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2篇 您的检索式：作者名="Sarah Goodwin"

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		题名	作者	年代	出处	被引量
	1	The Data Visualisation and Immersive Analytics Research Lab at Monash University显示文摘This article reviews two decades of research in topics in Information Visualisation emerging from the Data Visualisation and Immersive Analytics Lab at Monash University Australia(Monash IA Lab).The lab has been influential with contributions in algorithms,interaction techniques and experimental results in Network Visualisation,Interactive Optimisation and Geographic and Cartographic visualisation.It has also been a leader in the emerging topic of Immersive Analytics,which explores natural interactions and immersive display technologies in support of data analytics.We reflect on advances in these areas but also sketch our vision for future research and developments in data visualisation more broadly.	Tim Dwyer Maxime Cordeil Tobias Czauderna Pari Delir Haghighi Barrett Ens Sarah Goodwin Bernhard Jenny Kim Marriott Michael Wybrow	2020	Visual Informatics2020，4，4：	0
	2	VETA:Visual eye-tracking analytics for the exploration of gaze patterns and behaviours显示文摘Eye tracking is growing in popularity for multiple application areas,yet analysing and exploring the large volume of complex data remains difficult for most users.We present a comprehensive eye tracking visual analytics system to enable the exploration and presentation of eye-tracking data across time and space in an efficient manner.The application allows the user to gain an overview of general patterns and perform deep visual analysis of local gaze exploration.The ability to link directly to the video of the underlying scene allows the visualisation insights to be verified on the fly.The system was motivated by the need to analyse eye-tracking data collected from an‘in the wild’study with energy network operators and has been further evaluated via interviews with 14 eye-tracking experts in multiple domains.Results suggest that,thanks to state-of-the-art visualisation techniques and by providing context with videos,our system could enable an improved analysis of eye-tracking data through interactive exploration,facilitating comparison between different participants or conditions,thus enhancing the presentation of complex data analysis to non-experts.This research paper provides four contributions:(1)analysis of a motivational use case demonstrating the need for rich visual-analytics workflow tools for eye-tracking data;(2)a highly dynamic system to visually explore and present complex eye-tracking data;(3)insights from our applied use case evaluation and interviews with experienced users demonstrating the potential for the system and visual analytics for the wider eye-tracking community.	Sarah Goodwin Arnaud Prouzeau Ryan Whitelock-Jones Christophe Hurter Lee Lawrence Umair Afzal Tim Dwyer	2022	Visual Informatics2022，6，2：	0

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