Guidance in Visual Analytics through Mixed-Initiative and Implicit Interaction

通过混合主动和隐式交互进行可视化分析的指导

• 批准号: RGPIN-2021-04353
• 负责人: Collins, Christopher
• 金额: $ 3.5万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742900
• 关键词: Guidance; Visual; Analytics; through; Mixed

Visual analytics is the science of combining data processing and information visualization to support people in understanding data. Its strength comes from having computers do work appropriate to their capabilities, such as counting and organizing data, while human analysts do the work of reasoning, evidence gathering, and decision-making. The focus of the computational aspect of this collaboration has long been on data mining, layout, and displaying large amounts of information. Guiding the analytic process has primarily been solely the domain of the human analyst. My research will investigate ways for software to advise human analysts on steps to take when exploring datasets. Much interpersonal communication occurs implicit means - body language, intonation, facial expression, and word choice. Our explicit communication is supported by these implicit cues. Implicit cues offer a lot of opportunity to improve the effectiveness of our work with computer systems. For example, by monitoring the gaze of a user looking at a sequence of points in a chart, an analytic system could suggest additional unexplored items which may fit the user's interest, without being explicitly asked, and without the user explicitly stating their interest. This research will explore implicit cues from pen, touch, gestures in virtual reality, and eye gaze.  There is a trade-off around how far to take the role of computers in analyzing data. Automatic highlighting or hiding of data introduces risk of algorithmic bias. But burdening analysts without guidance is equally inappropriate, as the work is more difficult, and important data may be missed. I will investigate this trade-off: where should the control lie, what sorts of guidance is possible and helpful, and when should guidance be provided? Text analytics will be the main testbed for the investigation. Billions of pages of text, in many languages, are produced daily: emails, news, blogs, reviews, discussion forums, academic articles, and business reports. This research will produce a collection of interactive tools for text which couple implicit interaction, sophisticated linguistic analysis, and visualization to reveal hidden information, such as topics, trends, and emotions. I envision introducing new ways to navigate and use text collections online, lessening the burden of information overload by enriching and focusing the acts of analysis and reading. This research will introduce new visual analytic practices, achieving a closer coupling of analysts and algorithms. 12 trainees will receive specialized training in highly sought-after data science skills. The outcomes promise to improve Canadians' ability to gain insights from economically and socially important large-scale datasets in domains from business intelligence to health informatics. Blending the interactive digital media and artificial intelligence themes of Ontario's Open for Business Agenda, this research directly addresses government priorities.

视觉分析是将数据处理和信息可视化相结合以支持人们理解数据的科学。它的力量来自于让计算机做适合其能力的工作，例如计算和组织数据，而人类分析师则做推理，证据收集和决策。长期以来，这种合作的计算方面的重点一直是数据挖掘、布局和显示大量信息。引导分析过程主要是人类分析师的领域。我的研究将研究软件如何为人类分析师提供在探索数据集时应采取的步骤。很多人际交流都是通过内隐的方式进行的--肢体语言、语调、面部表情和用词.我们的外显交流是由这些内隐线索支持的。内隐线索提供了很多机会来提高我们使用计算机系统的工作效率。例如，通过监视用户注视图表中的一系列点的注视，分析系统可以建议可能适合用户兴趣的附加未探索项目，而无需明确询问，并且无需用户明确陈述他们的兴趣。这项研究将探索来自虚拟现实中的笔、触摸、手势和眼睛凝视的隐含线索。自动突出显示或隐藏数据会带来算法偏差的风险。但在没有指导的情况下给分析师增加负担同样是不合适的，因为这项工作更加困难，而且重要的数据可能会被遗漏。我将研究这种权衡：控制应该在哪里，什么样的指导是可能的和有帮助的，什么时候应该提供指导？ 文本分析将是调查的主要测试平台。每天都有数十亿页的文本以多种语言产生：电子邮件、新闻、博客、评论、论坛、学术文章和商业报告。这项研究将产生一个文本的互动工具，它结合了隐含的互动，复杂的语言分析和可视化来揭示隐藏的信息，如主题，趋势和情感。我设想引入新的方式来浏览和使用在线文本集合，通过丰富和集中分析和阅读的行为来减轻信息过载的负担。这项研究将引入新的可视化分析实践，实现分析师和算法的更紧密耦合。12名学员将接受备受追捧的数据科学技能的专业培训。这些成果有望提高加拿大人从商业智能到健康信息学等领域具有经济和社会重要性的大型数据集中获得见解的能力。融合互动数字媒体和人工智能的主题安大略的开放商业议程，这项研究直接解决政府的优先事项。