Three-dimensional visualization, interactive analysis and contextual mapping of s

描述（由申请人提供）：该项目正在开发第一个软件，以提供组合时间和地理空间中的健康结果的3D可视化，允许在同一场景中以多个空间和时间尺度显示健康数据，从而充分利用基本上是三维的人类视觉感知。这种可视化分析环境还将提供一个界面，用户可以：1）与系统动态交互（例如，使用数据查询，特征突出显示，3D场景旋转），以及2）通过使用包含本地上下文线索的背景地图（例如，具有主要城市和高速公路名称的正射影像，以增强位置感），将结果（例如癌症负担）置于上下文中。该可视化模块将被集成到TerraSeer空间-时间智能系统”（STIS”）中，提供一套全面的工具，用于量化与个体->邻里->区域相对应的空间变化嵌套尺度，使用基于区域和个人水平的数据绘制疾病发病率，统计分析（例如聚类检测、回归），并检测其在空间和时间上的变化。还将开发一个基于网络的绘图和数据可视化系统，以方便公共卫生部门使用这一新技术，并增加研究的影响。该项目将实现四个目标：1。进行需求分析，以确定要纳入软件的方法和功能。2.探索使用三维显示和视觉分析来表示和探索性数据分析健康结果及其与空间和时间中假定因素的关系。3.基于研究结果构建和测试一整套功能，并将其整合到Biomedware的时空可视化和分析技术（桌面和基于Web的应用程序）中，这将允许使用Google Earth产品轻松导入和导出数据层。4.应用该软件和方法来证明该方法及其独特的优势，用于调查诊断和生存数据时癌症阶段的地理和时间变化，以及探索健康结果与潜在因素之间的关系，如社会经济条件和接近筛查设施。这些技术，科学和商业创新将彻底改变我们在多个空间尺度和跨时间可视化和解释癌症发病率变化的能力，这将有助于为因果关系或影响生存或发病率的风险因素的深入个体研究产生假设，并建立有针对性的癌症控制干预措施的基本原理，包括考虑卫生服务需求，以及筛查和诊断检测的资源分配。绘制准确反映癌症负担并将其置于特定背景下的疾病分布图，将极大地促进当地社区对这些分布图的解读，并促使他们参与解决健康差距问题。 公共卫生相关性：这项研究的实质性好处是它在访问和链接不同的个人水平和基于人群的数据，其次是三维可视化，交互式分析和癌症发病率和死亡率的变化在多个空间尺度和跨时间的上下文映射的效用。本项目中开发的方法将有助于为因果关系或影响生存率或发病率的风险因素的深入个体研究产生假设，并建立有针对性的癌症控制干预措施的基本原理，包括考虑卫生服务需求以及筛查和诊断测试的资源分配。将这些创新的可视化和绘图工具纳入TerraSeer空间-时间情报系统，沿着开发一个基于网络的应用程序，将有助于公共卫生部门更有效地向当地社区传播其分析结果，并制定参与性战略，促进将研究结果转化为干预措施，以缓解所发现的问题。

DESCRIPTION (provided by applicant): This project is developing the first software to offer 3D visualization of health outcomes in a combined time and geography space, allowing the display of health data at multiple spatial and temporal scales within the same scene and thus taking full advantage of human visual perception that is fundamentally three dimensional. This visualization analytics environment will also provide an interface where the user can: 1) interact dynamically with the system (e.g. using data query, feature highlights, 3D scene rotation) and 2) contextualize the results, such as cancer burden, through the use of background maps that incorporate cues to the local context (e.g. orthophoto with names of major cities and highways to enhance the sense of place). This visualization module will be integrated into TerraSeer Space-Time Intelligence System" (STIS"), providing a comprehensive suite of tools for quantifying nested scales of spatial variation corresponding to individual -> neighborhood -> region, mapping disease incidence using both area-based and individual-level data, statistical analysis (e.g. cluster detection, regression) of health disparities, and detection of their changes in both space and time. A web- based mapping and data visualization system will also be developed to facilitate the use of this new technology by public health departments and increase the impact of the research. This project will accomplish four aims: 1. Conduct a requirements analysis to identify methods and functionality to incorporate into the software. 2. Explore the use of three-dimensional display and visual analytics for the representation and exploratory data analysis of health outcomes and their relationship to putative factors in both space and time. 3. Build and test a complete set of functionalities based on the research results, and incorporate them into Biomedware's space-time visualization and analysis technology (desktop and web-based applications) that will allow easy import and export of data layers with Google Earth Products. 4. Apply the software and methods to demonstrate the approach and its unique benefits for the investigation of geographic and temporal variations in cancer stage at diagnosis and survival data, and the exploration of relationships between health outcomes and potential factors, such as socio-economic conditions and proximity to screening facilities. These technologic, scientific and commercial innovations will revolutionize our ability to visualize and interpret variation in cancer incidence at multiple spatial scales and across time, which will help generating hypotheses for in depth individual studies of risk factors that are causal, or impact survival or morbidity, and establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. The creation of disease maps that accurately represent and contextualize the cancer burden will greatly facilitate their interpretation by local communities and engage their participation in addressing health disparities. PUBLIC HEALTH RELEVANCE: The substantial benefit of this research is its utility in accessing and linking diverse individual-level and population-based data, followed by the three-dimensional visualization, interactive analysis and contextual mapping of variation in cancer incidence and mortality at multiple spatial scales and across time. The methods developed in this project will help generating hypotheses for in depth individual studies of risk factors that are causal, or impact survival or morbidity, and establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. The incorporation of these innovative visualization and mapping tools into TerraSeer Space-Time Intelligence System" (STIS"), along with the development of a Web-based application, will help public health departments communicate more effectively the results of their analysis to local communities and develop participatory strategies to facilitate the translation of research results into interventions to alleviate the problems identified.