A data descriptor usually links to an openly accessible dataset that has been released independently or associates with datasets published in other conventional research articles as a complementary publication, so that these data can easily be cited, traced, and re-used for further research.

When a data descriptor links to a dataset published in a research article, it will have to provide additional content to merit a new paper, which may include updates to the dataset, a fuller release of the dataset, or useful information to enhance data transparency or reusability.

We ask reviewers to consider the following aspects when reviewing data descriptors:

Data description

• Are the data original, and is the source, well defined?
• Are the methodologies of data collection described with sufficient detail to allow another researcher to reproduce the results?
• Do the metadata accurately describe the data and adhere to relevant disciplinary or international standards?
• Is the copyright license described and appropriate (open licenses are preferred, but authors may use a different license if there is a compelling reason)?

Data quality

• Is the dataset technically sound?
• Were appropriate quality control measures employed and described?
• Are possible sources of error and noise appropriately described?

Data access, archiving, and metadata

• Have the data been archived appropriately with a unique identifier (preferably an assigned doi number)?
• Are the data in a format that can be reused by others (common, non-proprietary formats are preferred)?
• Are the data available for reuse?

For general guidance for peer reviewers, see here.