Data deposit is the process of transferring custodianship of research data to a third-party, such as a research data repository. Data deposit is not the same as data sharing. You may choose to deposit your data in a repository that enables you to share your data openly, in a repository that allows restricted access, in a closed archive, or with a designated custodian to preserve long-term access.
Data package
A data package is a collection of data files and documentation created to intentionally ensure your data remains accessible. Your data package will differ from your working data, typically containing only essential files. It may also involve renaming and reorganization of files and creating new documentation. The goal is to create a data package that someone other than you or your research group could understand.
Preparing data for deposit
Creating your data package may include doing certain actions to ensure your data can be properly understood, interpreted, and reused. These actions may include:
- Checking for missing files and data documentation
- Creating new documentation to provide information about how data can be accessed and used (including information about data licenses)
- Arranging and describing files
- Detecting and fixing code and other quality assurance issues
- Screening for privacy disclosure risk
- Transforming file formats for long term access
- Reviewing and augmenting metadata
Resources
Library resources
- README for Data Deposit: Template - this template can be used to create a README file to include in a data deposit.
- README for Data Deposit: Template Guide - this guide provides additional information and guidance about specific sections and fields in the README for Data Deposit Template.
Library services
The library provides support for:
- Understanding how to create a data package
- Understanding and navigating data curation
External resources
- Primer - Curation (Digital Research Alliance of Canada)
- Brief Guide - Data Curation (Digital Research Alliance of Canada)
- Data Curation Primers (Data Curation Network)
- The DCN CURATE(D) Steps (Data Curation Network)
- Curating Datasets for Reproducibility (University of Victoria)