It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.
Research Data Management
This guide will help researchers with managing research data as well as preparing for data management plans required by funders.
Since data is easily lost, digital files are fragile, and formats and storage media become obsolete, a storage strategy for active and archival data is a key component of a data management plan.
"Active" or "working" data refers to data as you collect and access it during the course of a project. Datasets may be expanding as you collect new data, and you may need to access data regularly for processing and analysis. It is important to decide where and how you will store your active data so that it is readily accessible to you but also secure. When making this decision, consider the following:
Anticipated size of dataset
Computational requirements: Large-scale analyses may require high-speed processors and a substantial amount of disk space.
Backup: It is essential that you regularly make one or more backup copies of your data and store backups in geographically separate locations from the master dataset. Keep in mind the Backup Rule of Three: keep an original copy, a second local copy, and a remote copy to mitigate the risk of data loss.
Security: If you are working with sensitive data such as medical data or other human subject data, ensure that the storage system you use meets security standards.
TAMU-CC Data Storage Options
There are several options for data storage on campus:
HPC Research Storage: 491 TBs (terabytes) of shared storage for those that utilize the campus HPC environment. (NSF grant funded)