INSPIRE: Automating Reasoning in Interpreting Climate Records of the Past

该INSPIRE奖由计算机和信息科学理事会信息和智能系统司的信息集成和信息学计划，地球科学理事会海洋科学司的海洋地质学和地球物理学计划，北极科学司的北极自然科学计划和极地计划办公室南极科学司的南极冰川学计划共同资助，和网络基础设施办公室分析冰或沉积物岩心等古气候记录的关键第一步是建立年龄模型，将岩心的深度与该点物质的日历年龄联系起来。年龄模型构建的推理过程复杂、微妙，而且科学要求很高，因为控制物质随时间积累速率的过程，以及在形成和取样之间影响核心的过程，都是未知的。地球科学家通过将地核视为犯罪现场来处理这个问题，并提出这样的问题：“什么物理和化学过程可能产生这种情况，这对时间轴有什么影响？“然而，可能性的数量之多，加上目前可用的和不断收集的气候学数据的数量和复杂性，严重限制了这些调查的范围。这个项目的目标就是要消除这个障碍。这项研究将产生一个名为CScibox的集成软件工具，它使用自动推理技术来帮助科学家分析冰和沉积物芯。它采用网络基础设施，在科学家的桌面上提供强大，直观的工具，同时充分利用现代数据和计算密集型计算和网络基础设施-包括基于工作流的计算，并行执行，分布式系统，集群机器和云。CScibox不仅将提高单个地球科学家分析单个岩心的能力;它有可能通过促进快速，可重复的分析和综合数据档案中各种原始数据中的信息来改变古气候学领域，以促进理解和改进科学决策。这将对社会产生广泛的影响，使科学家能够更深入地了解各种因素在复杂关系中的作用，这些关系产生了当今环境变化模型中使用的地球气候地质记录。该项目还具有广泛的教育影响。参与CSibox开发和实施的学生将培养跨学科研究的技能，并将学习如何在具有挑战性的科学背景下应用计算方法，该背景尚未从信息技术的发展中获益。CScibox设计为易于安装和使用;有关源代码、文档和使用示例，请参阅项目网站（http：//www.cs.colorado.edu/cscizb/cscience.html）。未来的步骤包括将工作扩展到其他古气候数据，与地球科学家合作，使用户界面尽可能直观，并在地球科学会议上举办演示和研讨会，以教育该社区了解该工具可以做什么以及如何使用它。

This INSPIRE award is jointly funded by the Information Integration and Informatics Program in the Information and Intelligent Systems Division of the Computer and Information Sciences Directorate, the Marine Geology and Geophysics Program in the Ocean Sciences Division of the Geosciences Directorate, the Arctic Natural Sciences Program in the Arctic Sciences Division and the Antarctic Glaciology Program in the Antarctic Sciences Division in the Office of Polar Programs, and the Office of Cyberinfrastructure. The critical first step in the analysis of paleoclimate records like ice or sediment cores is the construction of an age model, which relates the depth in a core to the calendar age of the material at that point. The reasoning involved in age-model construction is complex, subtle, and scientifically demanding because the processes that control the rate of material accumulation over time, and that affect the core between formation and sampling, are unknown. Geoscientists approach this problem by treating the core like a crime scene and asking the question: "What physical and chemical processes could have produced this situation, and what does that say about the timeline?" However, the sheer number of possibilities, coupled with the volume and complexity of the climatology data that is currently available and is continually collected, severely limit the scope of these investigations. The goal of this project is to remove this roadblock. This research will lead to an integrated software tool called CScibox, that uses automated reasoning techniques to help scientists analyze ice and sediment cores. It employs a cyberinfrastructure that provides powerful, intuitive tools on a scientist's desktop while taking full advantage of modern data- and computation-intensive computing and networking infrastructure -- including workflow-based computation, parallel execution, distributed systems, cluster machines and the cloud. CScibox will not only improve the ability of individual geoscientists analyze single cores; it has the potential to transform the field of paleoclimatology by facilitating rapid, reproducible analysis and synthesis of the information in the diverse collections of raw data available in data archives to foster understanding and improved scientific decision making. This will have broad impacts for society by allowing scientists to develop deeper insights into the roles of various factors in the complex relationships that give rise to geological records of the earth's climate that are used in today's models of environmental change. This project also has a broad educational impact. Students involved in the development and implementation of CScibox will develop skills in interdisciplinary research and will learn how to apply computational methodology in a challenging scientific context that has not yet significantly benefitted from developments in information technology. CScibox is designed to be easy to install and use; see the project web site (http://www.cs.colorado.edu/~lizb/cscience.html) for source code, documentation, and examples of its use. Future steps include extending the work to other paleoclimate data, working with geoscientists to make the user interface as intuitive as possible, and holding demos and workshops at geosciences conferences to educate that community about what the tool can do and how to use it.