中文簡介

GigaScience的目標是通過提高分析和數據傳播、組織、理解和使用的重現性，從而徹底改變出版業。作為一份開放獲取和開放數據的期刊，我們出版了來自生命和生物醫學科學各個領域的“大數據”研究的所有研究對象(數據、軟件工具和工作流)。這些資源的管理使用科學數據管理和管理的公平原則，即研究數據應該是可查找的、可訪問的、可互操作的和可重用的。為了實現我們的目標，該雜志采用了一種新穎的出版格式:一種將標準稿件出版與廣泛的數據庫連接起來的格式，該數據庫包含所有相關數據，并提供數據分析工具和云計算資源。GigaDB提供了出版的手稿和相關支持數據之間的直接聯系。我們還建立了GigaGalaxy，一個基于星系的數據分析平臺來托管計算方法和工作流，在一個更容易訪問和重現的環境中最大化地使用我們論文中的數據、工具和工作流。我們的范圍不僅包括“基因組”類型的數據和目前由大型公共存儲庫提供服務的高通量生物學領域，還包括越來越多難以訪問的數據，如成像、神經科學、生態學、隊列數據、系統生物學和其他新型大規模可共享數據。為開放科學開放存取和開放數據GigaScience發布的所有文章和內容(包括博客和同行的評論)都可以在發布后立即免費永久地在線訪問，無需支付訂閱費或注冊障礙。所有軟件都是在開放源碼計劃(OSI)批準的開放源碼許可下發布的，并在公共領域CC0豁免下提供支持數據。有關我們的開放存取政策和支持這些努力的文章處理費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據的原則，可重復性、可用性和實用性是我們發布的關鍵標準，而不是對影響的主觀評估。實現這一目標的關鍵是我們開放、集成和定制的GigaDB存儲庫，它可以幫助為所有研究對象提供一個家。開放的、可編程的數據和元數據是可重現性研究的關鍵。通過與協議和計算工作流存儲庫和平臺的集成，可進一步增強可重現性。GigaScience通過與bioRxiv預印版服務器和Publons平臺的集成，鼓勵發表前的討論和更快的科學交流，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。

　　英文簡介

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.

　　近年期刊自引率趨勢圖

　　JCR分區

JCR分區等級	JCR所屬學科	分區	影響因子
Q1	MULTIDISCIPLINARY SCIENCES	Q1	7.658

　　近年期刊影響因子趨勢圖

　　CiteScore數值

CiteScore	SJR	SNIP	學科類別	分區	排名	百分位
11.60	2.568	1.905	大類：Medicine 小類：Health Informatics	Q1	5 / 109	95%
			大類：Medicine 小類：Computer Science Applications	Q1	40 / 747	94%

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