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.

摘要 本补充提案的目的是收集神经科学的标准化种源元数据 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就绪。NSG项目始于2012年，旨在通过减少技术和 神经学家在大型建模项目中面临的管理障碍，这些项目对 性能计算资源。NSG的成功反映在其注册用户基础上 (目前为1370)自开始运营以来不断增长，每年NSG团队都成功 在NSF资助的超级计算机上获得了超过14,000,000个核心时间，并为 发表论文数量和博士/硕士论文数量。从2017年开始实验者和认知神经学家 开始使用NSG进行数据处理/分析和ML。NSG现在提供了16种以上的工具 用于模拟、数据处理和ML的超级计算机。正如在#年授予的家长U24赠款中承诺的那样 2019年，我们通过添加新功能增强了NSG，使其成为高效的开发和 向更广泛的神经科学界传播实验室开发的神经科学工具。应该指出的是 目前没有规定记录任何NSG工具的元数据或来源信息，以及 他们产生的数据集。目前，NSG的大量计算工具和数据集缺乏 支持将其集成到ML工作流中所需的标准化批注，支持 可解释的人工智能和重复性。在本补充中，我们将首先集成基于W3CProv规范的 NSG中的种源本体通过种源接口允许用户记录种源元数据 使用本体类。我们将通过一个试点项目演示来源本体的使用，该项目将 使用一种名为神经集成连接(NIC)工具的神经科学软件分析EEG数据以 计算神经功能障碍的大脑网络。NIC工具具有起源元数据 特性，并将成为第一个携带来自 从数据集生命周期的末尾开始。基于本体的网卡工具的标准化描述 数据将使NSG能够使它们可查找、可访问、可互操作和可重复使用。在这方面， 提供一种安全的方法来高效地共享和验证数据和元数据是重复使用所必需的 科学数据。为了实现这一目标，我们将利用美国国家科学基金会资助的开放科学链(OSC)项目 提供基于区块链的解决方案，以维护数据集及其元数据的完整性和来源 并提供了对区块链中存储的数据进行独立验证的方式。体验 通过在NSG框架内集成起源本体、NIC工具和OSC而获得，Will 允许我们在未来集成其他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。