Pan-Neurotrauma Data Commons

泛神经创伤数据共享

• 批准号: 10478255
• 负责人: ADAM R FERGUSON
• 金额: $ 73.85万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10478255
• 关键词: Adoption; Affect; Anatomy; Animal Model; Behavioral; Big Data; Big Data Methods; Brain; Certification; Collaborations; Common Data Element; Communities; Complex; Controlled Vocabulary; Data; Data Commons; Data Pooling; Data Set; Disease; Ecosystem; Educational workshop; FAIR principles; Feedback; Functional disorder; Future; Generations; Goals; Health; Healthcare; Heterogeneity; Human; Impairment; Individual; Infrastructure; Injury; International; Internet; Knowledge; Laboratories; Lead; Licensing; Medical; Metadata; Monitor; Multiple Trauma; Mus; National Institute of Neurological Disorders and Stroke; Nervous System Trauma; Neuraxis; Neurosciences; Ontology; Oranges; Outcome Assessment; Outcome Measure; Persons; Physiology; Police; Policies; Positioning Attribute; Predictive Value; Prevalence; Process; Publication Bias; Publications; Quality Control; Rattus; Recovery; Reporting; Reproducibility; Reproducibility of Results; Research; Research Personnel; Severities; Site; Spinal Cord; Spinal cord injury; Standardization; Structure; Syndrome; System; Terminology; Testing; Therapeutic; Tissue Expansion; Translations; Trauma; Traumatic Brain Injury; Traumatic CNS injury; Treatment Efficacy; U-Series Cooperative Agreements; United States National Institutes of Health; Visualization; Work; advanced analytics; base; body system; central nervous system injury; clinical implementation; clinically relevant; community engagement; complex data; dashboard; data complexity; data format; data interoperability; data management; data mining; data quality; data repository; data resource; data reuse; data sharing; data standards; data visualization; data wrangling; digital object identifier; diverse data; economic cost; economic impact; experience; experimental study; human data; improved; information framework; insight; interoperability; large scale data; neuroinformatics; new technology; novel; open data; open source; operation; pre-clinical; preservation; productivity loss; prospective; public repository; quality assurance; repaired; repository; skills; spinal cord and brain injury; success; symposium; therapeutic development; therapeutic evaluation; tool; trustworthiness; virtual laboratory; web portal; webinar

PROJECT SUMMARY/ABSTRACT Trauma to the central nervous system (CNS: spinal cord and brain) together affect more than 2.5 million people per year in the US, with economic costs of $80 billion in healthcare and loss-of-productivity. Yet, the precise pathophysiological processes impairing recovery remain poorly understood. This lack of knowledge is exacerbated by poor reproducibility of findings in animal models and limits translation of therapeutics across species and into humans. Part of the problem is that neurotrauma is intrinsically complex, involving heterogeneous damage to the central nervous system (CNS), by far the most complex organ system in the body. This results in a multifaceted CNS syndrome reflected across heterogeneous endpoints and multiple scales of analysis. Multi-scale heterogeneity makes traumatic brain injury (TBI) and spinal cord injury (SCI) difficult to understand using traditional analytical approaches that focus on a single endpoint for testing therapeutic efficacy. Single endpoint-testing provides a narrow window into the complex system of changes that describe SCI and TBI. Understanding these disorders involves managing datasets that include high volume anatomy data, high velocity physiology decision-support data, the high variety functional/behavioral data, and assessing correlations among these endpoints. In this sense, neurotrauma is fundamentally a data management problem that involves the classic ‘3Vs of big data’ (volume, velocity, variety). Of these, variety is perhaps the greatest data challenge in neurotrauma research for reproducibility in basic discovery, cross-species translation, and ultimately clinical implementation. For the proposed Data Repositories Cooperative Agreement (U24) we will build on our prior work managing data variety in the Open Data Commons for SCI (odc-sci.org) and TBI (odc-tbi.org) to make neurotrauma data Findable, Accessible, Interoperable, and Reusable (FAIR). The milestone-driven aims will: 1) further develop and harden our data lifecycle management system with end-to-end data version control and provenance tracking, data certification, and data citation; 2) develop in-cloud data dashboards and visualizations to monitor data quality and to promote data reuse, exploration, and hypothesis generation; 3) establish a pan- neurotrauma (PANORAUMA) data commons that brings together separate data assets currently supported by our multi-PI (MPI) team by aligning a patchwork of governance structures and policies. The goal of the proposed project is to develop a pooled repository for preclinical discovery, reproducibility testing, and translational discovery both within and across neurotrauma types. Our team is well-positioned to execute this project given that we developed some of the largest multicenter, multispecies neurotrauma data repositories of neurotrauma to-date (N>10,000 subjects 20,000 curated variables); the Neuroscience Information Framework (NIF); data terminologies and standards for these fields (MIASCI, NIFSTD); and policy work with the International Neuroinformatics Coordinating Facility (INCF). The PANORAUMA cooperative agreement is highly responsive to PAR-20-089, leveraging early successes in SCI and TBI data sharing to improve quality and sustainability.

项目摘要/摘要 中枢神经系统的创伤（CNS：脊髓和大脑）共同影响超过250万人 在美国，每年的经济成本为800亿美元的医疗保健和生产力丧失。但是，精度 病理生理过程损害了康复的理解仍然很少。缺乏知识是 在动物模型中发现的可重现性不佳，并限制了整个治疗的翻译 物种并进入人类。问题的一部分是，神经瘤本质上是复杂的，涉及 迄今为止，体内最复杂的器官系统对中枢神经系统（CNS）的异质损害。 这导致多方面的中枢神经系统综合征反映在异质端点和多个尺度上 分析。多尺度异质性使脑外伤（TBI）和脊髓损伤（SCI）难以难以 使用传统的分析方法理解，该方法专注于测试治疗效率的单个终点。 单端点测试为描述Sci和 TBI。了解这些疾病涉及管理包括大量解剖数据的数据集，高 速度生理学决策支持数据，多样性的功能/行为数据以及评估相关性 在这些端点。从这个意义上讲，神经曲从根本上是一个数据管理问题，涉及 经典的“大数据3V”（卷，速度，多样性）。其中，多样性可能是最大的数据挑战 在基本发现，跨物种翻译和最终临床的神经曲研究研究中 执行。对于拟议的数据存储库合作协议（U24），我们将在先前的基础上建立 在SCI（ODC-SCI.org）和TBI（ODC-tbi.org）的开放数据共享中管理数据变体的工作 Neurotrauma数据可发现，可访问，可互操作和可重复使用（公平）。里程碑驱动的目标将：1） 进一步开发并通过端到端数据版本控制和 出处跟踪，数据认证和数据引用； 2）开发云中数据仪表板和可视化 监视数据质量并促进数据重用，探索和假设产生； 3）建立一个锅 Neurotrauma（Panorauma）数据共享将目前支持的单独数据资产汇总在一起 我们的Multi-Pi（MPI）团队通过对齐治理结构和政策的拼凑而成。提议的目标 项目是为临床前发现，可重复性测试和翻译的汇总存储库开发 在神经瘤类型内部和跨性别的发现。我们的团队有很好的位置执行该项目 我们开发了一些最大的多中心，多种神经素的神经数据存储库 迄今（n> 10,000名受试者20,000个策划变量）；神经科学信息框架（NIF）；数据 这些领域的术语和标准（Miasci，Nifstd）；和国际政策合作 神经信息协调设施（INCF）。 Panorauma合作协议高度响应 到089年第20届公寓，利用SCI和TBI数据共享的早期成功来提高质量和可持续性。