Collaborative Research: CyberSEES:Type 2: Framework to Advance Climate, Economics, and Impact Investigations with Information Technology (FACE-IT)

与气候变化和粮食安全有关的问题需要了解自然世界和人类社会之间长期的相互作用。 了解气候变化，其对自然世界和社会的影响，以及社会反应中固有的权衡，需要在学术领域进行前所未有的合作。关于预期未来气候、土壤特征、经济活动、历史天气、人口和土地覆盖的新数据来源为这种合作提供了潜在的基础。 需要新的方法来在社区内和社区之间共享数据以及用于生成、合成和分析数据的软件。研究人员、合作者和社区在围绕数据进行合作时遇到的极端困难阻碍了这些研究挑战的进展。数据格式的多样性、计算工具的不足、共享数据和程序的困难、缺乏对亲社会行为的激励以及大量数据都是技术障碍。 FACE-IT项目采用网络基础设施综合方法，以推进人类和环境系统对气候变化的脆弱性、影响、缓解和适应的表征。 利用现有的研究网络基础设施，该项目将创建一个功能齐全的FACE-IT平台原型，具有新的功能，用于整合，组织，管理，分析和使用大量不同的数据。 该项目团队将与两个不同的跨学科社区合作，创建特定的FACE-IT平台，这将推动他们的研究，并使FACE-IT方法的效用的规模评估。人类面临的许多重要和具有挑战性的问题发生在社会，物理，生物和计算科学的交叉点。所提出的方法和途径具有普遍适用性，以促进跨不同社区的研究信息的使用。

Issues relating to climate change and food security require an understanding of the interaction between the natural world and human society over long time scales. Understanding climate change, its impacts on the natural world and society, and the tradeoffs inherent in societal responses demands an unprecedented degree of cooperation across academic fields. New data sources on expected future climate, soil characteristics, economic activity, historical weather, population, and land cover, provide a potential basis for this cooperation. New methods are needed for sharing within and across communities not only data but the software used to generate, synthesize, and analyze it. Progress on these research challenges is hindered by the extreme difficulties that researchers, collaborators and the community experience when they collaborate around data. Multiplicity of data formats, inadequate computational tools, difficulty in sharing data and programs, lack of incentives for pro-social behavior, and large data volumes are among the technology barriers. The FACE-IT project employs an integrated approach to cyberinfrastructure to advance the characterization of vulnerabilities, impacts, mitigation, and adaptation to climate change in human and environmental systems. Leveraging existing research cyberinfrastructure the project will create a full-featured FACE-IT Platform prototype with new capabilities for ingesting, organizing, managing, analyzing and using large quantities of diverse data. The project team will collaborate with two distinct interdisciplinary communities to create specific FACE-IT Instances that will both advance their research and enable at-scale evaluation of the utility of the FACE-IT approach.Many important and challenging problems facing humankind occur at the intersection of the social, physical, biological, and computational sciences. The proposed methods and approaches have general applicability for advancing the use of research information across diverse communities.