The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR.
The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR.
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DOI：
10.3389/fninf.2023.1276407
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发表时间：
2023
影响因子：
3.5
通讯作者：
Martone ME
中科院分区：
文献类型：
--
作者：
Martone ME
在过去的十年里，神经科学已经取得了重大的进步，从一个以缺乏数据共享为特征的基本上封闭的科学，转变为一个基本上开放的科学，其中公开可用的神经科学数据的数量急剧增加。虽然这种增长在很大程度上是由大型前瞻性数据共享研究推动的，但我们开始看到神经科学数据长尾共享的增加，这无疑是由期刊要求和基金授权推动的。随着这种开放性的转变，越来越多的神经科学实践和基础设施支持FAIR数据原则。FAIR对于神经科学来说尤其重要，因为它具有多种数据类型、规模和模型系统以及为它们服务的基础设施。正如神经信息学早期所设想的那样，神经科学目前由以神经科学为中心的数据存储库的全球分布式生态系统提供服务，主要围绕数据类型进行专业化。为了使神经科学数据可查找、可访问、可互操作和可重用，需要不同利益相关者之间的协调，包括产生数据的研究人员、使数据可用的数据存储库、跨数据搜索引擎的聚合器和索引器，以及帮助协调工作和开发对FAIR至关重要的社区标准的社区组织。国际神经信息学协调机构（International Neuroinformatics Coordinating Facility）领导了将神经科学推向FAIR的努力，部署了一些资源来帮助研究人员和知识库实现FAIR。从这个角度来看，我提供了在神经科学中实现公平所需的组成部分和实践的概述，并提供了从实验室到搜索引擎的神经科学公平基础设施的过去，现在和未来的想法。
Neuroscience has made significant strides over the past decade in moving from a largely closed science characterized by anemic data sharing, to a largely open science where the amount of publicly available neuroscience data has increased dramatically. While this increase is driven in significant part by large prospective data sharing studies, we are starting to see increased sharing in the long tail of neuroscience data, driven no doubt by journal requirements and funder mandates. Concomitant with this shift to open is the increasing support of the FAIR data principles by neuroscience practices and infrastructure. FAIR is particularly critical for neuroscience with its multiplicity of data types, scales and model systems and the infrastructure that serves them. As envisioned from the early days of neuroinformatics, neuroscience is currently served by a globally distributed ecosystem of neuroscience-centric data repositories, largely specialized around data types. To make neuroscience data findable, accessible, interoperable, and reusable requires the coordination across different stakeholders, including the researchers who produce the data, data repositories who make it available, the aggregators and indexers who field search engines across the data, and community organizations who help to coordinate efforts and develop the community standards critical to FAIR. The International Neuroinformatics Coordinating Facility has led efforts to move neuroscience toward FAIR, fielding several resources to help researchers and repositories achieve FAIR. In this perspective, I provide an overview of the components and practices required to achieve FAIR in neuroscience and provide thoughts on the past, present and future of FAIR infrastructure for neuroscience, from the laboratory to the search engine.
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