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: 10480765
• 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 2024-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10480765
• 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.

项目摘要 我们概述了下一代NIDDK信息网络（dkNET）的计划，这是一个集中的门户网站， 研究资源的发现和信息-数据，试剂，生物体，研究人员可用的工具 通过NIDDK支持的中心和其他相关项目。在这一阶段，我们将继续支持和 维护生物医学数据库的汇总数据。但自2012年dkNET推出以来，数据和 资源格局已经改变，对严格性和可重复性有了新的担忧，我们看到， 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 在开发和部署研究资源标识符（RRID）方面取得了相当大的成功， 识别、跟踪和汇总目前在350多个国家使用的文献中有关研究资源的数据 期刊RRID是分配给各个研究资源的唯一标识符，并构成 引用和跟踪系统，用于科学文献。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，以帮助研究人员不仅确定适当的 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，以确定和验证研究资源，并帮助支持中心跟踪其 产品.针对用户反馈和NIH新的数据管理要求和建议， 我们还将增加新的服务和工具来支持数据科学。在过去的这一阶段， PI帮助制定了FAIR原则，这些原则是使数据可查找、可解释、可互操作的建议 可重复使用。美国和欧洲的主要数据计划现在都在支持FAIR。充分执行 要求社区有办法开发和传播最佳实践和标准， 元数据、数据格式等。NIDDK是唯一准备帮助协调和加速这一进程， NIDDK支持研究人员。我们认为，要获得适当的数据管理和数据发布的支持， 重要的不仅仅是提供法规遵从性方面的帮助，而且还提供用于集成和 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，或MESSASA），我们将开发一个新的荟萃分析平台， 公平的经济学数据。通过对NIDDK资助的和 相关的组学数据资产，dkNET用户将可以访问一个用户友好但功能强大的建模平台 代谢器官中的信号传导事件以及细胞信号传导途径和代谢 疾病这些能力将伴随着积极和广泛的外联和传播 计划帮助扩大对dkNET和NIDDK支持的中心的认识和使用。