Spatial Analysis Across Biological Disciplines

亚利桑那州州立大学被授予开发模式分析，空间统计和地理注释2.0（PASSaGE 2）软件的赠款，用于探索，发现和分析生物（和其他）数据的空间模式。空间分析是科学探究的基本组成部分，包括生态学，进化和环境科学，流行病学，地质学，地理学和数学。基因组测序、全球定位系统和遥感方面的最新技术进步导致可用于分析的空间明确数据集的数量和规模迅速扩大。这些新数据将空间分析的范围推进到更广泛的人类活动中，但也迅速超越了传统空间分析软件和方法的能力。通过增强PASSaGE 1的优势，并扩展、调整和实施来自各种研究学科的空间分析现有计算算法，PASSaGE 2将支持多种数据类型的导入和分析，包括Unicode和ASCII文本、电子表格文件、图像和常见的地理信息系统数据格式;尽可能消除对特定算法数据维度的限制;通过扩展现有方法和开发新技术，允许灵活的协变量和多变量分析;提高图形输出的灵活性和质量，以便更好地直观地表示数据和结果，并制作可供出版的图形。该项目的更广泛影响是通过提供免费提供的易于使用的工具，使来自世界各地的研究人员和学生能够轻松进行和探索复杂的空间分析，从而加强科学研究和教育基础设施。

Arizona State University is awarded a grant to develop the Pattern Analysis, Spatial Statistics, and Geographic Exegesis 2.0 (PASSaGE 2) software for exploring, discovering, and analyzing spatial pattern of biological (and other) data. Spatial analysis is a fundamental part of scientific inquiry, including ecological, evolutionary and environmental science, epidemiology, geology, geography, and mathematics. Recent technological advances in genome sequencing, global positioning systems, and remote sensing have led to a rapid expansion of the number and size of spatially explicit datasets available for analysis. These new data have advanced the scope of spatial analysis to an even broader variety of human endeavors, but have also rapidly outpaced the capabilities of traditional spatial analytic software and methods. By building off strengths of PASSaGE 1 and expanding, adapting, and implementing existing computational algorithms for spatial analysis derived from a variety of research disciplines, PASSaGE 2 will support the import and analysis of numerous data types, including Unicode and ASCII text, spreadsheet files, images, and common Geographic Information Systems data formats; eliminate limits to data dimensionality for specific algorithms whenever possible; allow for flexible covariate and multivariate analysis through the extension of existing methods as well as the development of novel techniques; and increase the flexibility and quality of its graphical output to allow better visual representation of data and results and for the production of publication ready graphics. The broader impacts of this project are to enhance the scientific research and educational infrastructure by providing freely available, easy-to-use tools that allow researchers and students from around the world to easily conduct and explore complicated spatial analyses.