Scientific Data is inviting submissions that release data underlying influential research papers published three or more years ago, for potential inclusion in a special collection to be launched in 2018. In particular, we are encouraging submissions that describe important datasets that were not practical to share online with the original publication, due to technical constraints or a lack of appropriate data repositories at the time.
To be considered for publication among the first papers in this collection, manuscripts should be submitted to the editorial office by 1st December 2017.
Data associated with publications disappear at an alarming rate when not archived in formal data repositories (see Vines et al. 2013). This undermines the reliability of “share upon request” data policies used by many journals, and threatens the integrity of the scientific record as a whole. New data repositories offer researchers more stable ways to share their data, and also help ensure that data are as ‘FAIR’ as possible (learn more about the FAIR Data Principles). Excellent options are now available across a wide range of disciplines and for many complex and challenging data-types. But, while journals are increasingly promoting formal data deposition as part of their policies, there remains little incentive for researchers to return to their past studies and release older datasets.
Scientific Data is releasing this call for submissions to incentivize authors to archive and publish their older datasets before they disappear, and to highlight the value that older datasets can have for current research. Interested researchers are encouraged to explore our list of recommended data repositories to see if there are new options for datasets generated in their past work, or to contact us directly for impartial advice on repositories that will be suitable for their work. Researchers may wish to see the two Data Descriptors below for past relevant examples published at the journal:
- Plooij, F. X. et al. Longitudinal recordings of the vocalizations of immature
Gombe chimpanzees for developmental studies (2014).
- Cowley, G. S. et al. Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies (2014).
Authors will be asked to deposit their datasets to an approved data repository according to the policies of the journal. Data must be released to the wider research community upon publication of the Data Descriptor, under appropriately open terms that permit wide reuse in both academic and commercial settings.
Scientific Data does not make accept or reject decisions based on the perceived impact or importance of the research associated with data submitted to the journal, and welcomes submissions describing datasets that have not been used in previous publications. This call for submissions does not represent a deviation from that policy. Datasets that are not viewed as fitting the scope of this special collection will still be considered for publication in the journal according to our normal editorial standards.
Interested in publishing in the ‘Rescue your data’ collection?
If you would like to make a pre-submission enquiry, or have any questions, please contact the Managing Editor, Andrew Hufton: email@example.com