dkNET Coordinating Unit: An information network for FAIR resources and data

dkNET 协调单元：FAIR 资源和数据的信息网络

• 批准号: 10222656
• 负责人: Jeffrey S. Grethe
• 金额: $ 98.08万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-12-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10222656
• 关键词: Address; Adoption; Atlases; Awareness; Communities; Data; Data Aggregation; Data Analytics; Data Science; Data Set; Databases; Ensure; Enzymes; Europe; Evaluation; Event; FAIR principles; Feedback; Fostering; Foundations; Funding; Goals; Guidelines; Individual; Information Networks; Infrastructure; Journals; Libraries; Literature; Maintenance; Meta-Analysis; Metabolic; Metabolic Diseases; Mining; Modeling; National Institute of Diabetes and Digestive and Kidney Diseases; Nuclear Receptors; Organ; Organism; Performance; Phase; Pilot Projects; Process; Publishing; Reagent; Receptor Signaling; Recommendation; Reproducibility; Research; Research Personnel; Resources; Services; Signal Pathway; Signal Transduction; System; United States National Institutes of Health; Universities; Work; analytical tool; body system; cloud based; dashboard; data format; data management; data resource; data sharing; indexing; metadata standards; next generation; novel strategies; outreach; receptor; research and development; response; success; symposium; text searching; tool; transcription factor; user centered design; user-friendly

Project Summary We outline plans for the next generation NIDDK Information Network (dkNET), a centralized portal for discovery and information about research resources-data, reagents, organisms, tools available to researchers through NIDDK-supported centers and other relevant projects. In this phase, we will continue to support and maintain aggregated data from biomedical databases. But since the launch of dkNET in 2012, the data and resource landscape has changed, there are new concerns about rigor and reproducibility, and we are seeing data mandates and increased demand for data and data services. We will therefore capitalize upon our considerable success in developing and deploying Research Resource Identifiers (RRIDs), a system for identifying, tracking and aggregating data about research resources in the literature currently used in over 350 journals. RRIDs are unique identifiers assigned to individual research resources and form the basis of a citation and tracking system for use within the scientific literature. Through RRIDs, we will further develop our Resource Information Network, including analytics tools, to help researchers not only to identify appropriate resources, but to provide them with up to date information about the use and performance of these resources. We will also develop services in support of NIH's new rigor and reproducibility guidelines to help researchers develop plans to identify and validate research resources and help support centers in tracking use of their products. In response to user feedback and new NIH mandates and recommendations for data management and sharing, we will also add new services and tools in support of data science. During this past phase, the PI's helped develop the FAIR principles, recommendations for making data Findable, Accessible, Interoperable and Reusable. Major data initiatives in both the US and Europe are now supporting FAIR. Full implementation of FAIR requires that the community have a way to develop and disseminate best practices and standards for metadata, data formats, etc. NIDDK is uniquely poised to help coordinate and accelerate this process for NIDDK supported researchers. We believe to gain support for proper data management and data publishing, it is important not just to provide help in compliance, but to provide tools and services for integrating and analyzing FAIR data to address critical questions. In conjunction with the Signaling Pathways Project (SPP, formerly the Nuclear Receptor Signaling Atlas, or NURSA), we will develop a new meta-analysis platform for FAIR `omics data. Through the application of biocuration and consensomic analysis of NIDDK-funded and relevant `omics data assets, dkNET users will have access to a user-friendly but powerful platform for modeling signaling events in metabolic organs and intersections between cellular signaling pathways and metabolic disease. These capabilities will be accompanied by an aggressive and extensive outreach and dissemination plan to help broaden awareness of and use of dkNET and NIDDK-supported centers.

项目概要 我们概述了下一代 NIDDK 信息网络 (dkNET) 的计划，这是一个集中式门户网站 有关研究资源的发现和信息——研究人员可用的数据、试剂、生物体、工具 通过 NIDDK 支持的中心和其他相关项目。在这个阶段，我们将继续支持和 维护生物医学数据库中的汇总数据。但自 2012 年 dkNET 推出以来，数据和 资源格局发生了变化，人们对严谨性和可重复性产生了新的担忧，我们正在看到 数据任务以及对数据和数据服务的需求增加。因此，我们将利用我们的 在开发和部署研究资源标识符（RRID）方面取得了巨大成功，这是一个系统 识别、跟踪和汇总目前 350 多个文献中使用的研究资源的数据 期刊。 RRID 是分配给各个研究资源的唯一标识符，构成了 在科学文献中使用的引用和跟踪系统。通过 RRID，我们将进一步发展我们的 资源信息网络，包括分析工具，不仅帮助研究人员识别合适的 资源，而是向他们提供有关这些资源的使用和性能的最新信息。 我们还将开发支持 NIH 新的严格性和可重复性指南的服务，以帮助研究人员 制定计划来识别和验证研究资源并帮助支持中心跟踪其使用情况 产品。响应用户反馈以及 NIH 新的数据管理任务和建议 和共享，我们还将添加新的服务和工具来支持数据科学。在过去的这个阶段， PI 帮助制定了 FAIR 原则以及使数据可查找、可访问、可互操作的建议 并可重复使用。美国和欧洲的主要数据计划现在都支持 FAIR。全面实施 FAIR 要求社区有办法制定和传播最佳实践和标准 元数据、数据格式等。NIDDK 致力于帮助协调和加速这一过程 NIDDK 支持研究人员。我们相信，要获得对正确数据管理和数据发布的支持，它 重要的不仅仅是提供合规方面的帮助，还提供用于集成和服务的工具和服务。 分析 FAIR 数据以解决关键问题。与信号通路项目 (SPP, 以前的核受体信号图谱（NURSA），我们将开发一个新的荟萃分析平台 公平的组学数据。通过应用 NIDDK 资助的生物管理和共识分析 相关的组学数据资产，dkNET 用户将可以访问用户友好但功能强大的建模平台 代谢器官中的信号事件以及细胞信号通路与代谢之间的交叉点 疾病。这些能力将伴随着积极而广泛的外展和传播 计划帮助扩大对 dkNET 和 NIDDK 支持中心的认识和使用。