Environmental Data Initiative (EDI) - streamlining data curation to accelerate scientific inquiry

环境数据倡议 (EDI) - 简化数据管理以加速科学探究

• 批准号: 1629233
• 负责人: Corinna Gries
• 金额: $ 165.57万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-15 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1629233&HistoricalAwards=false
• 关键词: Environmental; Data; Initiative; EDI; streamlining

Global-scale environmental issues such as food security, the spread of disease, and the availability of clean water emphasize the importance of environmental data that can address specific problems while also providing predictions of future conditions. The increasing availability of large volumes of different kinds of data offers new opportunities to address these issues. This project will provide the environmental research community with efficient and reliable means for data management, storage, and sharing. The facilities developed will allow researchers, policy makers, managers, and other stakeholders to bring relevant data to bear on complex environmental questions. Modern approaches that encourage geographically distributed collaboration will be used to increase efficiency of data curation beyond those available for single projects. The project will provide the training and skills needed to overcome technical and social barriers to collaboration, thereby enhancing infrastructure to address ecological questions over broad spatial and temporal scales.Research in environmental sciences is often conducted by individual investigators over small spatial and temporal scales under funding models that provide limited capacity for data curation or sharing. Data that are archived in a stable, accessible repository and that are accompanied by appropriate metadata benefit both data producers and consumers through improved discoverability and reliability. This project builds on expertise available in the Long Term Ecological Research (LTER) community to provide these benefits. The project will leverage the collective experience of the LTER community to improve data management across a broad community through communication and collaboration. Training activities will be developed that range from the basics of metadata creation to the adoption of standardized best practices for specific types of data. The development of templates for describing a data lifecycle will accelerate the availability of data for synthesis. The project will promote shared technology to develop more commonly usable and more efficient approaches to data curation workflows. Participants in training workshops will be trained in developing workflow technology, re-using existing workflows, and archiving and sharing their developments. Through these workshops, together with community-level centers of expertise, and individual-based skill exchanges, the project will increase the volume of data available along with data discoverability and reuse. The Provenance Aware Synthesis Architecture repository will ensure long-term availability of data and open data access through federations such as DataONE. This repository will be expanded in several ways to accommodate a broader community of data providers and users. Enhancements include a scalable user identity management system, improved data documentation procedures to simplify data submission for non-technical users, and expanded data-quality assurance tools to accommodate a broader range of community practices. These advances will accelerate scientific inquiry through data curation and publication as well as through data discovery and integration.

全球范围的环境问题，如粮食安全、疾病传播和清洁水的供应，强调了环境数据的重要性，这些数据可以解决具体问题，同时还可以预测未来的情况。越来越多的不同种类的大量数据的可用性为解决这些问题提供了新的机会。该项目将为环境研究界提供有效和可靠的数据管理，存储和共享手段。开发的设施将使研究人员、决策者、管理人员和其他利益攸关方能够利用相关数据来解决复杂的环境问题。鼓励地理上分散的协作的现代方法将被用来提高数据管理的效率，而不是单一项目的效率。该项目将提供克服合作的技术和社会障碍所需的培训和技能，从而加强基础设施，以解决广泛的空间和时间尺度上的生态问题，环境科学研究往往由个人调查人员在小的空间和时间尺度上进行，其资助模式提供有限的数据管理或共享能力。归档在稳定、可访问的储存库中并附有适当元数据的数据，通过提高可重复性和可靠性，使数据生产者和消费者都受益。该项目建立在长期生态研究（LTER）社区的专业知识基础上，以提供这些好处。该项目将利用长期应急反应社区的集体经验，通过沟通和协作，改善整个广泛社区的数据管理。将开展培训活动，内容从创建元数据的基本知识到针对具体类型的数据采用标准化最佳做法。开发用于描述数据生命周期的模板将加快提供数据以供综合。该项目将促进共享技术，以开发更通用和更有效的数据管理工作流程方法。培训讲习班的参与者将接受开发工作流程技术、重新使用现有工作流程以及存档和分享其发展成果的培训。通过这些讲习班，再加上社区一级的专门知识中心和个人技能交流，该项目将沿着增加现有数据量，并提高数据的可重复性和再利用性。 Provenance Aware Synthesis Architecture存储库将确保数据的长期可用性，并通过DataONE等联合体开放数据访问。将以几种方式扩大这一储存库，以容纳更广泛的数据提供者和用户群体。增强功能包括可扩展的用户身份管理系统、改进的数据记录程序以简化非技术用户的数据提交，以及扩大的数据质量保证工具以适应更广泛的社区做法。 这些进步将通过数据管理和出版以及数据发现和整合来加速科学探究。