Browsing by Author "Dasgupta, Aritra"

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    Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization
    (© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Dasgupta, Aritra; Arendt, Dustin L.; Franklin, Lyndsey R.; Wong, Pak Chung; Cook, Kristin A.; Chen, Min and Benes, Bedrich
    Real‐world systems change continuously. In domains such as traffic monitoring or cyber security, such changes occur within short time scales. This results in a streaming data problem and leads to unique challenges for the human in the loop, as analysts have to ingest and make sense of dynamic patterns in real time. While visualizations are being increasingly used by analysts to derive insights from streaming data, we lack a thorough characterization of the human‐centred design problems and a critical analysis of the state‐of‐the‐art solutions that exist for addressing these problems. In this paper, our goal is to fill this gap by studying how the state of the art in streaming data visualization handles the challenges and reflect on the gaps and opportunities. To this end, we have three contributions in this paper: (i) problem characterization for identifying domain‐specific goals and challenges for handling streaming data, (ii) a survey and analysis of the state of the art in streaming data visualization research with a focus on how visualization design meets challenges specific to change perception and (iii) reflections on the design trade‐offs, and an outline of potential research directions for addressing the gaps in the state of the art.Real‐world systems change continuously. In domains such as traffic monitoring or cyber security, such changes occur within short time scales. This results in a streaming data problem and leads to unique challenges for the human in the loop, as analysts have to ingest and make sense of dynamic patterns in real time. While visualizations are being increasingly used by analysts to derive insights from streaming data, we lack a thorough characterization of the human‐centred design problems and a critical analysis of the state‐of‐the‐art solutions that exist for addressing these problems.
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    Privacy-Preserving Data Visualization: Reflections on the State of the Art and Research Opportunities
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Bhattacharjee, Kaustav; Chen, Min; Dasgupta, Aritra; Smit, Noeska and Oeltze-Jafra, Steffen and Wang, Bei
    Preservation of data privacy and protection of sensitive information from potential adversaries constitute a key socio-technical challenge in the modern era of ubiquitous digital transformation. Addressing this challenge needs analysis of multiple factors: algorithmic choices for balancing privacy and loss of utility, potential attack scenarios that can be undertaken by adversaries, implications for data owners, data subjects, and data sharing policies, and access control mechanisms that need to be built into interactive data interfaces. Visualization has a key role to play as part of the solution space, both as a medium of privacy-aware information communication and also as a tool for understanding the link between privacy parameters and data sharing policies. The field of privacy-preserving data visualization has witnessed progress along many of these dimensions. In this state-of-theart report, our goal is to provide a systematic analysis of the approaches, methods, and techniques used for handling data privacy in visualization. We also reflect on the road-map ahead by analyzing the gaps and research opportunities for solving some of the pressing socio-technical challenges involving data privacy with the help of visualization.