CDI-Type II: GLOBE: Evolving New Global Workflows for Land Change Science

土地变化科学是一个新兴的研究领域，旨在了解人类系统与陆地生物圈、大气层和其他地球系统之间通过人类对土地的利用而产生的相互作用。为了更好地量化、预测、调解和适应全球气候变化、生物多样性丧失以及土地利用和土地覆盖变化的其他后果，需要在LCS方面取得进展。尽管广泛的社会和自然科学家做出了巨大努力，但跨尺度综合推进LCS所需的多学科观察、模型和人类与自然耦合系统（CHNS）理论尚未出现。一个主要的障碍是在全球一体化和综合地方和区域的ChANS案例研究方面的巨大挑战。该项目将通过地球仪加速土地变化科学新的全球工作流程的出现：GLOBE是一个结合定量实时全球相关性评估、地理可视化、社会计算结构和机器学习算法的在线协作环境。这将与国际LCS机构和专家合作完成，使研究人员和机构能够通过使用机器学习，高级可视化，语义分析和社交网络的组合将这些与人类和环境变量的全球数据集相结合，快速共享，比较和综合本地和区域研究。该项目有四个核心目标，将通过以下三项综合活动来实现：目标1：创建一个在线协作环境，利用实时全球相关性分析、地理可视化和社会计算知识生成，以生成和共享土地变化科学新的全球工作流程。了解如何围绕结构化和非正式的科学工作流程构建有效的社交媒体工具。目标3：开发评估方法和指标，并使用它们来证明基于工作流的社交媒体工具在科学家测试LCS假设的背景下的效用。目标4：利用地球仪来描述和优化LCS中的全局知识生成。为了实现这些目标，该团队将参与以下活动：活动1：为地球仪开发社会计算基础设施。活动2：将地球仪建立为社会计算知识生成的手段。描述、分享和优化知识生成工作流程，以便在CHANS研究和数据收集过程中进行全球综合和协作。活动3：检验假设并确定新的研究机会。为了了解地球系统中人为的全球变化，科学家必须从当地和区域的观测中进行全球归纳。该项目将使关于人类与地球系统相互作用的性质的基本假设更容易用科学方法检验，从而使土地变化科学和理论取得重大进展。此外，该项目将使计算科学和社会科学参与开发用于科学合作和数据综合的交互式在线工具，这将有助于确定LCS科学的知识差距。这些工具将导致以新的方式对全球、区域和地方各级的土地变化过程观测和模型进行可视化、交流、连接、比较和综合。地球仪在使用中的实证调查将促进我们对科学合作的理解更普遍。更广泛的影响这个项目将发展，加强和支持跨广泛的科学学科的长期研究合作。它将支持经验丰富的教师，博士后研究人员，研究生和本科生的跨学科合作的教育和技能建设。该项目将设计、主持和传播用于跨尺度数据和知识共享、综合和设计具有全球代表性的观测系统的先进工具。通过创造一个分享和整合社会、生物和地球物理科学领域的地方知识、数据和想法的新环境，土地变化科学将有更大的潜力为地球系统的可持续管理提供信息。

This project focuses on Land Change Science (LCS).Land Change Science is an emerging field of study, aimed at understanding interactions among human systems and the terrestrial biosphere, atmosphere and other Earth systems as mediated through human use of land. Advances in LCS are needed to better quantify, predict, mediate, and adapt to global climate change, biodiversity loss, and other consequences of land use and land cover change.Despite vigorous efforts by a broad array of social and natural scientists, the cross-scale synthesis of multidisciplinary observations, models and theories on coupled human and natural systems (CHANS) that are required to advance LCS has yet to emerge. A major obstacle is the tremendous challenge in global integration and synthesis of local and regional CHANS case studies. This project will accelerate the emergence of new global workflows in land change science through GLOBE: an online collaboration environment combining quantitative real-time global relevance assessment, geovisualization, social-computational structures and machine learning algorithms. This will be accomplished in collaboration with international LCS institutions and experts, enabling researchers and institutions to rapidly share, compare, and synthesize local and regional studies by combining these with global datasets for human and environmental variables using a combination of machine learning, advanced visualization, semantic analysis and social networking. The project has four core objectives that will be achieved through three integrated activities, as follows: Objective 1: Create an online collaboration environment leveraging real-time global relevance analysis, geovisualization and social-computational knowledge generation towards the generation and sharing of new global workflows for land change science.Objective 2: Understand how to build effective social media tools organized around structured and informal scientific workflows.Objective 3: Develop evaluation methods and metrics and use them to demonstrate the utility of workflow-based social media tools in the context of scientists testing LCS hypotheses.Objective 4: Leverage GLOBE to characterize and optimize global knowledge generation in LCS.To achieve these goals, this team will engage in the following activities:Activity 1: Develop the social-computational infrastructure for GLOBE.Activity 2: Establish GLOBE as a means for social-computational knowledge generation. Characterize, share and optimize knowledge generation workflows for global synthesis and collaboration across CHANS studies and data collections.Activity 3: Test hypotheses and identify new research opportunities.To understand anthropogenic global changes in the Earth system, scientists must generalize globally from observations made locally and regionally. This project will make fundamental hypotheses on the nature of human interactions with earth systems more readily testable by scientific methods, enabling major advances in land-change science and theory. Moreover, this project will engage the computing and social sciences in developing interactive online tools for scientific collaboration and data synthesis that will help identify knowledge gaps in LCS science. The tools will result in new ways of visualizing, communicating, connecting, comparing and synthesizing observations and models of land change processes at global, regional and local scales. Empirical investigation of GLOBE in use will advance our understanding of scientific collaboration more generally.Broader impactsThis project will develop, enhance and support long-term research collaborations across a broad set of scientific disciplines. It will support education and skill building for interdisciplinary collaboration by seasoned faculty, postdoctoral researchers, graduate students and undergraduate students. The project will design, host and disseminate advanced tools for cross-scale data and knowledge sharing, synthesis, and design of globally representative observing systems. By creating a new environment for sharing and integrating local knowledge, data and ideas across the social, biological and geophysical sciences, land change science will have greater potential to inform the sustainable stewardship of earth systems.