From Big Biological Data to Tangible Insights: Designing tangible and multi-display interactions to support data analysis and model building in the biology domain

本研究计划的目标是设计、开发和评估有形和多显示接口，以促进生物领域内的协作数据分析和模型构建，特别是在处理大型和异构数据集方面。我们提出，结合视觉和运动技能的灵活视觉表示可以使人类更深入地探索和解释，并发现数据的意外特征，从而增强分析。这是基于越来越多的具身认知的证据，这些证据强调了感知和运动系统在我们的认知过程中的重要性。在有形和具体化交互（TEI）领域，人们对使用有形交互和大型交互界面来促进围绕大型数据集的问题解决和发现越来越感兴趣。通过将运动和感知系统结合在一起，有形界面和桌面界面已被证明是支持协作、分布式认知和反思的有效手段。尽管这些接口显示出处理大型生物数据集的潜在好处，但仍然存在许多挑战，包括用户的多样性、数据的异质性和数据集的规模。该项目建立在与瑞尔森大学研究DNA复制及其与癌症关系的生物学研究人员的跨学科合作基础上。他们的工作使用显微镜和DNA测序数据集，目的是识别和模拟DNA分叉崩溃的结构和影响，并预测其对癌症发展的影响。从TEI的角度来看，这个问题特别有趣，因为它体现了上述挑战：大型且异构的数据集，以及具有不同背景的多个研究人员。我们建议研究控制和表示的哪种组合可以最有效地支持该领域的协作数据分析和模型构建任务。该研究项目的贡献包括进一步加深我们对有形和多显示器交互技术如何支持生物学研究实践的理解；针对特定生物问题的界面原型的设计、开发和评估；制定设计指南，帮助TEI设计师和研究人员建立支持生物研究和发现的系统。该计划将通过解决可以从TEI技术中受益的问题来推进TEI领域，但由于其规模和复杂性而没有得到重视。更广泛地说，对大型复杂数据集的解释对加拿大和全球的科学进步变得越来越重要，该计划将有助于提供工具和技术，促进健康和医学领域中数据密集型领域的问题解决。

The goal of this research program is to design, develop, and evaluate tangible and multi-display interfaces that facilitate collaborative data analysis and model building within the biological domain, specifically in dealing with large and heterogeneous datasets. We propose that flexible visual representations that engage both visual and motor skills can enhance analyses by enabling humans to explore and interpret more deeply, and to discover unexpected features of their data. This is based on growing evidence from embodied cognition which underscores the importance of the perceptual and motor systems in our cognitive processes. In the area of tangible and embodied interaction (TEI), there has been increasing interest in using tangible interactions and large interactive surfaces to facilitate problem solving and discovery around large datasets. By engaging the motor and perceptual systems together, tangible and tabletop interfaces have proven to be an effective means of supporting collaboration, distributed cognition, and reflection. Although these interfaces show potential benefits for working with large biological datasets, there remain numerous challenges, including the diversity of users, the heterogeneity of the data, and the scale of the datasets. This program builds on an interdisciplinary collaboration with biology researchers at Ryerson University who study DNA replication and its relationship to cancer. Their work employs microscopy and DNA sequencing datasets, with the aim of identifying and modeling the structure and effects of DNA fork collapse, and of predicting its effects on the development of cancer. This problem is especially interesting from a TEI perspective as it exemplifies the challenges described above: large and heterogeneous datasets, and multiple researchers with diverse backgrounds. We propose to investigate what combinations of control and representation can most effectively support collaborative data analysis and model building tasks in this area. The contributions of the research program include furthering our understanding of how tangible and multi-display interaction techniques can support biological research practices; the design, development and evaluation of interface prototypes for specific biological problems; and the formulation of design guidelines that can aid TEI designers and researchers in building systems that support biological research and discovery. The program will advance the field of TEI by tackling problems that can benefit from TEI techniques but have not been given significant attention due to their scale and complexity. More broadly, the interpretation of large complex datasets is becoming increasingly critical to scientific advancement in Canada and globally, and this program will help to provide tools and techniques that can facilitate problem solving in data-intense areas within the health and medical domains.