The Interactions Lab from the University of Calgary welcomes you to join us in our speaker series. We have a wonderful range of speakers from all over the world and they are here to spread their passion for data. Our lectures include an overview of speakers' research regarding data and data visualizations.
A new speaker will present every 6 weeks, so feel free to visit our homepage for updates. Please follow this website to find out more information about when the next one is presenting.
Dr. Dominikus Baur works as a freelance data visualization developer. His award-winning projects for clients like Google, the OECD or Microsoft Research make large datasets accessible, understandable, and usable. His work covers the whole spectrum from mobile apps, to websites, to large, touch-controlled installations – always focused on the people using them. As a computer scientist, he sees his work in the larger context of technological and societal developments and doesn’t shy away from asking critical questions.
Topic coming soon!
I am a Lecturer (eq. Assistant Professor) in the Department of Computer Science at City, University of London, and part of the giCentre research group.
I am a computer scientist specializing in information visualization and human computer interaction. I conduct research on designing and studying new interactions for visualizations and on understanding how people may make use of and interact with visualizations in their everyday lives. I am particularly interested in designing visualization tools for authoring personal visualizations and for exploring and communicating open data; in sports visualization; and in visualization beyond the desktop.
Before joining City, I was a Post-doc in the Department of Computer Science at the University of Calgary, InnoVis, with Sheelagh Carpendale. I obtained my PhD on Direct Manipulation for Information Visualization, at Université Paris Sud-XI in 2014, under the supervision of Jean-Daniel Fekete in the INRIA team AVIZ and Frédéric Vernier in the LIMSI-CNRS team AMI.
Although more and more people generate, collect, and have access to data, only few people can visualize and makes sense of data, using efficient and mainstream, but relatively complex, visualization tools. In contrast, most people in their everyday lives lack tools for exploring, making sense of, and sharing data. Thus, most people lack the tools to participate in the increasingly data-driven stories and debates of modern society. I will propose and illustrate strategies for engaging people with data in their everyday lives, around interaction discoverability, personal agency and sense of control, and flexibility in exploring, authoring, and sharing personal data. I will further discuss how I envision visualization changing the relationship between self and data, by revealing how data is ubiquitous, personal and cherishable, experiential and reflective, and a medium for sharing stories about self and others.
Parmit Chilana is an Assistant Professor at the School of Computing Science at Simon Fraser University where she directs the human-computer interaction (HCI) lab. Parmit’s core research in HCI focuses on the design and study of novel tools and techniques that help people use, learn, and program feature-rich software. Her work has been recognized with several awards and honors, including Best Paper and Honorable Mention awards at the ACM CHI conference. Parmit received her PhD from the University of Washington where her award-winning dissertation on crowdsourced contextual help became the basis of AnswerDash, a venture-funded startup in Seattle. Before coming to SFU, Parmit was an Assistant Professor at the University of Waterloo.
Millions of users seek help every day to troubleshoot feature-rich software applications, learn new functionality, or find application-related information. Although many knowledgebases, tutorials, Q&A sites, and other approaches exist for technical help retrieval, few users find them useful for all their help needs. In this talk, I will describe our approach for supporting in-application help retrieval by inventing new systems and techniques that connect users with each other in the context of their own tasks.
I will first present LemonAid, a selection-based crowdsourced contextual help retrieval system that allows users ask questions and retrieve answers from other users within a web-based application by selecting a label, widget, image, or another interface element.
Next, I will describe Social CheatSheet, an interactive information platform for retrieving community-curated help in the sidebar of any web application and show how users can quickly generate and aggregate task-focused curated instructions and multi-step tutorials using a combination of their own annotated screenshots and snippets of web-based help resources.
Lastly, I will discuss some of our initial work in connecting users directly with experts by establishing a shared visual context and enabling in-context real-time conversations within a 3D modeling application. In presenting all of these systems, I will discuss results from various formative studies, lab studies, and field evaluations that shed light on the effectiveness, usability, and utility of these approaches and talk about opportunities for future research to explore how to offer more automatic targeted curated help to users of feature-rich software.
Dr. Stefania Forlini is Associate Professor of English at the University of Calgary. An expert in nineteenth-century literature, material culture, and critical theory, her research employs both traditional and more recent digital humanities methods for literary analysis to examine how the popularization of science and technology shapes literary forms and material aesthetic practices. Her publications span the areas of Victorian studies, science fiction studies, the digital humanities, and information visualization.
The word “data” (from Latin) means that which is “given”. However, in humanities research, which depends heavily on interpretation, there are very few, if any, “givens”. This talk distills insights gained from incorporating information visualization into research in literary studies. In doing so, it considers how traditional humanistic practices of close reading and critical interpretation can help promote more ethical, creative and critically discerning engagements with data and its representations.
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