中文簡(jiǎn)介

GigaScience的目標(biāo)是通過(guò)提高分析和數(shù)據(jù)傳播、組織、理解和使用的重現(xiàn)性，從而徹底改變出版業(yè)。作為一份開放獲取和開放數(shù)據(jù)的期刊，我們出版了來(lái)自生命和生物醫(yī)學(xué)科學(xué)各個(gè)領(lǐng)域的“大數(shù)據(jù)”研究的所有研究對(duì)象(數(shù)據(jù)、軟件工具和工作流)。這些資源的管理使用科學(xué)數(shù)據(jù)管理和管理的公平原則，即研究數(shù)據(jù)應(yīng)該是可查找的、可訪問(wèn)的、可互操作的和可重用的。為了實(shí)現(xiàn)我們的目標(biāo)，該雜志采用了一種新穎的出版格式:一種將標(biāo)準(zhǔn)稿件出版與廣泛的數(shù)據(jù)庫(kù)連接起來(lái)的格式，該數(shù)據(jù)庫(kù)包含所有相關(guān)數(shù)據(jù)，并提供數(shù)據(jù)分析工具和云計(jì)算資源。GigaDB提供了出版的手稿和相關(guān)支持?jǐn)?shù)據(jù)之間的直接聯(lián)系。我們還建立了GigaGalaxy，一個(gè)基于星系的數(shù)據(jù)分析平臺(tái)來(lái)托管計(jì)算方法和工作流，在一個(gè)更容易訪問(wèn)和重現(xiàn)的環(huán)境中最大化地使用我們論文中的數(shù)據(jù)、工具和工作流。我們的范圍不僅包括“基因組”類型的數(shù)據(jù)和目前由大型公共存儲(chǔ)庫(kù)提供服務(wù)的高通量生物學(xué)領(lǐng)域，還包括越來(lái)越多難以訪問(wèn)的數(shù)據(jù)，如成像、神經(jīng)科學(xué)、生態(tài)學(xué)、隊(duì)列數(shù)據(jù)、系統(tǒng)生物學(xué)和其他新型大規(guī)?？晒蚕頂?shù)據(jù)。為開放科學(xué)開放存取和開放數(shù)據(jù)GigaScience發(fā)布的所有文章和內(nèi)容(包括博客和同行的評(píng)論)都可以在發(fā)布后立即免費(fèi)永久地在線訪問(wèn)，無(wú)需支付訂閱費(fèi)或注冊(cè)障礙。所有軟件都是在開放源碼計(jì)劃(OSI)批準(zhǔn)的開放源碼許可下發(fā)布的，并在公共領(lǐng)域CC0豁免下提供支持?jǐn)?shù)據(jù)。有關(guān)我們的開放存取政策和支持這些努力的文章處理費(fèi)的更多信息可以在這里找到。我們的原則基于公開和公平數(shù)據(jù)的原則，可重復(fù)性、可用性和實(shí)用性是我們發(fā)布的關(guān)鍵標(biāo)準(zhǔn)，而不是對(duì)影響的主觀評(píng)估。實(shí)現(xiàn)這一目標(biāo)的關(guān)鍵是我們開放、集成和定制的GigaDB存儲(chǔ)庫(kù)，它可以幫助為所有研究對(duì)象提供一個(gè)家。開放的、可編程的數(shù)據(jù)和元數(shù)據(jù)是可重現(xiàn)性研究的關(guān)鍵。通過(guò)與協(xié)議和計(jì)算工作流存儲(chǔ)庫(kù)和平臺(tái)的集成，可進(jìn)一步增強(qiáng)可重現(xiàn)性。GigaScience通過(guò)與bioRxiv預(yù)印版服務(wù)器和Publons平臺(tái)的集成，鼓勵(lì)發(fā)表前的討論和更快的科學(xué)交流，從而使研究周期更加透明和開放，從而將citable DOIs歸功于審稿人。

投稿網(wǎng)址：https://www.editorialmanager.com/giga/default.aspx

英文簡(jiǎn)介

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.