an effect. This work presents the first results on how photos with human faces relate to engagement on large scale image sharing communities. In addition to contributing to the research around online user behavior, our findings offer a new line of future work using visual analysis.
Highlighting interventions and user differences: informing adaptive information visualization support
Authors: Giuseppe Carenini, Cristina Conati, Enamul Hoque, Ben Steichen, Dereck Toker, James T. Enns
Published at CHI, 2014

There is increasing evidence that the effectiveness of information visualization techniques can be impacted by the particular needs and abilities of each user. This suggests that it is important to investigate information visualization systems that can dynamically adapt to each user. In this paper, we address the question of how to adapt. In particular, we present a study to evaluate a variety of visual prompts, called "interventions", that can be performed on a visualization to help users process it. Our results show that some of the tested interventions perform better than a condition in which no intervention is provided, both in terms of task performance as well as subjective user ratings. We also discuss findings on how intervention effectiveness is influenced by individual differences and task complexity.
In-your-face, yet unseen?: improving head-stabilized warnings to reduce reaction time
Authors: Felix Lauber, Andreas Butz
Published at CHI, 2014

One unique property of head-mounted displays (HMDs) is that content can easily be displayed at a fixed position within the user's field of view (head-stabilized). This ensures that critical information (e.g. warnings) is continuously visible and can, in principle, be perceived as quickly as possible. We examined this strategy with a physically and visually distracted driver. We ran two consecutive studies in a driving simulator, comparing different warning visualizations in a head-up display (HUD) and a HMD. In an initial study, we found no significant effects of warning type or display technology on the reaction times. In a second study, after modifying our visualization to include a visual reference marker, we found that with only this minor change, reaction times were significantly lower in the HMD when compared to the HUD. Our insights can help others design better head-stabilized notifications.
ISSE: an interactive source separation editor
Authors: Nicholas J. Bryan, Gautham J. Mysore, Ge Wang 0002
Published at CHI, 2014

Traditional audio editing tools do not facilitate the task of separating a single mixture recording (e.g. pop song) into its respective sources (e.g. drums, vocal, etc.). Such ability, however, would be very useful for a wide variety of audio applications such as music remixing, audio denoising, and audio-based forensics. To address this issue, we present ISSE - an interactive source separation editor. ISSE is a new open-source, freely available, and cross-platform audio editing tool that enables a user to perform source separation by painting on time-frequency visualizations of sound, resulting in an interactive machine learning system. The system brings to life our previously proposed interaction paradigm and separation algorithm that learns from user-feedback to perform separation. For evaluation, we conducted user studies and compared results between inexperienced and expert users. For a variety of real-world tasks, we found that inexperienced users can achieve good separation quality with minimal instruction and expert users can achieve state-of-the-art separation quality.
Kinetica: naturalistic multi-touch data visualization
Authors: Jeffrey M. Rzeszotarski, Aniket Kittur
Published at CHI, 2014

Over the last several years there has been an explosion of powerful, affordable, multi-touch devices. This provides an outstanding opportunity for novel data visualization techniques that leverage new interaction methods and minimize their barriers to entry. In this paper we describe an approach for multivariate data visualization that uses physics-based affordances that are easy to intuit, constraints that are easy to apply and visualize, and a consistent view as data is manipulated in order to promote data exploration and interrogation. We provide a framework for exploring this problem space, and an example proof of concept system called Kinetica. We describe the results of a user study that suggest users of Kinetica were able to explore multiple dimensions of data at once, identify outliers, and discover trends with minimal training.
Monadic exploration: seeing the whole through its parts
Authors: Marian Dörk, Rob Comber, Martyn Dade-Robertson
Published at CHI, 2014

Monadic exploration is a new approach to interacting with relational information spaces that challenges the distinction between the whole and its parts. Building on the work of sociologists Gabriel Tarde and Bruno Latour we turn to the concept of the monad as a useful lens on online communities and collections that expands the possibility for creating meaning in their navigation. While existing interfaces tend to emphasize either the structure of the whole or details of a part, monadic exploration brings these opposing perspectives closer together in continuous movements between partially overlapping points of view. We present a visualization that reflects a given node's relative position within a network using radial displacements and visual folding. To investigate the potential of monadic exploration we report on an iterative design process of a web-based visualization of a highly cross-referenced book and its six-month deployment.
NewsViews: an automated pipeline for creating custom geovisualizations for news
Authors: Tong Gao, Jessica Hullman, Eytan Adar, Brent J. Hecht, Nicholas Diakopoulos
Published at CHI, 2014

Interactive visualizations add rich, data-based context to online news articles. Geographic maps are currently the most prevalent form of these visualizations. Unfortunately, designers capable of producing high-quality, customized geovisualizations are scarce. We present NewsViews, a novel automated news visualization system that generates interactive, annotated maps without requiring professional designers. NewsViews' maps support trend identification and data comparisons relevant to a given news article. The NewsViews system leverages text mining to identify key concepts and locations discussed in articles (as well as potential annotations), an extensive repository of 'found' databases, and techniques adapted from cartography to identify and create visually 'interesting' thematic maps. In this work, we develop and evaluate key criteria in automatic, annotated, map generation and experimentally validate the key features for successful representations (e.g., relevance to context, variable selection, 'interestingness' of representation and annotation quality).
Permulin: mixed-focus collaboration on multi-view tabletops
Authors: Roman Lissermann, Jochen Huber, Martin Schmitz, Jürgen Steimle, Max Mühlhäuser
Published at CHI, 2014

We contribute Permulin, an integrated set of interaction and visualization techniques for multi-view tabletops to support co-located collaboration across a wide variety of collaborative coupling styles. These techniques (1) provide support both for group work and for individual work, as well as for the transitions in-between, (2) contribute sharing and peeking techniques to support mutual awareness and group coordination during phases of individual work, (3) reduce interference during group work on a group view, and (4) directly integrate with conventional multi-touch input. We illustrate our techniques in a proof-of-concept implementation with the two example applications of map navigation and photo collages. Results from two user studies demonstrate that Permulin supports fluent transitions between individual and group work and exhibits unique awareness properties that allow participants to be highly aware of each other during tightly coupled collaboration, while being able to unobtrusively perform individual work during loosely coupled collaboration.
Pervasive information through constant personal projection: the ambient mobile pervasive display (AMP-D)
Authors: Christian Winkler 0001, Julian Seifert, David Dobbelstein, Enrico Rukzio
Published at CHI, 2014

The vision of pervasive ambient information displays which show relevant information has not yet come true. One of the main reasons is the limited number of available displays in the environment which is a fundamental requirement of the original vision. We introduce the concept of an Ambient Mobile Pervasive Display AMP-D which is a wearable projector system that constantly projects an ambient information display in front of the user. The floor display provides serendipitous access to public and personal information. The display is combined with a projected display on the user's hand, forming a continuous interaction space that is controlled by hand gestures. The paper introduces this novel device concept, discusses its interaction design, and explores its advantages through various implemented application examples. Furthermore, we present the AMP-D prototype which illustrates the involved challenges concerning hardware, sensing, and visualization.