Browsing by Author "Collins, Christopher"

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Abbreviating Text Labels on Demand
(IEEE, 2017-10) Shimabukuro, Mariana; Collins, Christopher
Long text labels is a known challenge in information visualizations.There are some techniques used in order to solve this problem like setting a very small font size. On the other hand, sometimes the font size is so small that the text can be difficult to read. Wrapping sentences, dropping letters and text truncation are some techniques do deal with this problem. In order to investigate a solution for labeling long words we ran a study on how people create and interpret word abbreviations. Based on the study data we designed a new algorithm to automatically make words as short as they need to fit the text. Examples applications of this algorithm are presented in this paper.
An adaptive crowdsourced investigation of word abbreviation techniques for text visualizations
(2017-04-01) Shimabukuro, Mariana Akemi; Collins, Christopher
A known problem in information visualization labeling is when the text is too long to fit in the label space. There are some common known techniques used in order to solve this problem like setting a very small font size. On the other hand, sometimes the font size is so small that the text can be difficult to read. Wrapping sentences, dropping letters and text truncation can also be used. However, there is no research on how these techniques affect the legibility and readability of the visualization. In other words, we don’t know whether or not applying these techniques is the best way to tackle this issue. This thesis describes the design and implementation of a crowdsourced study that uses a recommendation system to narrow down abbreviations created by participants allowing us to efficiently collect and test the data in the same session. The study design also aims to investigate the effect of semantic context on the abbreviation that the participants create and the ability to decode them. Finally, based on the study data analysis we present a new technique to automatically make words as short as they need to be to maintain text legibility and readability.
Approaching Humanities Questions Using Slow Visual Search Interfaces
(2021-06-01) Bradley, Adam James; Sawal, Victor; Collins, Christopher
In this paper we discuss a visual search system that was designed and implemented for humanities scholars to ask questions of large document corpora. The system allows searches to be specified through traditional search, as well as through providing reference documents or visually exploring a semantic ontology for terms of interest. We offer a discussion of using visualization to try to answer humanities questions and take an honest look at the difficulties of using a methodology of one discipline to solve the problems of another.
Augmenting free-form annotations with digital metadata for close reading of poetry
(2015-12-01) Mehta, Hrim; Collins, Christopher
Many people, literary critics in particular, practice close reading, making annotations by hand while performing a detailed analysis of a text. Current digital tools for literary criticism,however, have many limitations with respect to annotation. In this work, we present an ethnographic study of 14 professional literary critics performing free-form annotations in the context of literary criticism, and a subsequent tool, MetaTation, for enhancing the close reading process, based on our findings. Our study revealed a set of cognitive processes supported through free-form annotation that have not previously been discussed in this context. We derived design guidelines for digital tools which augment active reading and annotation. The resulting system, MetaTation, uses an interactive pen-and-paper system with a peripheral display to provide analytic support while minimizing interference to the cognitive processes that guide the work flow. Through turning paper-based annotations into implicit queries, MetaTation provides well-organized and relevant supplemental information in a just-in-time manner.
Characterizing midair handwriting in virtual reality
(2024-04-01) Chan, Matthew; Collins, Christopher; Qureshi, Faisal
Midair handwriting poses challenges due to the lack of a physical plane to press against while writing, making it difficult to determine when ink should be placed. In this thesis, we gathered midair handwriting data from 24 participants in an environment that allowed them to write freely. We compared writing with a pen-like object and writing using a finger across two writing methods (writing freely versus on a virtual whiteboard). Using our data, we trained a neural network to detect when ink should be placed during midair handwriting, achieving an overall 85% accuracy. We developed a data-viewing application to recreate sentences for visual analysis. Participant feedback favoured the pen-like object as a writing utensil, with equal preference for both writing methods. Our contributions include a midair handwriting Virtual Reality (VR) application for data collection, a dataset containing 480 sentences of frame-by-frame midair handwriting data, and 20 unique prompts used in participant trials.
A "Communication Skills for Computer Scientists" Course
(ACM, 2009-07) Blume, Lil; Baecker, Ronald; Collins, Christopher; Donohue, Aran
This paper describes "Communication Skills for Computer Scientists," a novel undergraduate course at the University of Toronto. We describe in detail the three major instructional streams of the course: writing, speaking, and interpersonal communications. We present a novel approach to teaching writing, interactive multimedia web technology to teach public speaking, and specific interpersonal skills training as the integral parts of the course. We contribute a detailed description of the curriculum and report measures of success, both quantitative data and reactions from students in their own words.
Critical InfoVis: Exploring the Politics of Visualization
(ACM, 2013-04-27) Dörk, Marian; Feng, Patrick; Collins, Christopher; Carpendale, Sheelagh
As information visualization is increasingly used to raise awareness about social issues, difficult questions arise about the power of visualization. So far the research community has not given sufficient thought to how values and assumptions pervade information visualization. Taking engaging visualizations as a starting point, we outline a critical approach that promotes disclosure, plurality, contingency, and empowerment. Based on this approach, we pose some challenges and opportunities for visualization researchers and practitioners.
Design by Immersion: A Transdisciplinary Approach to Problem-Driven Visualizations
(IEEE, 2019-08-26) Hall, Kyle Wm.; Bradley, Adam J.; Hinrichs, Uta; Huron, Samuel; Wood, Jo; Collins, Christopher; Carpendale, Sheelagh
While previous work exists on how to conduct and disseminate insights from problem-driven visualization projects and design studies, the literature does not address how to accomplish these goals in transdisciplinary teams in ways that advance all disciplines involved. In this paper we introduce and define a new methodological paradigm we call design by immersion, which provides an alternative perspective on problem-driven visualization work. Design by immersion embeds transdisciplinary experiences at the center of the visualization process by having visualization researchers participate in the work of the target domain (or domain experts participate in visualization research). Based on our own combined experiences of working on cross-disciplinary, problem-driven visualization projects, we present six case studies that expose the opportunities that design by immersion enables, including (1) exploring new domain-inspired visualization design spaces, (2) enriching domain understanding through personal experiences, and (3) building strong transdisciplinary relationships. Furthermore, we illustrate how the process of design by immersion opens up a diverse set of design activities that can be combined in different ways depending on the type of collaboration, project, and goals. Finally, we discuss the challenges and potential pitfalls of design by immersion.
Exploring Entities in Text with Descriptive Non-photorealistic Rendering
(IEEE, 2013-03) Chang, Meng-Wei; Collins, Christopher
We present a novel approach to text visualization called descriptive non-photorealistic rendering which exploits the inherent spatial and abstract dimensions in text documents to integrate 3D non-photorealistic rendering with information visualization. The visualization encodes text data onto 3D models, emphasizing the relative significance of words in the text and the physical, real-world relationships between those words. Analytic exploration is supported through a collection of interactive widgets and direct multitouch interaction with the 3D models. We applied our method to analyze a collection of vehicle complaint reports from the National Highway Traffic Safety Administration (NHTSA), and through a qualitative study, we demonstrate how our system can support tasks such as comparing the reliability of different models, finding interesting facts, and revealing possible causal relations between car parts.
Exploring entities in text with descriptive non-photorealistic rendering
(2012-12-01) Chang, Meng-Wei; Collins, Christopher
We present a novel approach to text visualization called descriptive non-photorealistic rendering which exploits the inherent spatial and abstract dimensions in text documents to integrate 3D non-photorealistic rendering with information visualization. The visualization encodes text data onto 3D models, emphasizing the relative signi ficance of words in the text and the physical, real-world relationships between those words. Analytic exploration is supported through a collection of interactive widgets and direct multitouch interaction with the 3D models. We applied our method to analyze a collection of vehicle complaint reports from National Highway Traffic Safety Administration (NHTSA), and through a qualitative evaluation study, we demonstrate how our system can support tasks such as comparing the reliability of di fferent makes and models, finding interesting facts, and revealing possible causal relations between car parts.
Gloss positioning for a gaze aware L2 reading aid
(2023-08-01) Zhao, Zixin; Collins, Christopher
An important aspect of language learning is reading texts written in the learner’s second language (L2). However, reading can be a daunting task for language learners, as text may contain a large amount of unknown vocabulary. We developed a gaze-informed application that has the ability to augment articles with information about the text during reading, dynamically providing overlaid captions – or glosses – interlinearly, in the right margin, and a combination of both glosses. To test the usability of each type of gloss, we ran participant studies (N=19) with French learners where marginal glosses led to an increase in vocabulary matching scores (p<.01). We found that gloss positioning preferences mainly depend on L2 proficiency, with intermediate learners preferring marginal glosses and beginner learners preferring interlinear and combination of both glosses. Overall, participants all found that glossed text was helpful, but personal goals and L2 proficiencies affected gloss preferences.
Implicit gaze interaction for information visualization
(2021-08-01) Wang, Feiyang; Collins, Christopher
This thesis presents a novel marker-free method for identifying screens of interest when using head-mounted eye-tracking for visualization in cluttered and multi-screen environments. The presented approach offers a solution for discerning visualization entities from sparse backgrounds by incorporating edge-detection into the existing pipeline. The system allows for both more efficient screen identification and improved accuracy over the state-of-the-art ORB algorithm. To make use of this pipeline in visualization applications, a model is introduced to track a user’s interest in rendered visualization objects by collecting the gaze data and calculating the object group’s interest scores across selected visual features. With the interest model, We offer an implicit gaze interaction system that provides subtle interaction supports to improve group-of-interest objects visibility and to ease object selection in crowded regions of information visualizations.
An investigation of semantic patterns in passwords
(2013-08-01) Veras Guimaraes, Rafael; Collins, Christopher; Thorpe, Julie
The advent of large password leaks in recent years has exposed the security problems of passwords and enabled deeper empirical investigation of password patterns. Researchers have only touched the surface of patterns in password creation, having characterized patterns in terms of frequency, length, composition rules and, to some extent, syntactic patterns. The semantics of passwords remain largely unexplored. In this thesis, we aim to fill this gap by employing Natural Language Processing techniques to extract and leverage understanding of semantic patterns in passwords. We present the first framework for segmentation, semantic classification and semantic generalization of passwords and a model that captures the semantic essence of password samples. The results of our investigation demonstrate that the knowledge captured by our model can be used to crack more passwords than the state-of-the-art approach. In experiments limited to 3 billion guesses, our approach can guess 67% more passwords from the LinkedIn leak and 32% more passwords from the MySpace leak. Furthermore, we explore the implications of using date patterns in guessing attacks and investigate the lexical differences between standard English and the language used in passwords.
Lexichrome: Text Construction and Lexical Discovery with Word-Color Associations Using Interactive Visualization
(ACM, 2020-07-03) Kim, Chris K; Collins, Christopher; Hinrichs, Uta; Mohammad, Saif M
Based on word-color associations from a comprehensive, crowdsourced lexicon, we present Lexichrome: a web application that explores the popular perception of relationships between English words and eleven basic color terms using interactive visualization. Lexichrome provides three complementary visualizations: "Palette" presents the diversity of word-color associations across the color palette; "Words" reveals the color associations of individual words using a dictionary-like interface; "Roget's Thesaurus" uncovers color association patterns in different semantic categories found in the thesaurus. Finally, our text editor allows users to compose their own texts and examine the resultant chromatic fingerprints throughout the process. We studied the utility of Lexichrome in a two-part qualitative user study with nine participants from various writing-intensive professions. We find that the presence of word-color associations promotes awareness surrounding word choice, editorial decision, and audience reception, and introduce a variety of use cases, features, and opportunities applicable to creative writing, corporate communication, and journalism.
Magic Pen: automatic pen-mode switching for document annotation
(2022-08-01) Desousa, Kevin A.; Collins, Christopher
Traditional digital pen interfaces use menu buttons to change pen modes, resulting in time and cognitive load spent on round-trips and potential errors from tapping small mode selection buttons. This thesis presents Magic Pen, a technique that automatically switches between digital pen modes. The Magic Pen system is driven by a Long Short-Term Memory (LSTM) model trained on pen data collected from nine participants and uses Transfer Learning (TL) to tune itself towards a user’s specific annotations iteratively. If Magic Pen chooses the incorrect mode, mitigation techniques incorporate flick gestures and screen taps to correct or remove a stroke. An annotation environment was also developed to rapidly prototype annotation systems with user-supplied documents. Magic Pen was originally evaluated with 18 participants and further evaluated with 8 participants. Magic Pen was preferred over a more conventional menu approach, and using TL allowed for greater model predictability and stability.
Managing developer interruption
(2018-12-01) Perez Dias, Gabrielle Cristina; Collins, Christopher; Bradbury, Jeremy
The high frequency of interruptions during cognitively-intense activities can be annoying and detrimental to deadline-driven work, such as software development. When developers are interrupted they not only lose productivity from the time spent attending to the interruption but also from the time required to recover from it when they resume working. This thesis provides a solution that addresses the recovery process challenges. It focuses on the recovery of momentum based on the understanding that interruption recovery involves knowledge about the interrupted activity, the developer, as well as the context of the work. We designed FastRecovery, a tool in which data is collected while the developer is working normally. Once an interruption is detected, our tool processes the data assigning scores to each task in order to discover important moments. We propose a set of rules to include the most different types of tasks that a developer can perform. Thereafter, a curated video review is created to mitigate the effects of developer interruptions. A user study was conducted to evaluate the efficacy of our solution. Six participants used the tool for two periods of three days while we collected usage feedback along with self-reported impressions about the tool. The study results were positive and indicate that FastRecovery is beneficial with recovery from unexpected interruptions. Due to the small scale of the study these results are best characterized as an initial indication that our approach is promising with respect to interruption recovery.
A modular interface framework for multimodal annotations and visualizations in Human-AI collaboration
(2021-07-01) Kim, Chris; Collins, Christopher
Modular is a web-based annotation, visualization, and inference software plat-form for computational language and vision research. The platform enables researchers to set up an interface for efficiently annotating language and vision datasets, visualizing the predictions made by a machine learning model, and interacting with an intelligent system. Artificial intelligence (AI) research, including machine learning, computer vision, and natural language processing, requires large amounts of annotated data. The current research and development pipeline involves each group collecting their own datasets using an annotation tool tailored specifically to their needs, followed by a series of engineering efforts in loading other external datasets and developing their own interfaces, often mimicking some components of existing annotation tools. Extensible and customizable as required by individual projects, the framework has been successfully applied to a number of research efforts in human-AI collaboration, including commonsense grounding of language and vision data, conversational AI for collaboration with human users, and explainable AI in improving interpretability of the AI system. Facilitated by the aforementioned Modular framework, the dissertation ex-amines a notable set of opportunities that inspire the new, productive symbiosis between human users and AI agents, where the two parties can successfully complete a complex task together and mutually benefit in providing advantages missing from the other party. Finally, the dissertation sets out to evaluate whether human users can establish a level of appropriate trust and reliance through AI explanation.
Object-centric temporal navigation for dynamic information visualizations.
(2014-08-01) Kondo, Brittany; Collins, Christopher
We introduce object-centric temporal navigation for time-varying information visualizations. In our approach, navigation through time is controlled by interacting directly with any data item, enabling simultaneous exploration of the time dimension while focusing on the changing item. Subtle visualizations of a data item’s temporal trend are provided to guide navigation. To demonstrate how object-centric navigation can be designed for different types of dynamic visualizations, we created two techniques: DimpVis, for exploring changing visual variables in different information visualizations, and Glidgets, for exploring topological changes in dynamic graphs. Both techniques enable intuitive investigation of spatial queries. For example, using DimpVis to answer “Was this bar ever at 500?” in an animated bar chart, one simply has to drag the bar to that height. Comparative task-based evaluations revealed that DimpVis was quantitatively competitive to existing navigation techniques. Additionally, both Glidgets and DimpVis were overall subjectively preferred over the time slider by participants.
Perceptual Biases in Font Size as a Data Encoding
(IEEE, 2017-07-04) Alexander, Eric; Chang, Chih-Ching; Shimabukuro, Mariana; Franconeri, Steven; Collins, Christopher; Gleicher, Michael
Many visualizations, including word clouds, cartographic labels, and word trees, encode data within the sizes of fonts. While font size can be an intuitive dimension for the viewer, using it as an encoding can introduce factors that may bias the perception of the underlying values. Viewers might conﬂate the size of a word’s font with a word’s length, the number of letters it contains, or with the larger or smaller heights of particular characters (‘o’ vs. ‘p’ vs. ‘b’). We present a collection of empirical studies showing that such factors—which are irrelevant to the encoded values—can indeed inﬂuence comparative judgements of font size, though less than conventional wisdom might suggest. We highlight the largest potential biases, and describe a strategy to mitigate them.
Personalized Views for Immersive Analytics
(ACM, 2016-11) Bonada, Santiago; Veras, Rafael; Collins, Christopher
In this paper we present work-in-progress toward a vision of personalized views of visual analytics interfaces in the context of collaborative analytics in immersive spaces. In particular, we are interested in the sense of immersion, responsiveness, and personalization afforded by gaze-based input. Through combining large screen visual analytics tools with eye-tracking, a collaborative visual analytics system can become egocentric while not disrupting the collaborative nature of the experience. We present a prototype system and several ideas for real-time personalization of views in visual analytics.