Data And Deployment
Connecting to a Cloud Database
ReVISit is inherently a serverless program. As such, we developed a storage engine architecture in order to store the data that is gathered from users as they move through the study. While you can test the program locally using the browser's local storage, you will need to set up some sort of cloud database in order to save study participant data. Our intention is that those who create the study have full control over the data that is generated by participants — no data is ever linked back to the reVISit repository or those who have contributed to its creation. See the Deployment section for more information about deploying your study to GitHub.io once the connection to Firebase has been set up.
Firebase
3 items
Supabase
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Deploying To a Static Website
Publish your study as a static website so Participants can open it in their browsers. First, complete the installation guide and check that your study builds locally with yarn build or npm run build.
Deploying with Docker
This guide explains how to build and run a ReVISit study with Docker using:
Configuring the Landing Page
The landing page is the list of studies at the root of your ReVISit deployment. You can group studies into tabs, add descriptions, and choose which studies appear. Visitors can browse this list without needing access to your study data.
Connecting with External Participant Platforms
ReVISit makes it easy to connect with participant management platforms such as Prolific, SONA Systems, and other custom services. ReVISit can automatically collect participant IDs from study links, display those IDs inside the study, and redirect participants to a platform-specific return link after completion.
User Management in reVISit
ReVISit's built-in user management works with Firebase and Supabase. For Firebase, set up Firebase Authentication with Google sign-in using the Firebase setup guide. For Supabase, configure GitHub OAuth using the Supabase authentication guide.
The Lifecycle of a reVISit Study
A reVISit study will go through multiple stages over its lifetime. It'll first start as a local study that is iteratively refined until the study is fully built, it will then be deployed and tested, it will be sent out to participants for data to be collected, and finally the study will be disseminated to reviewers.