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Call for submissions: Reproducible data processing

Call for Submissions

Special Article Collection on
Reproducible data processing

In collaboration with Harvard Dataverse

Scientific Data is inviting submissions that provide compelling examples of how portable computing technologies can be used to create transparent, reproducible descriptions of data processing workflows. Submissions considered for this collection should describe valuable research datasets that involve some form of computational processing in their production. Authors should provide source code for all data processing steps in a way that would allow others, including referees, to easily understand and execute all processing steps.

Submitted articles may be considered for inclusion in a special article collection.

Interested researchers are encouraged to first review our criteria for publication for Data Descriptors. Submissions may be from a wide range of research disciplines including fields in both the natural and social sciences.

Authors will have the option to host their data and processing code at Code Ocean. Code Ocean is a computational reproducibility platform that hosts code and data in a cloud-based environment. Users can view, execute and modify the computational workflow in the browser and reproduce the outputs described in the accompanying Data Descriptor without the need to install software locally. Authors may also choose to submit their Data Descriptor as a fully integrated “reproducible manuscript”, using technologies such as Jupyter or knitr.

Researchers will be encouraged to use the Harvard Dataverse to host their data, whenever appropriate. Staff at Harvard Dataverse will assist participating authors in passing code and data files to Code Ocean.

Interested authors should contact the journal before submission so that we can advise them on the best way to host their data, code and manuscript files.

Acceptance for publication will be based on the reuse value of the described dataset, the technical rigour of the procedures used to generate the data, and the transparency of all data processing steps.

Upon publication, data and code must be released to the wider research community under appropriate open data and open source licenses.

To be considered for publication in the potential special collection, manuscripts should be submitted to the editorial office via our online system by 15th April 2019; submissions after this date are welcome, and may still be considered for inclusion in this special collection on a case-by-case basis.

Interested in publishing in this special collection?
If you have any questions or would like to make a presubmission enquiry, please contact the Chief Editor, Andrew Hufton, with appropriate details:

Scientific Data is an open-access, peer-reviewed journal for descriptions of scientifically valuable datasets. Our primary article-type, the Data Descriptor, is designed to make your data more discoverable, interpretable and reusable.


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