Ideally, a data review should discuss the quality, completeness and reusability of a given data collection, as well as the relevance of the dataset and its potential contribution to the scientific debate. There is no single 'gold standard' for what a data review should look like or contain, but the following questions may help you to write a useful data review:

• What exactly is the data about and what kind of files does the data collection contain (in terms of subject, time, scope, geographical information, formats, size, etc.)?
• Is the data easy to read and use?
• Are the data files properly cleaned, logically organised, and internally consistent?
• Are the data files complete and consistent with the description?
• Are the data collection methods described well enough to be understood and replicated by others?
• Is anything missing from the methodological description?
• What about the reliability, validity, relevance and comparability of the data?
• Are limitations, gaps and potential sources of error (including methods, calculation and interpretation) adequately addressed?
• Is there an accurate description how and where the data can be accessed and used for further research (including information on licences, access, URL)?
• Are there any legal restrictions or ethical considerations related to the collection or secondary use of the data?
• Is the dataset used for academic research and/or discussed in academic publications?