Elements: Science-i Cyberinfrastructure for Forest Ecosystem Research

森林在历史上一直维持着粮食、水、能源安全和人类福祉，但日益受到气候变化、生物多样性丧失、森林砍伐和森林退化的威胁。为了应对这些全球性挑战，森林合作研究需要从世界各地收集的大量森林清查数据、高性能计算设施以及国际和跨学科专业知识，以提供循证的森林养护和恢复做法。然而，缺乏研究数据、计算能力和专家支持来提出研究问题，是森林合作研究的主要障碍，特别是对来自代表性不足社区的研究科学家而言。为了克服这一障碍，该项目创建了一个网络基础设施“科学-i”，该基础设施具有定制的数据治理框架，围绕该框架，数据贡献者，研究人员和包括土著利益相关者在内的社区在一个安全，可查找，可访问，可互操作和可重复使用的平台中连接起来，共同产生拯救世界森林生态系统的知识。Science-i利用来自57个国家的343名注册研究科学家组成的不断增长的社区，他们将贡献数据和专业知识，以支持合作森林研究，气候适应规划和社区决策。Science-i还通过一个框架实现了高价值的科学调查，该框架将来自当地数据贡献者的森林资源清查数据与各种级别的数据共享限制相结合，并允许代表性不足的研究人员共享使用先进的分析工具，研究代码和高性能计算资源。该项目将美洲原住民的经验和专门知识纳入全球一致和地方相关知识的共同生产中，其目标是开发Science-i网络基础设施，为数据驱动的合作森林研究提供必要和及时的支持，解决对拯救世界森林生态系统至关重要的科学问题。Science-i基于创新的动态数据治理框架，通过动态策略执行实现多源数据管理。定制，以解决合作森林研究中的数据共享的挑战，这个框架支持并纳入多个数据共享政策，预定义的本地原始数据集的数据贡献者，在一个动态的系统，使这些政策在整个数据生命周期的执行。Science-i收集来自世界各地的原始森林资源清查数据集，并将其整合到不同保密级别的全球数据集中，以便它们可以被许多正在进行的研究项目所利用。整个团队的协作由一个安全的项目沙箱支持，使项目成员能够利用机器学习工具包和内置的社区协作功能，共同产生全球一致和本地相关的知识，这将促进我们对全球森林系统生态过程的理解，阐明确定和解释陆地生物多样性及其在空间和时间上与环境相互作用的基本原则。该项目使社区参与各种知识合作生产，教育和推广活动，并支持由女性PI，研究生，博士后和/或其他早期职业研究人员领导的12个科学研究项目。Science-i还通过合作外展活动，如与联合国粮食及农业组织（粮农组织）共同主办的年度全球网络研讨会，吸引不同的受众和社区。“科学-i”项目的若干研究项目旨在促进农村和土著社区的具有气候抗御能力的森林管理和养护。由全国印第安人碳联盟协调的美洲原住民利益攸关方将在根据研究结果共同制定政策和实用指南方面发挥主导作用。将组织两个虚拟研讨会和两个现场研讨会，以吸引用户、利益相关者和开发人员，包括来自代表性不足的社区的25名参与者，他们将被支持参加面对面的研讨会。NSF高级网络基础设施办公室的这一奖项由NSF生物基础设施部门（BIO/DBI）共同支持。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Forests, which have been sustaining food, water, energy security, and human well-being throughout history, are increasingly threatened by climate change, biodiversity loss, deforestation, and forest degradation. Central to tackling these global challenges, collaborative forest research requires massive forest inventory data collected from around the world, high-performance computing facilities, as well as international and interdisciplinary expertise to provide evidence-based forest conservation and restoration practices. However, a lack of research data, computing capacity, and expert support for framing research questions poses a major obstacle to collaborative forest research, especially for research scientists from under-represented communities. To overcome this obstacle, this project creates a cyberinfrastructure “Science-i” with a customized data governance framework around which data contributors, researchers, and communities including indigenous stakeholders are connected in a secure, findable, accessible, interoperable, and reusable platform to co-produce knowledge for saving the world’s forest ecosystems. Science-i leverages a growing community of 343 registered research scientists from 57 countries who will contribute data and expertise to support collaborative forest research, climate adaptation planning, and community decision-making. Science-i also enables high-value scientific inquiries with a framework that integrates forest inventory data from local data contributors with various levels of data-sharing restrictions, and allows shared use of advanced analysis tools, research codes, and high-performance computing resources by the under-represented researchers. The project incorporates Native American experience and expertise into the co-production of globally consistent and locally relevant knowledge.The objective of this project is to develop Science-i cyberinfrastructure to provide essential and timely support for data-driven collaborative forest research that addresses scientific questions central to saving the world’s forest ecosystems. Science-i is based on an innovative dynamic data governance framework that enables multi-source data management with dynamic policy enforcement. Customized to address the data-sharing challenges in collaborative forest research, this framework supports and incorporates multiple data-sharing policies, pre-defined by data contributors of local raw datasets, in a dynamic system so that these policies are enforced throughout the data lifecycle. Science-i collects local raw forest inventory datasets from all over the world, and integrates them into global datasets of different confidentiality levels so that they can be utilized by a number of ongoing research projects. The team- wide collaboration is supported by a secure project sandbox that enables project members to utilize a machine learning toolkit and built-in community collaboration functions to co-produce globally consistent and locally relevant knowledge that will advance our understanding of the ecological processes of global forest systems, and elucidate fundamental principles that identify and explain terrestrial biodiversity and its interactions with the environment over space and time. This project engages communities with various knowledge co-production, education, and outreach activities, and supports twelve research projects in Science-i led by female PIs, graduate students, postdocs, and/or other early-career researchers. Science-i also engages diverse audiences and communities through collaborative outreaching events such as annual global webinars co-hosted with the Food and Agriculture Organization of the United Nations (FAO). Several Science-i research projects are aimed at promoting climate-resilient forest management and conservation among rural and indigenous communities. Native American stakeholders, coordinated by the National Indian Carbon Coalition will take a leading role in co-producing policies and practical guidelines based on the research results. Two virtual and two in-person workshops will be organized to engage users, stakeholders, and developers, including 25 participants from under-represented communities who will besupported to attend in-person workshops.This award by the NSF Office of Advanced Cyberinfrastructure is jointly supported by the NSF Division of Biological Infrastructure (BIO/DBI).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.