How do we get the data to build computational models?

机译：我们如何获得数据以建立计算模型？

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We present a new approach to building radically distributed databases of neuroscience data. It aims to make available to modelers the huge amount of useful experimental data and notes which currently sits on experimenters PCs and lab notebooks. The approach has two components. The initial phase is a user friendly desktop application which experimental neuroscientists can use to markup data and build small catalogs of their data. The second phase is a server application which acts like a "smarter Google" which is able to combine and index catalogs from multiple researchers and labs so that modelers can download local copies of data relevant to their study.

机译：我们提出了一种建立神经科学数据的根本分布式数据库的新方法。它旨在为建模人员提供大量有用的实验数据和注释，这些数据和注释目前位于实验人员的PC和实验室笔记本上。该方法有两个组成部分。初始阶段是用户友好的桌面应用程序，实验神经科学家可以使用它来标记数据并建立其数据的小目录。第二阶段是一个服务器应用程序，其作用类似于“更智能的Google”，它能够合并和索引来自多个研究人员和实验室的目录，以便建模人员可以下载与他们的研究相关的本地数据副本。

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来源
《Computational Neuroscience Meeting(CNS03); 20030705-09; Alicante(ES)》|2003年|P.1103-1108|共6页
会议地点 Alicante(ES)
作者
F. Howell; R. Cannon; N. Goddard;
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作者单位

Institute for Adaptive and Neural Computation, Division of Informatics, University of Edinburgh, 5 Forrest Hill, Edinburgh EH1 2QL, Scotland, UK;

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会议组织
原文格式 PDF
正文语种 eng
中图分类生理学;
关键词
data management; databases; XML; NeuroML;

机译：数据管理;数据库; XML; NeuroML;
入库时间 2022-08-26 14:29:48

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How do we get the data to build computational models?

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