502 research outputs found

    Summary of the workshop on visual methods and analyzing visual data in human computer interaction

    No full text
    Visual methods have become increasingly vital in Human Computer Interaction (HCI) research, particularly as we analyze and interpret the complex visual data that emerges from various interaction modalities. However, the methodologies for analyzing this visual data remain underdeveloped compared to textual data analysis. This workshop seeks to unite HCI researchers who work with visual data-such as hand sketches, photographs, physical artifacts, UI screenshots, videos, and information visualizations-To identify, name, and categorize methods for analyzing visual data in HCI.</p

    Interactive tables in the wild - visitor experiences with multi-touch tables in the Arctic exhibit at the Vancouver Aquarium

    No full text
    Funding: Alberta Innovates–Technology Futures (Alberta Ingenuity & iCORE), CFI, NSERC, and SMART Technologies.This report describes and discusses the findings from a field study that was conducted at the Vancouver Aquarium to investigate how visitors explore and experience large horizontal multi-touch tables as part of public exhibition spaces. The study investigated visitors’ use of two different tabletop applications—the Collection Viewer and the Arctic Choices table—that are part of the Canada’s Arctic exhibition at the Vancouver Aquarium. Our findings show that both tabletop exhibits enhanced the exhibition in different ways. The Collection Viewer table evoked visitors curiosity by presenting visually interesting information and engaged by supporting lightweight, playful, and open-ended information exploration. The Arctic Choices table enabled visitors to explore a variety of information about environmental and political changes within the Arctic in depth by providing detailed data visualizations. The application triggered a lot of insightful discussions among visitors. Our study findings include a discussion of the factors that attracted visitors’ attention and triggered interaction with both tabletop exhibits, the character and duration of information exploration, general exploration strategies, and factors that triggered social and collaborative information exploration. We also discuss usability issues of both tabletop applications alongside possible solutions

    Gestures in the wild : studying multi-touch gesture sequences on interactive tabletop exhibits

    No full text
    In this paper we describe our findings from a field study that was conducted at the Vancouver Aquarium to investigate how visitors interact with a large interactive table exhibit using multi-touch gestures. Our findings show that the choice and use of multi-touch gestures are influenced not only by general preferences for certain gestures but also by the interaction context and social context they occur in. We found that gestures are not executed in isolation but linked into sequences where previous gestures influence the formation of subsequent gestures. Furthermore, gestures were used beyond the manipulation of media items to support social encounters around the tabletop exhibit. Our findings indicate the importance of versatile many-to-one mappings between gestures and their actions that, other than one-to-one mappings, can support fluid transitions between gestures as part of sequences and facilitate social information exploration

    Making sense of wild data : using visualization to analyze in-the-wild video records

    No full text
    In this paper we describe our use of information visualization to facilitate the analysis of in-the-wild video data. Video recording is often the method of choice when conducting in-the-wild studies. It results in highly rich and detailed data collections that can be revisited many times and analyzed from different perspectives. However, the qualitative analysis of video recordings collected in real-world settings is known as a tedious and time consuming activity, because the data can contain a large number of activity layers that have to be identified and manually extracted through video coding. We have utilized customized information visualizations to create visual representations of coded video recordings that consider particularly the temporal, social and spatial context of interactions. We describe how these visual abstractions from rich video data were valuable in various stages of our analysis process, including the cataloguing of video data, identifying research questions, in-depth analysis, and, finally, communicating our study results. We also point out various challenges that we identified in this process.Non peer reviewe

    GROUPLAB AT SKIGRAPH

    No full text
    The Western Computer Graphics Symposium, nicknamed &apos;SkiGraph&apos;, is an annual professional meeting comprising mostly graphics researchers and their graduate students from Western Canada. In 2000, several Western Canadian researchers in Human Computer Interaction: Saul Greenberg (U.Calgary), Carl Gutwin (U. Saskatchewan), Kori Inkpen (Simon Fraser) and Sheelagh Carpendale (U. Calgary) agreed to use Skigraph as a way to get themselves and their graduate students together, where students would present papers describing their research. Because it was important for all graduate students to share their ideas, the papers written could range from identification of research areas and tentative proposals of research problems all the way to detailed results from mature work. This research report collects five research papers by students at Grouplab to SkiGraph (Grouplab is the laboratory for human computer interaction research at the University of Calgary). The papers are listed below. In all cases, the students are the first author followed by faculty members who have supervised or contributed to the work in one way or another. Individual papers may be cited directly by including the following information.We are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at [email protected]

    3d tabletop display interaction

    No full text
    Bibliography: p. 199-212Some pages are in colour

    Digging Into Data White Paper:Trading Consequences

    No full text
    Scholars interested in nineteenth-century global economic history face a voluminous historical record. Conventional approaches to primary source research on the economic and environmental implications of globalised commodity flows typically restrict researchers to specific locations or a small handful of commodities. By taking advantage of cutting-edge computational tools, the project was able to address much larger data sets for historical research, and thereby provides historians with the means to develop new data-driven research questions. In particular, this project has demonstrated that text mining techniques applied to tens of thousands of documents about nineteenth-century commodity trading can yield a novel understanding of how economic forces connected distant places all over the globe and how efforts to generate wealth from natural resources impacted on local environments.The large-scale findings that result from the application of these new methodologies would be barely feasible using conventional research methods. Moreover, the project vividly demonstrates how the digital humanities can benefit from trans-disciplinary collaboration between humanists, computational linguists and information visualisation experts. Important facets of this project include:· After considerable difficulty and lengthy negotiations, we acquired significantly more historical documents than we originally expected. The full corpus exceeds 7 billion word tokens, which is very big data by humanist standards.· Lexicon creation proved to be one of the most challenging and interesting aspects of the project, requiring interdisciplinary skills in archival research, linked data, text mining and knowledge of the historical context.· The project has identified almost 2,000 commodities that were regularly traded in the nineteenth century, two orders of magnitude more than are standardly studied by historians.· Historical sources that have undergone Optical Character Recognition (OCR) are challenging to process and this, in combination with the particular questions asked by historians, required the text mining team to develop new approaches and new text processing tools for the project.· The geospatial nature of the data lent itself well to an interactive visualisation that displays commodities in relation to locations on a world map. The same commodities can also be visualised on a timeline to show how trading evolved over the nineteenth century.· The relational database and visualisation software is well advanced and ready for use in historical research. The database can by used by historians for unguided research aimed at developing new research questions and identifying crucial primary source texts related to a specific commodit

    Node focused visualization of large trees

    No full text
    Bibliography: p. 97-110Most pages are in colour

    Studying direct-touch interaction for 2D flow visualization

    No full text
    Traditionally, scientific visualization research concentrates on the development and improvement of interactive techniques to support expert data analysis. While many scientific visualization tools have been developed for desktop environments and individual use, scenarios that go beyond mouse and keyboard interaction have received considerably less attention. We present a study that investigates how large-display direct-touch interaction affects data exploration and insight generation among groups of nonexperts exploring 2D vector data. In this study, pairs of participants used interaction techniques to customize and explore 2D vector visualizations and collaboratively discussed the process to develop their own understanding of the data sets
    corecore