In section C of Element 1: Data Type, you're asked to briefly list the metadata, other relevant data, and associated documentation (e.g. study protocols, and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data 

NIH's description of metadata and documentation is helpful: "Metadata and other documentation associated with a dataset allow users to understand how the data were collected and how to interpret the data. Importantly, this ensures that others can use the dataset and prevents misuse, misinterpretation, and confusion.

Your documentation can describe the project (e.g. protocols, data collection methods, structure and organization of datafiles) and/or the dataset(s) (e.g. variable names and descriptions, codes or classification schemes used, algorithms used to transform data such as computer code.)

Documentation often takes the form of protocols, readme files, data dictionaries, and/or codebooks, depending on the type of research. 

Example:

Protocols and details regarding the instrument settings will be provided in a plain text README document. Variable definitions related to the collected data will be recorded in a data dictionary and available with the shared datasets. Computer code used for data transformation and analysis will be available publicly through GitHub.

Learn about methods of documenting your data