File storage and transfer

Brown Data Risk Classification is a system Brown has developed to classify its information assets into one of four risk-based categories (No Risk, Level 1, Level 2, or Level 3) for the purpose of determining who is allowed to access the information and what security precautions must be taken to protect it against unauthorized access. It is the data and service owner’s responsibility to ensure appropriate security measures are taken depending on the risk classification. If you have any questions or need help, please reach out to the Information Security Group (isg@brown.edu).

A digital object identifier (DOI) is unique and persistent identifier used to identify a physical, digital, or abstract object (e.g., journal article, research report, or data set). The DOI remains constant over the life of the object, and as such, provides a digital, searchable, and persistent link. The Brown University Library will help students, faculty, and staff obtain a DOI for digital assets produced via the scholarly, instructional, research, and administrative activities at Brown. You can learn more here

Many storage services offer the ability to take "snapshots" or backup copies of your data. As the terms suggests, these amount to duplicate copies—frozen at a given point in time—of your data. And if necessary, your data could be restored to a prior snapshot or replication copy of the data.

Are you using these data for teaching purposes, and if so, do you need your students to be able to access the data from with the Canvas learning management system?

Most of the storage services the University offers can accommodate very large data sets. But there are fewer options once your data grows to exceptionally large sized. And for the exceptionally large data sets, these will also often exceed the free allocations that Brown provides—and thus, you might need to pay a small fee for the additional storage.

The "warmth" of a data set is essentially the frequency with which it needs to be accessed or updated. A "hot" data set is one that you are actively working with as part of your model fitting or analysis. A "warm" data set is one that is still sometimes accessed for reading and writing. A "cold" data set is effectively never (or only extremely rarely) accessed. Cold storage is often referred to as "archival storage". So, cold storage solutions are most appropriate when the analysis of the data is complete. That is, when you are done with the data, but you are keeping them around because of either obligations from grants or funding agencies, or just in case they are needed at some later time.