Managing data access can often feel like busywork for researchers — you're only trying to do good with the data, otherwise you wouldn't have spent all those years in grad school.
However, some of the most rich and useful research data has profound privacy implications. It is essential that the research community remains good stewards of such data, and to this end Redivis provides data managers with robust, highly configurable access control tools.
While absolutely necessary, the Redivis access system is built with researchers' time in mind. Specifically, data access on Redivis is:
Simple: Apply for and manage access to datasets all in one place, using an intuitive and clean UI
Transparent: See all the steps required to gain access before you start out. Customizable access levels allow data owners to share as much information about the dataset as possible — without compromising the underlying security of the data.
Robust: The rules are the rules, and data managers can be confident that researchers are only accessing and working with datasets pursuant to those rules.
All users of Redivis should develop an understanding of access level concepts
Organization administrators and dataset owners can learn about configuring access
Researchers can learn about how to request access
And administrators / data owners can learn how to approve access requests
Export restrictions can be used to limit how data can be exported from Redivis
And finally, when tables are combined in projects they follow the access rules of their source datasets