Neuroscience Gateway to Enable Dissemination of Computational And Data Processing Tools And Software.

神经科学网关能够传播计算和数据处理工具和软件。

• 批准号: 10594344
• 负责人: Amitava Majumdar
• 金额: $ 33.28万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-20 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10594344
• 关键词: Award; Brain; Characteristics; Clinical; Cognitive; Communities; Computer Models; Computer software; Data; Data Set; Data Store; Development; Disease; Doctor of Philosophy; Electroencephalography; Environment; FAIR principles; Funding; Future; Grant; Health; High Performance Computing; Hour; Internet; Metadata; Methods; Modeling; Neurophysiology - biologic function; Neurosciences; Ontology; Parents; Pilot Projects; Publications; Reproducibility; Research; Secure; Standardization; Time; Workload; base; blockchain; brain cell; computerized data processing; computerized tools; computing resources; experience; large datasets; nervous system disorder; open data; operation; simulation; success; supercomputer; tool

Summary The objective of this supplement proposal is to collect standardize provenance metadata of the Neuroscience Gateway (NSG) datasets and computational tools using a provenance ontology, which will enable them to be AI/ML ready. The NSG project began in 2012 to catalyze progress in neuroscience by reducing technical and administrative barriers that neuroscientists faced in large scale modeling projects which require high performance computing resources. NSG's success is reflected in the facts that its base of registered users (currently 1370) has grown continually since it started operation, every year the NSG team successfully acquires over 14,000,000 core hours of time on NSF funded supercomputers and it has contributed to large number of publications and Ph.D./MS thesis. Starting in 2017 experimentalists and cognitive neuroscientists began to use NSG for data processing/analysis and ML. NSG now provides over sixteen tools on supercomputers for simulation, data processing and ML. As promised in the parent U24 grant awarded in 2019, we have enhanced NSG by adding new features making it an efficient environment for development and dissemination of lab-developed neuroscience tools to the broader neuroscience community. It should be noted that currently there is no provision to record metadata or provenance information for any of the NSG tools and the data sets they produce. Currently the large number of NSG computational tools and the datasets lack standardized annotations that is needed to enable them to be integrated into ML workflows with support for explainable AI and reproducibility. In this supplement, we will first integrate a W3C PROV specification-based provenance ontology in NSG through a provenance interface to allow users to record provenance metadata using ontology classes. We will demonstrate the use of provenance ontology through a pilot project that will use a neuroscience software called the NeuroIntegrative Connectivity (NIC) tool that analyzes EEG data to compute functional brain networks in neurological disorders. The NIC tool has provenance metadata characteristics built into it, and will be the first NSG tool to carry the metadata provenance information from the beginning to the end of a dataset’s lifecycle. The ontology-based standardized description of both the NIC tool and data will enable NSG to make them findable, accessible, interoperable, and reusable. In this context, providing a secure method to efficiently share and verify the data and metadata is necessary for reuse of scientific data. To achieve this, we will utilize the NSF-funded Open Science Chain (OSC) project which provides a blockchain based solution to maintain the integrity and provenance for datasets and its metadata and provides a way to perform independent verification of the data stored in the blockchain. The experience gained via integrating a provenance ontology, the NIC tool and the OSC within the framework of NSG, will allow us in the future to integrate metadata provenance information of other NSG tools and make the NSG comprehensively more suitable for AI/ML workloads.

概括 该补充提案的目的是收集神经科学的标准化来源元数据 使用起源本体的网关（NSG）数据集和计算工具，这将使它们能够 AI/ML 已准备就绪。NSG 项目于 2012 年启动，旨在通过减少技术和成本来促进神经科学的进步。 神经科学家在需要高门槛的大规模建模项目中面临的行政管理 NSG 的成功体现在其注册用户基础。 （目前 1370）自运营以来不断增长，NSG 团队每年都成功 在 NSF 资助的超级计算机上获得了超过 14,000,000 小时的核心时间，并为大规模 从 2017 年开始实验学家和认知神经科学家的出版物和博士/硕士论文数量。 开始使用 NSG 进行数据处理/分析，NSG 现在提供超过 16 种工具。 用于模拟、数据处理和机器学习的超级计算机 正如 2019 年授予的 U24 母基金中所承诺的那样。 2019 年，我们通过添加新功能增强了 NSG，使其成为高效的开发环境和 值得注意的是，将实验室开发的神经科学工具传播给更广泛的神经科学界。 目前没有规定记录任何 NSG 工具的元数据或出处信息，并且 目前，NSG 缺乏大量计算工具和数据集。 标准化注释，使它们能够集成到 ML 工作流程中并支持 可解释的 AI 和可重复性 在本补充中，我们将首先集成基于 W3C PROV 规范。 NSG 中的起源本体通过起源接口允许用户记录起源元数据 我们将通过一个试点项目演示起源本体的使用。 使用称为 NeuroIntegrative Connectivity (NIC) 工具的神经科学软件，该工具将脑电图数据结合起来 计算神经系统疾病中的功能性大脑网络 NIC 工具具有来源元数据。 内置的特性，并将成为第一个携带元数据来源信息的 NSG 工具 数据集生命周期的开始到结束 NIC 工具的基于本体的标准化描述。 数据将使 NSG 能够使它们可查找、可访问、可互操作和可重用。 提供一种安全的方法来有效地共享和验证数据和元数据对于重用是必要的 为了实现这一目标，我们将利用 NSF 资助的开放科学链 (OSC) 项目，该项目 提供基于区块链的解决方案来维护数据集及其元数据的完整性和来源 并提供了一种对区块链中存储的数据进行独立验证的体验。 通过在 NSG 框架内集成起源本体、NIC 工具和 OSC 获得的，将 允许我们将来集成其他 NSG 工具的元数据来源信息，并使 NSG 全面更适合 AI/ML 工作负载。