Provide a concise and informative title for your dataset that accurately reflects its content.
In this section, provide an overview of your dataset and describe the project in which the dataset was collected. Highlight the purpose, scope, and potential uses of your dataset. Also, consider including links to relevant publications or resources that provide additional context.
Include any necessary prerequisites for using your dataset, such as specific software or hardware requirements. Provide clear instructions for how to access, download, and use your data files.
Describe the organization of your data package, including the contents of each folder and the files it contains. Use tables or file trees to make it easy for users to understand your data structure. Consider also including any related datasets that users might find useful.
Provide a clear and consistent naming convention for your dataset files. Explain the meaning behind the naming conventions used.
Describe the file format(s) used in your dataset and the software required to open them.
If applicable, describe the research questions or hypotheses that guided the collection of your dataset. Explain the data collection methods, including any ethical considerations taken into account.
Provide a codebook that explains the variables in your dataset. This is particularly important for tabular data, but it is useful for any other type of file as well. Include at least the variable name, a brief description, and the data type. Use a format similar to the following:
| Variable | Description | Data type |
|---|---|---|
| my_var | Description of the variable | Data type, e.g. string, integer |
Include a license that allows others to use and share your work. Consider using an open data license such as the Creative Commons licenses. For example:
This work is licensed under a Creative Commons Attribution 4.0 International License.
Provide clear instructions on how to cite your dataset or related publications in a research paper or publication.
Include contact information for questions or comments about your dataset. You can also provide clear instructions for how users can provide feedback, contribute, or suggest improvements to your work.