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数字出版并不够:科学传播中“蓝图”的必要性

Digital publishing isn't enough: the case for 'blueprints' in scientific communication.

作者信息

Jennings-Antipov Laura D, Gardner Timothy S

机构信息

Riffyn, Oakland, CA, U.S.A.

出版信息

Emerg Top Life Sci. 2018 Dec 21;2(6):755-758. doi: 10.1042/ETLS20180165.

Abstract

Since the time of Newton and Galileo, the tools for capturing and communicating science have remained conceptually unchanged - in essence, they consist of observations on paper (or electronic variants), followed by a 'letter' to the community to report your findings. These age-old tools are inadequate for the complexity of today's scientific challenges. If modern software engineering worked like science, programmers would not share open source code; they would take notes on their work and then publish long-form articles about their software. Months or years later, their colleagues would attempt to reproduce the software based on the article. It sounds a bit silly, and yet even, this level of prose-based methodological discourse has deteriorated in science communication. Materials and Methods sections of papers are often a vaguely written afterthought, leaving researchers baffled when they try to repeat a published finding. It's time for a fundamental shift in scientific communication and sharing, a shift akin to the advent of computer-aided design and source code versioning. Science needs reusable 'blueprints' for experiments replete with the experiment designs, material flows, reaction parameters, data, and analytical procedures. Such an approach could establish the foundations for truly open source science where these scientific blueprints form the digital 'source code' for a supply chain of high-quality innovations and discoveries.

摘要

自牛顿和伽利略时代以来,用于记录和交流科学的工具在概念上一直没有改变——本质上,它们包括在纸上(或电子形式)进行观察,然后向科学界发送一封“信件”来报告你的发现。这些古老的工具不足以应对当今科学挑战的复杂性。如果现代软件工程像科学那样运作,程序员就不会共享开源代码;他们会记录自己的工作,然后发表关于其软件的长篇文章。数月或数年之后,他们的同事会尝试根据文章来重现该软件。这听起来有点荒谬,然而,即使是这种基于散文的方法性论述在科学交流中也已经退化。论文的材料与方法部分往往是事后模糊撰写的,这使得研究人员在试图重复已发表的研究结果时感到困惑。现在是科学交流与共享发生根本性转变的时候了,这种转变类似于计算机辅助设计和源代码版本控制的出现。科学需要可重复使用的实验“蓝图”,其中要完整包含实验设计、材料流程、反应参数、数据和分析程序。这样一种方法可以为真正的开源科学奠定基础,在这种科学中,这些科学蓝图构成了高质量创新与发现供应链的数字“源代码”。

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