"Archiving" in the context of information sciences means a process of curation (a.k.a. careful selection and description), preservation, and often sharing.
Archiving data is one of the last phases in the research lifecycle. Here are a few things to keep in mind while your project is underway in order to support this final phase of your research:
If a given dataset is not useful or understandable, then perhaps it should not be archived. If there is any confusion, it is always best to speak with the staff at the data archive or repository you have selected. They will be able to review your data and documentation to better inform you of your data's archiving and preservation needs.
The resources below are repositories dedicated to sharing and distributing code to increase searchability and accessibility.
If you are interested in preserving your code and getting a DOI, check out "Making Your Code Citable," or this GitHub browser widget.