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Annotation Big Data Analytics has become a major decision support factor in industry and government organisations Visual Analytics is the enabling science for effective exploration of big data through meaningful visualisations and interactive user interfaces Understanding the multidisciplinary nature, including user querying, powerful analytics, machine learning, visualisation, human computer interaction, perception and cognition, is critical for Visual Analytics to be effectively deployed The aim of BDVA is to bring together international experts to address cutting edge scientific problems from all relevant areas of big data visual analytics BDVA will host an exciting programme with internationally renowned keynote speakers, special sessions, and a day of hands on workshops tutorials.
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"How can we make sense of the myriad visual images surrounding us today? How can we strategically use images with a clear understanding of their function and impact? This book answers these questions by providing new "ways of seeing" visual representations through different lenses and in different contexts. It then provides practical guidance for creating purposeful and ethical visual communication. The authors recognize the accelerating dominion of images in communication, society, and culture. We human beings process images and video effortlessly and automatically. Visuals carry an emotional and visceral punch that text can rarely, if ever, match. As multinational marketers, social media influencers, and teenagers on TikTok know, visuals create their own language, accessible to all, regardless of traditional textual barriers of understanding such as education or language"--
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This dissertation by Kahin Akram Hassan explores user-centered evaluations of visualizations for temporal data, aimed at enhancing understanding and insights across various domains. The research focuses on developing effective visual analysis tools by considering user needs and data structures. It involves five user studies assessing different visualization techniques, such as radial designs for cyclic data, 2D and 3D parallel coordinates for pattern finding, and visual analytics tools for multivariate temporal datasets. The studies highlight the importance of selecting appropriate visualizations to facilitate user insights and underscore the role of user collaboration in creating effective tools. The work is intended for researchers and professionals in data visualization and analysis.
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This thesis by Quan Van Ho presents a geovisual analytics framework designed to manage, process, and visualize large multivariate data sets. The framework, implemented in Adobe Flash ActionScript and HTML5, emphasizes interactive and web-enabled tools to aid users in making data-driven decisions, even in time-critical situations. It introduces techniques for linking multiple coordinated views, capturing and sharing insights through a snapshot technique, and applies these methods across various domains such as ocean data, network data, spatial interaction data, and flood data. The work aims to reduce development time for customized geovisual analytics applications, making visual analytics accessible to a broader audience.
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This dissertation by Elmira Zohrevandi explores the development and evaluation of real-time visual analytics interfaces designed to enhance human-automation collaboration in air traffic control. The thesis applies ecological design theories to create visual tools that support air traffic controllers in conflict detection and resolution tasks. It introduces four novel interfaces to improve controllers' analytical capabilities and reduce traffic complexity. The research aims to present information effectively to operators, minimizing cognitive overload and enhancing decision-making processes. The intended audience includes researchers and professionals in air traffic control and visualization design fields.
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"This volume collects landmark research in a burgeoning field of visual analytics for linguistics, called LingVis. Combining linguistic data and linguistically oriented research questions with techniques and methodologies developed in the computer science fields of visual analytics and information visualization, LingVis is motivated by the growing need within linguistic research for dealing with large amounts of complex, multidimensional data sets. An innovative exploration into the future of LingVis in the digital age, this foundational book both provides a representation of the current state of the field and communicates its new possibilities for addressing complex linguistic questions across the larger linguistic community"--
Information visualization --- Visual analytics --- Linguistics
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