In the interest of allowing the most researchers to access as much information as possible, without compromising security, Redivis implements a tiered access system for working with data. These access levels will determine what information you can see on a dataset and whether or not you can manipulate the data in a project.
There are six conceptual access levels on Redivis. These access levels are configurable — they can public, or restricted to certain individuals, or require approval of specific requirements.
If you have no access to a dataset, you won't even be able to see that the dataset exists. It won't show up in search queries, and navigating to the dataset page will return a "Not found" page. This is for the case when the data owner only wants specific people to have knowledge of a dataset's existence — in order to see the dataset, the owner will need to directly share it with you.
The ability to see that the dataset exists, as well as its description, some documentation, tags, and name and description of its tables. Users with overview access only will not be able to see variable names and statistics, nor will they be able to view, query, or export underlying data in any way. They will also only be able to see those documentation sections that are allowed for overview access.
In addition to the properties of overview access, metadata access allows users to view variable names and summary statistics, as well as documentation sections limited to metadata access. They still cannot view, query, or export underlying data in any way.
Sample access only applies to datasets that have sampling configured. If a user has sample access to a dataset, they will have data access to all sample tables, and metadata access to the corresponding unsampled tables. If only some of the tables on a dataset have a sample configured, the user will also have data access to any tables that don't have a sample available.
If a dataset doesn't have a sample configured for a particular version, a user with sample access will only have metadata access to its tables.
If a user has data access, they can view and query all tables in the dataset, and export data and data derivatives pursuant to any usage restrictions. They will also be able to see all sections of the documentation.
Anyone specified as a "manager" of a dataset will have automatic data access, regardless of whether they have completed the necessary requirements.
Dataset editors can update the dataset's documentation, metadata, and data, and release subsequent versions. They cannot manage who has access to the dataset or change its access configuration.
The owner of a dataset is defined as the user that the dataset belongs to, or for organization-owned datasets, any administrator of that organization. Dataset owners can configure the dataset's access rules, approve access requests, and perform any other operation on the dataset.