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  • Overview
  • Workflow node access
  • Assigning workflows to a study
  • Usage rules
  • Access security

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  1. Reference
  2. Data access

Data access in workflows

Last updated 3 months ago

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Overview

You can view any that is public or shared with you, or that you are the owner of. However, your ability to view specific datasets, tables, and transform nodes within a workflow is determined based on your access to the relevant datasets. This ensures that dataset owners have full control over who can access their data, while giving workflow owners flexibility in defining who they collaborate with.

If you open a workflow and only have access to some of the datasets, you will see limited information depending on your access level.

Workflow node access

  • None: The node will be black, and you will not be able to see any information about it outside of its name and owner.

  • Overview: The node will be black, and you will only be able to see its name and description.

  • Data: The node will be grey, and you will be able to interact with it normally.

Assigning workflows to a study

You can change the study a workflow is in by clicking on the workflow's name in the top black bar, then clicking on Study.

If your workflow is not assigned to the appropriate study, you will not be able to run any transforms in the workflow. These transforms will display as having "Limited access" and cannot be run, similarly to when you don't have appropriate access to the source datasets. Click the Limited access button to get more information and assign your workflow to the appropriate study.

Usage rules

Access security

Data administrators have full control over access to their datasets. No action a researcher takes on Redivis can leak metadata or data to another researcher who wasn't already allowed to see the data by the data owner.

Workflow owners have full control over who can view and edit their workflows, with the exception that data administrators have read-only access to any workflows using their data.

If someone has access to a workflow when the workflow page is loaded access is computed for every node (dataset, transform, table, or notebook) within the workflow. The access level to a each node (none, overview, metadata, or data) will be computed based on the user’s minimum access to all of the source datasets for that node.

All tables and transforms in your workflow are derived from one or more source datasets. When determining your to a particular node, Redivis computes the lowest access level across all source datasets. Your ability to interact with workflow nodes for different access levels is as follows:

Metadata: The node will be checkered. If a table, you will be able to see variable names and , but you will not be able to look at cells or download the data. If a transform, you can view its configuration and code, but cannot run it.

If your access level to a node is lower than "data", when you click on the node you will see a red button in the top right showing your current access level. Click on this button to see which datasets are contributing to your reduced access and to subsequently

View an with limited data access. The workflow is public, which means anyone can open it, but what you can see in different nodes is dependent on your access to the source dataset(s) for that node.

If a dataset's access is controlled by , your workflow must be assigned to an approved study while working with that dataset. Conceptually, approval of a study requirement gives you access to work with a dataset in the context of that study, and for this reason all queries in your workflow must be in the context of that study.

If a table is derived from multiple datasets, the on that table will represent the intersection of the configurations from each dataset. If you request export approval, and the table contains datasets with export restrictions from multiple organizations, you will have to request approval from each organization.

access level
apply for access.
example workflow
export restrictions
workflow
study requirements
univariate statistics