EuroVisSTAR2020

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https://diglib.eg.org/handle/10.2312/2632896

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Browsing EuroVisSTAR2020 by Subject "Human centered computing"

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    The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Chatzimparmpas, Angelos; Martins, Rafael M.; Jusufi, Ilir; Kucher, Kostiantyn; Rossi, Fabrice; Kerren, Andreas; Smit, Noeska and Oeltze-Jafra, Steffen and Wang, Bei
    Machine learning (ML) models are nowadays used in complex applications in various domains, such as medicine, bioinformatics, and other sciences. Due to their black box nature, however, it may sometimes be hard to understand and trust the results they provide. This has increased the demand for reliable visualization tools related to enhancing trust in ML models, which has become a prominent topic of research in the visualization community over the past decades. To provide an overview and present the frontiers of current research on the topic, we present a State-of-the-Art Report (STAR) on enhancing trust in ML models with the use of interactive visualization. We define and describe the background of the topic, introduce a categorization for visualization techniques that aim to accomplish this goal, and discuss insights and opportunities for future research directions. Among our contributions is a categorization of trust against different facets of interactive ML, expanded and improved from previous research. Our results are investigated from different analytical perspectives: (a) providing a statistical overview, (b) summarizing key findings, (c) performing topic analyses, and (d) exploring the data sets used in the individual papers, all with the support of an interactive web-based survey browser. We intend this survey to be beneficial for visualization researchers whose interests involve making ML models more trustworthy, as well as researchers and practitioners from other disciplines in their search for effective visualization techniques suitable for solving their tasks with confidence and conveying meaning to their data.
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    A Survey on Transit Map Layout - from Design, Machine, and Human Perspectives
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Wu, Hsiang-Yun; Niedermann, Benjamin; Takahashi, Shigeo; Roberts, Maxwell J.; Nöllenburg, Martin; Smit, Noeska and Oeltze-Jafra, Steffen and Wang, Bei
    Transit maps are designed to present information for using public transportation systems, such as urban railways. Creating a transit map is a time-consuming process, which requires iterative information selection, layout design, and usability validation, and thus maps cannot easily be customised or updated frequently. To improve this, scientists investigate fully- or semi-automatic techniques in order to produce high quality transit maps using computers and further examine their corresponding usability. Nonetheless, the quality gap between manually-drawn maps and machine-generated maps is still large. To elaborate the current research status, this state-of-the-art report provides an overview of the transit map generation process, primarily from Design, Machine, and Human perspectives. A systematic categorisation is introduced to describe the design pipeline, and an extensive analysis of perspectives is conducted to support the proposed taxonomy. We conclude this survey with a discussion on the current research status, open challenges, and future directions.