INSPIRE: Automating Reasoning in Interpreting Climate Records of the Past

该INSPIRE奖由计算机与信息科学局信息与智能系统部的信息集成与信息学项目、地球科学局海洋科学部的海洋地质与地球物理项目、北极科学部的北极自然科学项目和极地项目办公室南极科学部的南极冰原学项目共同资助。以及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，该模型将岩心的深度与该点材料的日历年龄联系起来。年龄模型构建的推理是复杂的、微妙的，而且在科学上要求很高，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岩心的过程，都是未知的。地球科学家通过将地核视为犯罪现场来解决这个问题，并提出这样的问题：“什么样的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，可能性的绝对数量，加上目前可获得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消除这个障碍。这项研究将导致一个名为CScibox的集成软件工具，它使用自动推理技术帮助科学家分析冰和沉积物岩心。它采用的网络基础设施可以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不仅提高了单个地球科学家分析单个岩心的能力；它有可能改变古气候学领域，促进对数据档案中可获得的各种原始数据中的信息进行快速、可重复的分析和综合，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，这些关系产生了地球气候的地质记录，这些记录被用于当今的环境变化模型。这个项目也有广泛的教育影响。参与CScibox开发和实施的学生将培养跨学科研究的技能，并将学习如何在尚未从信息技术发展中显著受益的具有挑战性的科学背景下应用计算方法。CScibox设计为易于安装和使用；请参阅项目网站（http://www.cs.colorado.edu/~lizb/cscience.html）获取源代码、文档和使用示例。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行演示和研讨会，向社区宣传该工具的功能以及如何使用它。

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.