## Summary

Archiving research data is a critical final step in the research data lifecycle. It ensures that data remains accessible, understandable, and reusable over the long term, both for your future self and for other researchers. Proper archiving supports transparency, replicability, and the broader goals of open science.

A well-archived dataset includes not only the data itself but also comprehensive metadata and documentation. Choosing an appropriate repository, preferably a trusted, discipline-specific or institutional one helps safeguard the data against loss or degradation, and ensures that it can be cited correctly.

By planning for archiving early in your research process and adhering to best practices, you contribute to a more robust and reliable scientific record. Archiving is not just about storage, it's about preserving the value of your research for years to come.

Task 1:

Choose a Repository
Choose a suitable repository for archiving your (real or hypothetical) research dataset. Briefly answer:

1. Is the repository discipline-specific, institutional, or general-purpose?

2. What features make it appropriate for your data?

3. Does the repository provide a DOI or other persistent identifier?