Service Workbench
  • General User Guide
    • Introduction
    • Studies
      • Open Data Studies
      • Controlled Data Studies
        • Human Connectome
        • TCGA (The Cancer Genome Atlas)
        • EMory BrEast Imaging Dataset (EMBED)
      • Organization Studies
    • Research workspaces
      • Workspace statuses
      • Workspace configurations
      • How can I create a workspace linked to a study?
      • How can I create a workspace WITHOUT a study?
      • Installing packages into workspaces
      • Using custom Jupyter Notebook kernels
      • Uploading data into SWB
    • Instances
    • Example Analyses & Notebooks
    • FAQ
      • Why was my workspace stopped when I was working on it?
      • How can I install devtools in R/Rstudio?
      • I don't see a 'studies' folder in my workspace?
      • Error: 'Forbidden' or 'Unable to connect'
      • Error: 'We have a problem! null is not an object'...
      • 403 error page
      • Error provisioning environment sagemaker
      • Workspace in Unknown status
      • Cannot connect to SageMaker workspace
      • I can't get through to the log-in page on SWB.
    • Help / Contact Us
    • Release Notes
  • AIM-AHEAD
    • Accessing OCHIN Data
      • Phase 1: Regulatory Requirements
      • Phase 2: Data Exploration
      • Phase 3: Data Analysis
      • Example Researcher Workflow
    • Understanding the OCHIN Data
      • i2b2 Common Data Model
      • Example Queries
      • Additional information
  • Harvard Medical School
    • Introduction
    • Activating your account
    • Creating your workspace
  • LEAP-DEV
    • Workspace Configurations
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  1. General User Guide

Introduction

General user guide for Service Workbench (SWB) on Amazon Web Services (AWS)

SWB is the first open-source native cloud computing platform that provides a modular and scalable solution to the supply of research computing environments. The platform supplies research teams with a simple web application, empowering them to easily deploy and access any cloud workspace from a custom catalog of pre-configured environments leveraging all AWS AI/ML and native security controls.

SWB is a flexible and scalable cloud solution that promotes equitable access to the computational resources needed for AI/ML. Researchers have access to the compute power needed in a few clicks, regardless of the technical underlying complexity of it.

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Last updated 1 year ago