BCO-DMO: Accelerating Scientific Discovery through Adaptive Data Management

BCO-DMO：通过自适应数据管理加速科学发现

基本信息

批准号：
1924618
负责人：
Mak Saito
金额：
$ 1158.1万
依托单位：
Woods Hole Oceanographic Institution
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1924618&HistoricalAwards=false
关键词：
BCO DMO Accelerating Scientific Discovery

项目摘要

Scientific research is intrinsically reliant upon the creation, management, analysis, synthesis, and interpretation of data. Once generated, data are essential to demonstrating the veracity and reproducibility of scientific results, and existing data hold great potential to accelerate scientific discovery through reuse. The Biological and Chemical Oceanography and Data Management Office (BCO-DMO) was created in 2006 to assemble, curate, and publicly serve all data and related products resulting from grants funded by the NSF core programs for Biological and Chemical Oceanography, and Office of Polar Programs. BCO-DMO provides limnological and marine chemical, biological, and physical data inventories from several large and intermediate-sized programs, as well as single-investigator projects to support cross-disciplinary collaboration to address pressing environmental questions, problems, and challenges that are exacerbated with the increasing pace of climate change. BCO-DMO is committed to data management capacity building efforts, improving data literacy and increasing science engagement in data management topics through education, training, and outreach. The project collaborates with academic institutions and teachers, where the BCO-DMO database is leveraged for oceanographic curricula, and engages in targeted training of informatics students, cross-pollinating their knowledge with geoscience domain data management.BCO-DMO's goal is to facilitate the integration of its diverse datasets to enable researchers to achieve a deeper understanding of ocean ecological and biogeochemical systems. As a domain repository, BCO-DMO adds value and improves interoperability of data to support activities such as synthesis and modeling, and the reuse of oceanographic data for new research. Open access to the BCO-DMO database lowers barriers to allow economically challenged countries to gain access to research quality data for field decision support, policy-relevant issues, and educational purposes. The project takes an active role in the exchange of knowledge at national and international geoscience and informatics meetings and workshops, where standards development and adoption occur. BCO-DMO also participates in the development and use of open-source, standards-based technologies that enable interoperable data systems to exchange data and information that will foster next-generation research in all disciplines. While continuing to perform its core mission of data management, BCO-DMO will reconstitute its data infrastructure to mobilize a new adaptive data management strategy for addressing the evolutionary change coinciding with the big data revolution. Leveraging data semantics BCO-DMO will construct a knowledge graph for sustainably operating an adaptive data repository. This infrastructure will support dataset-level and repository-level metrics, an improved data submission experience and new data and metadata access capabilities. Through declarative workflows, the processing of contributed data will increase in efficiency, and result in actionable provenance records for complete transparency of data curation practices. Taking a holistic perspective on education, outreach and community engagement, formalized programs will be developed to promote data reuse and interest in oceanographic science.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.

科学研究本质上依赖于数据的创建、管理、分析、综合和解释。一旦生成，数据对于证明科学结果的准确性和可重复性至关重要，并且现有数据具有通过重用加速科学发现的巨大潜力。生物和化学海洋学和数据管理办公室 (BCO-DMO) 成立于 2006 年，负责收集、整理和公开提供由 NSF 生物和化学海洋学核心项目以及极地办公室资助的所有数据和相关产品。节目。 BCO-DMO 提供来自多个大中型项目以及单一研究者项目的湖泊学和海洋化学、生物和物理数据清单，以支持跨学科合作，解决日益加剧的紧迫环境问题、问题和挑战随着气候变化步伐的加快。 BCO-DMO 致力于数据管理能力建设，通过教育、培训和推广提高数据素养并增加对数据管理主题的科学参与。该项目与学术机构和教师合作，利用 BCO-DMO 数据库进行海洋学课程，并对信息学学生进行有针对性的培训，将他们的知识与地球科学领域数据管理交叉授粉。BCO-DMO 的目标是促进整合其多样化的数据集使研究人员能够更深入地了解海洋生态和生物地球化学系统。作为一个领域存储库，BCO-DMO 增加了数据的价值并提高了数据的互操作性，以支持合成和建模等活动，以及海洋学数据在新研究中的重用。 BCO-DMO 数据库的开放访问降低了障碍，使经济困难的国家能够获得用于现场决策支持、政策相关问题和教育目的的研究质量数据。该项目在国家和国际地球科学和信息学会议和研讨会上的知识交流中发挥了积极作用，这些会议和研讨会是标准制定和采用的地方。 BCO-DMO 还参与基于标准的开源技术的开发和使用，这些技术使可互操作的数据系统能够交换数据和信息，从而促进所有学科的下一代研究。在继续履行其数据管理核心使命的同时，BCO-DMO 将重组其数据基础设施，以调动新的自适应数据管理策略，以应对与大数据革命同时发生的演进变化。利用数据语义 BCO-DMO 将构建一个知识图谱，以可持续地操作自适应数据存储库。该基础设施将支持数据集级和存储库级指标、改进的数据提交体验以及新的数据和元数据访问功能。通过声明性工作流程，贡献数据的处理将提高效率，并产生可操作的来源记录，从而实现数据管理实践的完全透明。从教育、推广和社区参与的整体角度出发，将制定正式计划，以促进数据重用和对海洋科学的兴趣。该奖项反映了 NSF 的法定使命，并通过利用基金会的智力优势和更广泛的影响进行评估，被认为值得支持审查标准。