Scientia Arctica: A Knowledge Archive for Discovery and Reproducible Science in the Arctic

加州大学圣巴巴拉分校、美国国家科学基金会（nsf）资助的新墨西哥大学DataONE和美国国家海洋和大气管理局（通过马里兰大学）的研究人员将建立和运营一个多机构的知识档案，服务于不同的北极学科，包括生态学、地球科学、大气科学、海洋学、人类学、考古学、社会科学和政治学。该档案将提供保存和发现NSF北极科学部资助研究的所有产品的能力，包括数据、元数据、软件、文档，以及使用DataONE联邦数据存储库的基础设施将这些产品链接到一个连贯的知识模型中的来源。该合作协议将支持由美国国家科学基金会北极科学部门资助的北极研究数据的综合存档，这需要一个能够处理北极产生的复杂性、异质性和数据量的系统。通过构建已经处理这些类型数据的成功的存储库基础结构，存储库将在项目开始时上线，立即对研究人员有用，并通过功能扩展和细化进行持续改进。档案中的新功能将使数据、科学和政策之间的关键联系成为可能。数据科学奖学金计划、培训研讨会和短期课程将为至少190名研究生和本科生提供跨学科培训机会。选择将促进代表性不足的群体，目标是增加研究界数据科学家的多样性。回国的学生将有助于交流数据科学问题，并将在全国范围内影响科学学科的巨大变化。此外，新的基础设施和数据将对全球北极研究和政策产生持久的影响。北极科学在政策和社会上的重要性是不成比例的，部分原因是北极气候变化的影响，部分原因是受这些变化影响的石油、天然气和其他工业的资源影响。数字研究数据将成为影响科学和社会的新见解的基础。数据存储将利用加州大学圣巴巴拉分校KNB数据存储库（KNB，以前的生物复杂性知识网络）进行版本控制和访问，以实现有效的存档。数据将被复制到KNB、环境信息中心（NCEI）和亚马逊云等不同行政机构，因为这对长期保存至关重要。DataONE面向研究人员的工具将适应提供方便的途径来记录和归档不同的数据格式，作为科学家正常工作流程的一部分。该基础设施将得到一组出色的社区服务的支持，包括数据发现工具、元数据评估和编辑、数据清理和集成、数据管理咨询和用户帮助台服务。一个数据恢复小组将与社区合作，优先考虑和拯救来自过去NSF研究的关键北极数据，这些数据目前无法访问。除了数据档案的传统功能外，现代基于云的数据设施将支持科学过程的详细来源跟踪、数据使用和引用报告、异质学科之间的联系以及文献、研究者和资助计划之间的直接联系。可用性和外联专家将与跨学科的北极科学顾问委员会和更广泛的极地科学界合作，通过评估工具和服务，收集需求和用例，以及优先考虑对档案基础设施和服务提供的改进，推动持续改进。使用数据和可用性研究将推动评估和开发的迭代周期，以改进操作。

Investigators at the University of California Santa Barbara, the NSF-funded DataONE at the University of New Mexico, and NOAA (through the University of Maryland) will build and operate a multi-institutional knowledge archive serving diverse Arctic disciplines, including ecology, earth science, atmospheric science, oceanography, anthropology, archaeology, and social and political science. The archive will provide the capability to preserve and enable discovery of all products of NSF Arctic Science Section funded research, including data, metadata, software, documents, and provenance that link these in a coherent knowledge model, using infrastructure from the DataONE federation of data repositories.This cooperative agreement will support a comprehensive archive of data from Arctic research funded by the NSF Arctic Sciences section, which necessitates a system that can handle the complexity, heterogeneity, and volume of data generated in the Arctic. By building upon successful repository infrastructures that already handle these kinds of data the repository will come online at project inception, be immediately useful to researchers, and undergo continuous improvement through feature expansions and refinement. Novel features in the archive will enable critical linkages between data, science, and policy. A data science fellowship program, training workshops, and a short course will provide interdisciplinary training opportunities for at least 190 graduate and undergraduate students. Selection will promote underrepresented groups with the goal to increase the diversity of data scientists in the research community. Students returning to their home universities will help communicate data science issues and will effect a large change across science disciplines nationally. In addition, the new infrastructure and data will have a lasting impact on Arctic research and policy globally. Arctic science has policy and societal importance that are disproportionally large, partly because of the impacts of climate change in the Arctic, and partly because of the resource implications on the oil, gas, and other industries that are affected by these changes. Digital research data will serve as a foundation for new insights that impact both science and society.Data storage will be accomplished utilizing the UC Santa Barbara KNB Data Repository (KNB, formerly the Knowledge Network for Biocomplexity) for its versioning and accessioning to enable an effective archive. Data will be replicated to administratively diverse institutions at the KNB, the Centers for Environmental Information (NCEI) and the Amazon cloud, as this is critical to long-term preservation. DataONE researcher-facing tools will be adapted to provide convenient pathways to document and archive diverse data formats as part of scientists' normal workflow. This infrastructure will be supported with an outstanding set of community services, including data discovery tools, metadata assessment and editing, data cleansing and integration, data management consulting, and user help-desk services. A data recovery team will engage the community to prioritize and rescue critical Arctic data from past NSF research that is currently inaccessible. In addition to the traditional functions of a data archive, modern cloud-based data facilities will support detailed provenance tracking of the science process, data usage and citation reporting, linkages among heterogeneous disciplines, and direct linkages between the literature, investigators, and funding programs. Usability and outreach specialists will engage an interdisciplinary Arctic Science Advisory Board and the broader polar science communities to drive continuous improvement by evaluating tools and services, gathering requirements and use cases, and prioritizing improvements to infrastructure and service offerings of the archive. Usage data and usability studies will drive an iterative cycle of assessment and development to improve operations.