Aims and scope

Scientific Data is an open access journal dedicated to data, publishing descriptions of research datasets and articles on research data sharing from all areas of natural sciences, medicine, engineering and social sciences. It aims to advance the sharing and reuse of scientific data, promote wider data sharing and reuse, and to credit those that share.

Find out more about the key principles that drive Scientific Data

Scientific Data primarily publishes Data Descriptors. These 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 focus on helping others reuse data, rather than testing hypotheses, or presenting new interpretations, methods or in-depth analyses.

Scientific Data also welcomes original articles on the technologies, policies, data standands, platforms and workflows used to support data sharing within a repository use case. 

Scientific Data uses a thorough peer-review process that evaluates the rigour and quality of the experiments used to generate the data and the completeness of the description of the data. The actual data are stored in one or more public, community-recognized repositories, and release of the data is verified as a condition of publication.

Data Descriptors may describe data from new or published studies, and can be published alongside traditional research works. Data Descriptors that describe previously published datasets should provide new content sufficient to merit further publication: for example, updates to important datasets, fuller release of a dataset, or additional information that aids reuse. Please see our policies on complementary and prior publication.