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3 open source tools for scientific publishing
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======
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One industry that lags behind others in the adoption of digital or open source tools is the competitive and lucrative world of scientific publishing. Worth over £19B ($26B) annually, according to figures published by Stephen Buranyi in [The Guardian][1] last year, the system for selecting, publishing, and sharing even the most important scientific research today still bears many of the constraints of print media. New digital-era technologies present a huge opportunity to accelerate discovery, make science collaborative instead of competitive, and redirect investments from infrastructure development into research that benefits society.
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The non-profit [eLife initiative][2] was established by the funders of research, in part to encourage the use of these technologies to this end. In addition to publishing an open-access journal for important advances in life science and biomedical research, eLife has made itself into a platform for experimentation and showcasing innovation in research communication—with most of this experimentation based around the open source ethos.
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Working on open publishing infrastructure projects gives us the opportunity to accelerate the reach and adoption of the types of technology and user experience (UX) best practices that we consider important to the advancement of the academic publishing industry. Speaking very generally, the UX of open source products is often left undeveloped, which can in some cases dissuade people from using it. As part of our investment in OSS development, we place a strong emphasis on UX in order to encourage users to adopt these products.
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All of our code is open source, and we actively encourage community involvement in our projects, which to us means faster iteration, more experimentation, greater transparency, and increased reach for our work.
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The projects that we are involved in, such as the development of Libero (formerly known as [eLife Continuum][3]) and the [Reproducible Document Stack][4], along with our recent collaboration with [Hypothesis][5], show how OSS can be used to bring about positive changes in the assessment, publication, and communication of new discoveries.
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### Libero
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Libero is a suite of services and applications available to publishers that includes a post-production publishing system, a full front-end user interface pattern suite, Libero's Lens Reader, an open API, and search and recommendation engines.
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Last year, we took a user-driven approach to redesigning the front end of Libero, resulting in less distracting site “furniture” and a greater focus on research articles. We tested and iterated all the key functional areas of the site with members of the eLife community to ensure the best possible reading experience for everyone. The site’s new API also provides simpler access to content for machine readability, including text mining, machine learning, and online application development.
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The content on our website and the patterns that drive the new design are all open source to encourage future product development for both eLife and other publishers that wish to use it.
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### The Reproducible Document Stack
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In collaboration with [Substance][6] and [Stencila][7], eLife is also engaged in a project to create a Reproducible Document Stack (RDS)—an open stack of tools for authoring, compiling, and publishing computationally reproducible manuscripts online.
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Today, an increasing number of researchers are able to document their computational experiments through languages such as [R Markdown][8] and [Python][9]. These can serve as important parts of the experimental record, and while they can be shared independently from or alongside the resulting research article, traditional publishing workflows tend to relegate these assets as a secondary class of content. To publish papers, researchers using these languages often have little option but to submit their computational results as “flattened” outputs in the form of figures, losing much of the value and reusability of the code and data references used in the computation. And while electronic notebook solutions such as [Jupyter][10] can enable researchers to publish their code in an easily reusable and executable form, that’s still in addition to, rather than as an integral part of, the published manuscript.
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The [Reproducible Document Stack][11] project aims to address these challenges through development and publication of a working prototype of a reproducible manuscript that treats code and data as integral parts of the document, demonstrating a complete end-to-end technology stack from authoring through to publication. It will ultimately allow authors to submit their manuscripts in a format that includes embedded code blocks and computed outputs (statistical results, tables, or graphs), and have those assets remain both visible and executable throughout the publication process. Publishers will then be able to preserve these assets directly as integral parts of the published online article.
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### Open annotation with Hypothesis
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Most recently, we introduced open annotation in collaboration with [Hypothesis][12] to enable users of our website to make comments, highlight important sections of articles, and engage with the reading public online.
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Through this collaboration, the open source Hypothesis software was customized with new moderation features, single sign-on authentication, and user-interface customization options, giving publishers more control over its implementation on their sites. These enhancements are already driving higher-quality discussions around published scholarly content.
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The tool can be integrated seamlessly into publishers’ websites, with the scholarly publishing platform [PubFactory][13] and content solutions provider [Ingenta][14] already taking advantage of its improved feature set. [HighWire][15] and [Silverchair][16] are also offering their publishers the opportunity to implement the service.
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### Other industries and open source
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Over time, we hope to see more publishers adopt Hypothesis, Libero, and other projects to help them foster the discovery and reuse of important scientific research. But the opportunities for innovation eLife has been able to leverage because of these and other OSS technologies are also prevalent in other industries.
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The world of data science would be nowhere without the high-quality, well-supported open source software and the communities built around it; [TensorFlow][17] is a leading example of this. Thanks to OSS and its communities, all areas of AI and machine learning have seen rapid acceleration and advancement compared to other areas of computing. Similar is the explosion in usage of Linux as a cloud web host, followed by containerization with Docker, and now the growth of Kubernetes, one of the most popular open source projects on GitHub.
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All of these technologies enable organizations to do more with less and focus on innovation instead of reinventing the wheel. And in the end, that’s the real benefit of OSS: It lets us all learn from each other’s failures while building on each other's successes.
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We are always on the lookout for opportunities to engage with the best emerging talent and ideas at the interface of research and technology. Find out more about some of these engagements on [eLife Labs][18], or contact [innovation@elifesciences.org][19] for more information.
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via: https://opensource.com/article/18/3/scientific-publishing-software
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作者：[Paul Shanno][a]
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译者：[tomjlw](https://github.com/tomjlw)
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校对：[校对者ID](https://github.com/校对者ID)
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本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
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[a]:https://opensource.com/users/pshannon
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[1]:https://www.theguardian.com/science/2017/jun/27/profitable-business-scientific-publishing-bad-for-science
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[2]:https://elifesciences.org/about
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[3]:https://elifesciences.org/inside-elife/33e4127f/elife-introduces-continuum-a-new-open-source-tool-for-publishing
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[4]:https://elifesciences.org/for-the-press/e6038800/elife-supports-development-of-open-technology-stack-for-publishing-reproducible-manuscripts-online
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[5]:https://elifesciences.org/for-the-press/81d42f7d/elife-enhances-open-annotation-with-hypothesis-to-promote-scientific-discussion-online
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[6]:https://github.com/substance
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[7]:https://github.com/stencila/stencila
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[8]:https://rmarkdown.rstudio.com/
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[9]:https://www.python.org/
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[10]:http://jupyter.org/
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[11]:https://elifesciences.org/labs/7dbeb390/reproducible-document-stack-supporting-the-next-generation-research-article
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[12]:https://github.com/hypothesis
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[13]:http://www.pubfactory.com/
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[14]:http://www.ingenta.com/
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[15]:https://github.com/highwire
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[16]:https://www.silverchair.com/community/silverchair-universe/hypothesis/
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[17]:https://www.tensorflow.org/
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[18]:https://elifesciences.org/labs
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[19]:mailto:innovation@elifesciences.org
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3款用于学术发表的开源工具
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======
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有一个行业在采用数字或者开源工具方面已落后其它行业，那就是竞争与利润并存的学术出版业。根据 Stephen Buranyi 去年在 [The Guardian][1] 发表的一份图表，这个估值超过190亿英镑（260亿美元）的行业至今在其选择、发表甚至分享最重要的科学研究的系统方面，仍受限于印刷媒介的诸多限制。全新的数字时代科技展现了一个能够加速探索、推动科学合作性而不是竞争性以及将投入重新从基础建设导向有益社会的研究的巨大的机遇。
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非盈利性的 [eLife 倡议][2] 是由研究的资金赞助方建立，旨在通过使用数字或者开源技术来走出上述僵局。除了为生活中科学和生物医疗方面的重大成就出版开放式获取的杂志，eLife 已将自己变成了一个在研究交流方面的创新实验窗口——而大部分的实验都是基于开源精神的。
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参与开源出版项目给予我们加速接触、采用科学技术，提升用户体验的机会。我们认为这种机会对于推动学术出版行业是重要的。大而化之地说，开源产品的用户体验经常是有待开发的，而有时候这种情况会阻止其他人去使用它。作为我们在 OSS 开发中投入的一部分，为了鼓励更多用户使用这些产品，我们十分注重用户体验。
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我们所有的代码都是开源的并且我们也积极鼓励开源社区参与进我们的项目中。这对我们来说意味着更快的迭代、更多的实验、更大的透明度，同时也拓宽了我们工作的外延。
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我们现在参与的项目，例如 Libero （之前称作 [eLife Continuum][3]）和 [可复制文档栈][4] 的开发以及我们最近和 [Hypothesis][5] 的合作，展示了 OSS 是如何在校队、发表以及新发现的沟通方面带来正面影响的。
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### Libero
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Libero 是面向发布者的服务及应用套餐，它包括一个后生产出版系统、整套前端用户界面、Libero 的棱镜阅读器、一个开放式的API以及一个搜索推荐引擎。
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去年我们采取了用户导向的途径重新设计了 Libero 的前端，做出了一个使用户较少地分心并更多地集中注意在研究文章上的站点。我们和 eLife 社区成员测试并迭代了站点所有的核心功能以确保给所有人最好的阅读体验。网站的新 API 也给可供机器阅读的内容提供了更简单的访问途径，其中包括文字挖掘、机器学习以及在线应用开发。我们网站上的内容以及引领新设计的样式都是开源的，以鼓励 eLife 和其它想要使用它的发布者后续的开发。
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### 可复制文档栈
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在与 [Substance][6] 和 [Stencila][7] 的合作下，eLife 也参与了一个项目来创建可复制的文档栈（RDS）——一个开放式的创作、编纂以及在线出版可复制的计算型手稿的工具栈。
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今天越来越多的研究员能够通过 [R、Markdown][8] 和 [Python][9] 等语言记录他们的计算型实验。这些可以作为实验记录的重要部分，但是尽管它们可以通过最终的研究文章独立地分享，传统出版流程经常将它们视为次级内容。为了发表论文，使用这些语言的研究员除了将他们的计算结果用图片的形式“扁平化”提交外别无他法。但是这导致了许多实验价值和代码和计算数据可重复利用性的流失。诸如 [Jupyter][10] 的电子笔记本解决方案确实可以使研究员以一种可重复利用、可执行的简单形式发布，但是这种方案仍然独立于整个手稿发布过程之外，而不是集成在其中。
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[可复制文档栈][11] 项目着眼于通过开发、发布一个能够把代码和数据集成在文档自身的产品雏形来突出这些挑战并阐述一个端对端的从创作到出版的完整科技。它将最终允许用户以一种包含嵌入代码块和计算结果（统计结果、图表或图片）的形式提交他们的手稿并在出版过程中保留这些可视、可执行的部分。那时发布者就可以将这些作为发布的在线文章的整体所保存。
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### 用 Hypothesis 进行开放式注解
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最近，我们与 [Hypothesis][12] 合作引进了开放式注解，使得我们网站的用户们可以写评语、高亮文章重要部分以及与在线阅读的群体互动。
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通过这样的合作，开源的 Hypothesis 软件被定制得更具有现代化的特性如单次登录验证、用户界面定制选项，给予了发布者在他们自己网站上更多的控制。这些提升正引导着关于发表的学术内容高质量的讨论。
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这个工具可以无缝集成进发布者的网站，学术发表平台 [PubFactory][13] 和内容解决方案供应商 [Ingenta][14] 已经利用了它优化后的特性集。[HighWire][15] 和 [Silverchair][16] 也为他们的发布者提供了实施这套方案的机会。
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### 其它产业和开源软件
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过段时间，我们希望看到更多的发布者采用 Hypothesis、Libero 以及其它开源软件去帮助他们促进重要科学研究的发现以及循环利用。但是 eLife 所能利用的因这些软件和其它 OSS 科技带来的创新机会在其他产业也很普遍。
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数据科学的世界离不开高质量、强支持的开源软件和围绕它们形成的社区；[TensorFlow][17] 就是这样一个好例子。感谢 OSS 以及其社区，AI 的所有领域和机器学习相比于计算机的其它领域有了迅速的提升和发展。与之类似的是 Linux 云端网页主机、Docker 容器、Github上最流行的开源项目之一的 Kubernetes 使用的爆炸性增长。
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所有的这些科技使得不同团体能够四两拨千斤并集中在创新而不是造轮子上。最后，那才是 OSS 真正的好处：它使得我们从互相的失败中学习，在互相的成功中成长。
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我们总是在寻找与研究和科技界面方面最好的人才和想法交流的机会。你可以在 [eLife Labs][18] 上或者联系 [innovation@elifesciences.org][19] 找到更多这种交流的信息。
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--------------------------------------------------------------------------------
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via: https://opensource.com/article/18/3/scientific-publishing-software
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作者：[Paul Shanno][a]
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译者：[tomjlw](https://github.com/tomjlw)
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校对：[校对者ID](https://github.com/校对者ID)
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本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
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[a]:https://opensource.com/users/pshannon
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[1]:https://www.theguardian.com/science/2017/jun/27/profitable-business-scientific-publishing-bad-for-science
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[2]:https://elifesciences.org/about
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[3]:https://elifesciences.org/inside-elife/33e4127f/elife-introduces-continuum-a-new-open-source-tool-for-publishing
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[4]:https://elifesciences.org/for-the-press/e6038800/elife-supports-development-of-open-technology-stack-for-publishing-reproducible-manuscripts-online
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[5]:https://elifesciences.org/for-the-press/81d42f7d/elife-enhances-open-annotation-with-hypothesis-to-promote-scientific-discussion-online
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[6]:https://github.com/substance
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[7]:https://github.com/stencila/stencila
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[8]:https://rmarkdown.rstudio.com/
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[9]:https://www.python.org/
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[10]:http://jupyter.org/
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[11]:https://elifesciences.org/labs/7dbeb390/reproducible-document-stack-supporting-the-next-generation-research-article
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[12]:https://github.com/hypothesis
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[13]:http://www.pubfactory.com/
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[14]:http://www.ingenta.com/
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[15]:https://github.com/highwire
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[16]:https://www.silverchair.com/community/silverchair-universe/hypothesis/
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[17]:https://www.tensorflow.org/
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[18]:https://elifesciences.org/labs
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[19]:mailto:innovation@elifesciences.org
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