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The dataset supporting the conclusions of this article is available in the Open Science Framework repository, https://osf.io/9gfqx/.
The datasets supporting the conclusions of this article (complete survey and responses obtained) are available in the Open Science Framework repository (Additional file 1).
Three datasets supporting the conclusions of this article are available in the Open Science Framework repository https://osf.io/3htcp/files/ in the format Microsoft Excel (doi 10.17605/OSF.IO/3HTCP); explanations are added to the files.
The datasets supporting the conclusions of this article is have been included within the article with the additional data being available in the Open Science Framework repository [unique persistent identifier and hyperlink to dataset(s) in https://osf.io/5bwfg/. The authors declare that they have no competing of interests.
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In parallel with the advancement of various frameworks, repositories and platforms are efforts aimed at establishing data interchange formats for encoding information.
According to the literature, the description of the resources may be registered in public discovery frameworks, or repositories, so that they can be discovered by VN requestors.
We then describe the design of a repository framework that addresses these requirements.
To design, implement and evaluate a repository framework for preservation of research outputs based on hybrid cloud.
The main contributions of this work are: (i) To design, implement and evaluate a repository framework for preservation of research outputs based on hybrid cloud.
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Recently the concept of a data lake [4], a flat repository framework that holds a vast amount of raw data in their native formats including structured, semi-structured, and unstructured data, has emerged in the data management field.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com