Call for Papers - Scientific Data - Politics and elections data Collection

Scientific Data is currently welcoming submissions of Data Descriptors to a Politics and elections data Collection. A data descriptor is a non-traditional article type that describes externally deposited data.

They provide detailed descriptions of research datasets, including the methods used to collect the data and technical analyses supporting the quality of the measurements. Data Descriptors, examples of which can be found here, focus on helping others reuse data, rather than testing hypotheses, or presenting new interpretations, results or in-depth analyses. You only need to share and describe useful data, rather than communicate results, to be able to contribute a paper.

If you are interested in preparing a manuscript for consideration at Scientific Data as part of this Collection, please let us know and I would be happy to provide further detail. Submissions will be welcomed at any point up until 30th September 2024, but if you are unable to submit a manuscript before this date, please let us know as we may be able to be flexible.

To submit your manuscript for consideration at Scientific Data as part of this Collection, please follow the steps detailed on this page. When submitting your manuscript via the online submission system, please choose the ‘Politics and elections data’ Collection title from the Special Section dropdown menu on the submission form. Please be sure to express your interest in the Collection in your cover letter or Manuscript Comment field on the submission system. All manuscripts will be considered according to our editorial policies. Unfortunately, we cannot guarantee that any individual paper will be included in the Collection.

This article Collection is a great opportunity to contribute to sharing and describing open datasets in this exciting field of research, promote your contributions for others to use and cite, and gain credit for the work.

Please don't hesitate to let us know if you have any questions: 

Jose M. Pavía, pavia@uv.es
Samuel Baltz, sbaltz@umich.edu
Faija Miah, faija.miah@springernature.com