What is a Featured Workspace?
All users with a registered Researcher Workbench account have access to “Featured Workspaces,” which are workspaces designed to provide examples of cohorts, concept sets, and data analyses that can be used to inform or enhance your work. A type of Featured Workspace called "Tutorial Workspaces" provide instructions for key Researcher Workbench components and representations of the All of Us dataset. Tutorial Workspaces are a great starting point for learning how to analyze data within the All of Us dataset as these workspaces walk you through basic data manipulation, and analysis techniques specific to the All of Us data.
Featured Workspaces can be accessed from the left-hand navigation bar in the Researcher Workbench by clicking a section labeled “Featured Workspaces.” Login to the Researcher Workbench is required to access these workspaces. In order for you to edit these workspaces, you need to clone the workspace of interest by clicking on the left side of the workspace icon on the “snowman” icon and then selecting “Duplicate.” This will open the cloned workspace's “About” section, where you can choose to change the name or any other description within this space and then click “Duplicate Workspace.” If you do not clone these workspaces, you will not be able to copy the code or other components for your own analyses, as users are readers only of the original Featured Workspaces.
Featured Workspaces are divided into three categories: Tutorial Workspaces, Demonstration Projects, and Phenotype Library. You can learn more about the description of each Featured Workspaces in this support article.
Skills Assessment Training Notebooks - an overview of the All of Us Researcher Workbench
If you are new the All of Us Researcher Workbench, you might feel lost at first and not know where to start with your analysis. The Skills Assessment Training notebooks are an introductory set of notebooks to teach you the basics of the All of Us data structure and model, while providing general steps to follow to start and complete your analysis.
This Featured Workspace is categorized into three main categories:
1. Get Familiar with OMOP Common Data Model and Athena
2. Collect Data for Analysis
3. Wrangle your Data to Prepare for Analysis.
Subcategories include learning how to use All of Us tools, how to query data using SQL, and how to manipulate data using R or Python coding languages. These self directed training notebooks assess users' understanding of the workbench and OMOP through interactive quizzes to help users check their knowledge not only on Python, R, and SQL, but also on the general data structure and data model used by the All of Us program.