GigaScience

GigaScience的目标是通过提高分析和数据传播、组织、理解和使用的重现性，从而彻底改变出版业。作为一份开放获取和开放数据的期刊，我们出版了来自生命和生物医学科学各个领域的“大数据”研究的所有研究对象(数据、软件工具和工作流)。这些资源的管理使用科学数据管理和管理的公平原则，即研究数据应该是可查找的、可访问的、可互操作的和可重用的。为了实现我们的目标，该杂志采用了一种新颖的出版格式:一种将标准稿件出版与广泛的数据库连接起来的格式，该数据库包含所有相关数据，并提供数据分析工具和云计算资源。GigaDB提供了出版的手稿和相关支持数据之间的直接联系。我们还建立了GigaGalaxy，一个基于星系的数据分析平台来托管计算方法和工作流，在一个更容易访问和重现的环境中最大化地使用我们论文中的数据、工具和工作流。我们的范围不仅包括“基因组”类型的数据和目前由大型公共存储库提供服务的高通量生物学领域，还包括越来越多难以访问的数据，如成像、神经科学、生态学、队列数据、系统生物学和其他新型大规模可共享数据。为开放科学开放存取和开放数据GigaScience发布的所有文章和内容(包括博客和同行的评论)都可以在发布后立即免费永久地在线访问，无需支付订阅费或注册障碍。所有软件都是在开放源码计划(OSI)批准的开放源码许可下发布的，并在公共领域CC0豁免下提供支持数据。有关我们的开放存取政策和支持这些努力的文章处理费的更多信息可以在这里找到。我们的原则基于公开和公平数据的原则，可重复性、可用性和实用性是我们发布的关键标准，而不是对影响的主观评估。实现这一目标的关键是我们开放、集成和定制的GigaDB存储库，它可以帮助为所有研究对象提供一个家。开放的、可编程的数据和元数据是可重现性研究的关键。通过与协议和计算工作流存储库和平台的集成，可进一步增强可重现性。GigaScience通过与bioRxiv预印版服务器和Publons平台的集成，鼓励发表前的讨论和更快的科学交流，从而使研究周期更加透明和开放，从而将citable DOIs归功于审稿人。

GigaScience aims to revolutionize publishing by promoting reproducibility of analyses and data dissemination, organization, understanding, and use. As an open access and open-data journal, we publish ALL research objects (data, software tools and workflows) from ''big data'' studies across the entire spectrum of life and biomedical sciences. These resources are managed using the FAIR Principles for scientific data management and stewardship that state that research data should be Findable, Accessible, Interoperable and Reusable.To achieve our goals, the journal has a novel publication format: one that links standard manuscript publication with an extensive database that hosts all associated data and provides data analysis tools and cloud-computing resources. GigaDB provides a direct link between the published manuscript and the relevant supporting data. We have also built GigaGalaxy, a Galaxy-based data analysis platform to host computational methods and workflows, maximizing use of the data, tools and workflows in our papers in a more accessible and reproducible environment.Our scope covers not just ''omic'' type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale sharable data.Open Access and Open Data for Open ScienceAll articles and content (including blogs and peer reviews) published by GigaScience are made freely and permanently accessible online immediately upon publication, without subscription charges or registration barriers. All software is published under Open Source Initiative (OSI)-approved open source licences, and supporting data presented under a public domain CC0 waiver. Further information about our open access policies and our article processing charges to support these efforts can be found here.Our PrinciplesBuilt upon the principles of open and FAIR data, reproducibility, usability and utility are our key criteria for publication rather than subjective assessments of impact. Key to achieving this is our open, integrated and custom built GigaDB repository that can help provide a home to all research objects. Open and citable data and metadata are key to reproducible research. Reproducibility is further enhanced via integration with protocol and computational workflow repositories and platforms. Making the research cycle more transparent and open, GigaScience encourages pre-publication discussion and faster scientific communication through integration with the bioRxiv pre-print server and the Publons platform to credit reviewers with citable DOIs.