Big Data Infrastructures for Neuroinformatics

神经信息学大数据基础设施

• 批准号: 1000232010-2017
• 负责人: Glatard, Tristan
• 金额: $ 8.74万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Canada Research Chairs
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=695626
• 关键词: Big; Data; Infrastructures; Neuroinformatics

Reproducibility, the ability to re-generate results obtained by other researchers, is a fundamental principle of the scientific method. Recently, however, numerous studies have challenged the reproducibility of computational experiments in various disciplines, questioning the validity of a wide range of scientific findings. The goal of my research program is to advance Big Data infrastructures to ensure computational reproducibility in the neuroinformatics domain. I will focus particularly on three axes: (1) reproducibility evaluations of data analysis pipelines across infrastructures, (2) automated deployment and configuration of high-performance pipelines, (3) decentralized sharing of Big Data analyses across Web platforms.

复制能力，即复制其他研究人员获得的结果的能力，是科学方法的基本原则。然而，最近，许多研究对各个学科的计算实验的可重复性提出了挑战，对广泛的科学发现的有效性提出了质疑。 我的研究计划的目标是推进大数据基础设施，以确保在神经信息学领域的计算再现性。我将特别关注三个方面：（1）跨基础设施的数据分析管道的可重复性评估，（2）高性能管道的自动化部署和配置，（3）跨Web平台的大数据分析的分散共享。