Engineering Immersive Analytics Applications

工程沉浸式分析应用***拟议研究计划的长期目标是研究允许开发人员有效地为大型多维数据集构建复杂沉浸式分析（IA）应用程序并将其嵌入其他软件应用程序的过程。该计划将解决沉浸式分析应用程序的软件工程挑战，并开发支持开发人员创建沉浸式分析应用程序的指南和工具。***沉浸式分析是一个相对较新的研究领域，目前的应用通常是由沉浸式技术和分析技术的专家创建的。机器学习和数据挖掘技术允许分析数据和检测模式。虚拟现实方法允许将分析结果放置在虚拟空间中，而增强现实技术则在现实世界的物理位置显示虚拟对象。沉浸式分析旨在为复杂数据集创建多维虚拟表示，并将其嵌入虚拟或物理空间。通过将分析结果置于沉浸式环境中，我们可以将人类带入决策过程，并通过使用空间认知和邻近交互来提高对多维数据集的理解，从而潜在地增强决策过程。虽然沉浸式分析具有很高的潜力，但我们还不清楚它在哪些应用场景和数据特征上改善了人类的决策。计划中的一个工作流将解决这个问题，并从经验上研究沉浸式环境中哪种类型的数据集可以提高理解和任务性能。***拟议项目的第二项工作将开发和集成沉浸式分析工具，为希望快速创建创新沉浸式分析解决方案的研究人员和开发人员提供开源工具包。这些工具将提供用于将维度映射到物理维度的api。它们还将提供动画功能，以在第四维度的基础上随时间改变3D模型。***第三个工作流将研究构建IA应用程序的工程流程。工程IA应用是一个重要的研究领域，因为大数据分析的快速发展趋势正在与将数据融入现实环境的新方法相结合，从而需要开发此类应用程序的工程方法，使具有一般软件开发背景的软件开发人员能够创建IA应用程序并将其与现有工具和流程集成。***专注于针对大数据的IA指南，使得本研究的结果对各个行业都有效。我们期望加拿大有大量的受体能力从拟议的方案中受益。

Engineering Immersive Analytics Applications***The long-term goal of the proposed research program is to investigate processes that allow developers to effectively build complex immersive analytics (IA) applications for large multi-dimensional data sets and embed these into other software applications. The program will address the software engineering challenges for immersive analytics applications and develop guidelines and tools that support developers in creating immersive analytics applications. ***The field of immersive analytics is a relatively new research area and current applications are usually created by experts in immersive technologies as well as analytics techniques. Machine learning and data mining techniques allow to analyze data and detect patterns. Virtual reality approaches allow to place analysis results in virtual spaces while augmented reality techniques display virtual objects in physical real-world locations. Immersive analytics aims at creating multi-dimensional virtual representations of complex data sets and embed them in virtual or physical spaces. By placing analysis results in immersive environments, we can bring humans into decision-making processes and potentially enhancing them by using spatial cognition and proxemic interactions to improve understanding of multi-dimensional data sets. ***While anecdotally immersive analytics has a high potential, we really do not yet understand for which application scenarios and data characteristics it is improving human decision making. One stream of work in the proposed program will address this question and study empirically for which kind of data sets an immersive environment enhances understanding and task performance. ***A second stream of work of the proposed program will develop and integrate tools for immersive analytics, providing an open source toolkit for researchers and developers that want to quickly create innovative immersive analytics solutions for their problems. The tools will provide APIs for mapping dimensions to physical dimensions. They also will provide animation capabilities to change the 3D model over time based on a fourth dimension. ***The third stream of work will investigate engineering processes for building IA applications. Engineering IA applications is an important research area as the fast-growing trend towards big-data analysis is merging with new approaches for immersing data in a real-world context, resulting in a need for engineering approaches for the development of such applications that enable software developers with a general software development background to create IA applications and integrate them with existing tools and processes. ***The focus on guidelines for IA aimed for big data makes the results of this research effective for various industries.We expect that Canada has substantial receptor capacity to benefit from the proposed program.