Pan-American Advanced Studies Institute on Methods in Computational Discovery for Multidimensional Problem Solving; Universidad del Valle, Guatemala, July 2013

由美国国家科学基金会（NSF）和美国能源部（DOE）联合支持的泛美高级研究所（PASI）奖将于2013年7月在危地马拉的瓦莱大学（Universidad del Valle）举行。PASI由伊利诺伊大学厄巴纳-香槟分校传播系教授Marshall S. Poole博士组织，旨在向初级研究人员介绍基于计算的发现（CBD）方法。在寻找重大问题（如生物多样性、自然系统建模、水生态等）的解决方案时，自然科学和社会科学以及人文和艺术领域的研究人员正在生成大量和/或高度复杂的数据集，这些数据集远远超出了人类在没有复杂技术增强的情况下感知或分析的能力。CBD允许研究人员收集、转换和分析来自各种来源的数据，包括传感器、视频档案、望远镜和超级计算机等。因此，获得先进的计算资源以及数据采集、管理、转换、可视化、分析和保存方面的复杂技能受到研究人员的高度重视。例如，复杂的可视化工具和技术增强了人类对极端、复杂和/或抽象数据集的理解，使其更容易看到模式和关系，并形成或测试假设。该研究所将专注于CBD的技术和分析方法，并帮助研究人员将这些方法应用于他们自己的研究。主要目标是(1)扩展参与者对高性能计算（HPC）和支持涉及大量或复杂数据集的CBD的专业工具和技术的知识；(2)提供使用易于访问的桌面开源工具探索大型复杂数据集的实践经验；(3)将研究人员从代表性不足的群体引入CBD领域；(4)培养新的大学伙伴关系，以促进演讲者和与会者之间的国内和国际合作研究。此外，该小组还将通过网页向更广泛的受众提供关于该小组审议情况的最新信息，以传播会议的结果和报告。

This Pan-American Advanced Studies Institutes (PASI) award, jointly supported by the NSF and the Department of Energy (DOE), will take place July 2013 at the Universidad del Valle in Guatemala. Organized by Dr. Marshall S. Poole, Professor in the Department of Communications at the University of Illinois, Urbana-Champaign, the PASI aims to introduce junior researchers to methods in computation-based discovery (CBD). In searching for solutions to major problems (e.g., biodiversity, modeling of natural systems, water ecology, and others), researchers across the natural and social sciences as well as the humanities and arts are generating massive and/or highly complex data sets that extend well-beyond humans' capacities to perceive or analyze without sophisticated technological augmentation. CBD allows researchers to gather, transform, and analyze data from a range of sources, including, for example, sensors, video archives, telescopes, and supercomputers. Thus, access to advanced computational resources and also to sophisticated skills in data acquisition, management, transformation, visualization, analytics, and preservation, are highly valued by researchers. For example, sophisticated visualization tools and techniques enhance human understanding of extreme, complex and/or abstract data sets, making it easier to see patterns and relationships and to form or test hypotheses.The Institute will focus on CBD technical and analytical methods and help investigators apply these to their own research. Key goals are to (1) expand participants' knowledge of high performance computing (HPC) and specialized tools and techniques that support CBD involving massive or complex data sets; (2) provide hands-on experience in exploring large and complex data sets using easily accessible desktop open source tools; (3) bring researchers from underrepresented populations into the CBD field; and (4) foster new collegial partnerships that stimulate both national and international co-operative research among the presenters and attendees. In addition, the PASI will also provide up-to-date information on the deliberations of the PASI to a wider audience through a web page to disseminate results and reports of the meeting.