CAREER: Ubilytics: Harnessing Existing Device Ecosystems for Anywhere Sensemaking

这一研究项目解决的根本问题是，我们如何利用环境中现有的网络设备生态系统，随时随地理解和利用海量、异质和多规模的数据。将这些设备组装到统一的传感环境中，将能够在现场进行深入分析。例如，管理科学实验室笔记本中的异类数据，用例子、手册和视频支撑本科生课堂学习，以及通过将事实、发现和证据联系起来支持警方调查。在更高的层面上，这一概念将通过支持设计与创意、指挥与控制以及科学发现等领域来刺激我们的数字经济。然而，尽管可以随时访问无数手持设备以及那些集成在我们物理环境中的设备，但目前每个单独的设备都被设计为关注的焦点，不能轻松地与其他设备组合以提高工作效率，并且计算和存储资源有限。该项目引入了一种名为普适分析(Ubilytics)的综合新方法，用于将这些无处不在的数字设备整合到统一环境中，以便随时随地分析和感知数据。Ubilytics基于三个原则，利用人机交互、视觉分析和普适计算，以及分布式、扩展和体现认知的综合。首先，通用交互需要设计一种交互模型，该模型将多个设备组合成一个整体的分布式接口，透明地桥接多个设备、表面甚至物理对象，并将交互与各种数据类型统一起来。其次，必须创建灵活的视觉结构，以便生成适应不同设备尺寸、分辨率、视角和距离的表示，支持以自我为中心和以世界为中心的配置中的空间和布局管理，并且可以利用新颖和适当的显示器进行输出。第三，必须通过发现、合并和同步异类设备的方法来实现高效的分布式架构，并支持通用组件模型以促进重用，将成本高昂的计算卸载到云中，并将ubilytics环境网格化以进行协作。轰动效应通常被归因于专业分析师从观察到的数据中找到意义，但这项研究将全面审视普通用户和专家用户、专用和移动环境中的感知效应，以及大规模和小规模数据集。因此，这项工作将通过关注三个范例领域而造福社会：(1)科学发现，(2)课堂学习，(3)警察调查。它还将通过将研究整合到本科编程课程中来促进发现和理解，该课程用作在ubilytics环境中学习的试验台。另一个目标是通过参加女性工程学项目以及在暑期研究实习期间指导少数族裔本科生，扩大代表不足群体的参与。结果、软件和文档将在开放源码和知识共享许可下发布。

This research project addresses the fundamental question of how we can use the existing ecosystem of networked devices in our surroundings to make sense of and exploit massive, heterogeneous, and multi-scale data anywhere and at any time. Assembling these devices into unified sensemaking environments would enable deep analysis in the field. Examples include managing heterogeneous data in scientific lab notebooks, scaffolding undergraduate classroom learning with examples, manuals, and videos, and supporting police investigation by linking facts, findings, and evidence. On a higher level, this concept would stimulate our digital economy by supporting fields such as design and creativity, command and control, and scientific discovery. However, despite this ready access to a myriad of handheld devices as well as those integrated in our physical environments, each individual device is currently designed to be the focus of attention, cannot easily be combined with other devices to improve productivity, and has limited computational and storage resources. This project introduces a comprehensive new approach called ubiquitous analytics (ubilytics) for harnessing these ever-present digital devices into unified environments for anywhere analysis and sensemaking of data.Ubilytics draws on human-computer interaction, visual analytics, and ubiquitous computing as well as a synthesis of distributed, extended, and embodied cognition, based on three principles. First, universal interaction requires designing an interaction model that combines several devices into a holistic distributed interface, transparently bridges multiple devices, surfaces, and even physical objects, and unifies interaction with various data types. Second, flexible visual structures must be created in order to generate representations that adapt to varying device dimensions, resolution, viewing angle, and distance, support space and layout management in ego-centric and world-centric configurations, and can utilize both novel and appropriated displays for output. Third, efficient distributed architecture must be achieved through methods for discovering, merging, and synchronizing heterogeneous devices with support for a generic component model to facilitate reuse, offloading costly computation into the cloud, and meshing ubilytics environments for collaboration. Sensemaking is often attributed to professional analysts finding meaning from observed data, but this research will take a comprehensive view of sensemaking for both casual and expert users, in both dedicated and mobile settings, and with both large-scale and small-scale datasets. This work will therefore benefit society by focusing on three example domains: (1) scientific discovery, (2) classroom learning, and (3) police investigation. It will also advance discovery and understanding by integrating the research in an undergraduate programming course used as a testbed for learning in ubilytics environments. Another goal is to broaden participation of underrepresented groups by engaging in a women in engineering program as well as by mentoring minority undergraduate students during summer research internships. Results, software, and documentation will be disseminated under Open Source and Creative Commons licenses.