The Caltech Library is happy to provide guidance on where and how to share data in compliance with funder and journal mandates.
We recommend researchers share data in subject- or data-type-specific data repositories where that is an expected practice in your research field. For example, the NIH Genomic Data Sharing policy requires that certain genetic data from projects funded by NIH must be shared in an appropriate data repository.
Caltech Library offers a free data sharing service, CaltechDATA at https://data.caltech.edu, that accepts any type of data associated with Caltech projects. CaltechDATA offers standard data preservation and DOI (permanent identifier) services. We also offer services, at an additional cost, for preserving large volumes of data (> 500 GB); please contact us to discuss options and costs. Find out more information or read the CaltechDATA FAQ or contact us at email@example.com.
If you have questions about choosing an appropriate subject repository, using CaltechDATA, or finding another generalist data repository, please contact firstname.lastname@example.org and we will be happy to assist.
The Caltech Library developed several resources to help with the management of scientific research data.
To learn about a range of data management topics, we encourage you to borrow the book "Data Management for Researchers: Organize, Maintain, and Share your Data for Research Success" (Call Number: Q180.55.E4 B75 2015), which was written by Caltech's Biology & Biological Engineering Librarian.
A shorter summary of 10 data management strategies is available in the open-access article "Foundational Practices of Research Data Management", which was co-written by Caltech's Biology & Biological Engineering Librarian.
The naming convention worksheet walks researchers through the process of creating a file naming convention for a group of files. This process includes: choosing metadata, encoding and ordering the metadata, adding version information, and properly formatting the file names.
The close-out checklist describes a range of activities for helping ensure that research data are properly managed at the end of a project or at researcher departure. Activities include: making stewardship decisions, preparing files for archiving, sharing data, and setting aside important files in a "FINAL" folder.
This handout summarizes a range of documentation methods for research data, including: laboratory notebook, e-lab notebook, README.txt, template, data dictionary, codebook, metadata schema, standard, and taxonomy. The handout describes when to apply each documentation type and what information the method covers.