Linkr
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Documentation Getting started Quickstart

Quickstart

Try Linkr online in two minutes, with no install required.

Summary

Open the online demo, create a workspace and then a project. In a few clicks you have access to a full IDE, a SQL engine and Python/R runtimes, all inside your browser. No install. No data leaving your machine.

Client-only

This guide runs entirely in the browser, no server required.

Prerequisites

  • A modern browser: recent Firefox, Safari, Chrome or Edge.
  • Nothing else. No account, no install.

Where is my data stored?

In your browser, through a built-in database called IndexedDB. It is a per-site local storage mechanism. Nothing is sent to a remote server. If you clear site data in your browser, Linkr’s content will be wiped — use the ZIP export to back up any important project.

Steps

1

Open the demo

Go to linkr-v2-b1800b.frama.io. The app loads directly in your browser. The first load may take a few seconds while DuckDB-WASM and the runtimes are downloaded and cached.

2

Create a workspace

A workspace is an organisational container (similar to a GitHub organisation or a GitLab group) that holds your projects, databases and wiki. Click Workspaces then New workspace, and give it a name — e.g. 'My sandbox'.

linkr-v2-b1800b.frama.io
Linkr
Menu
Home
Workspaces
Catalog
Settings
Workspaces

No workspaces yet

Create your first workspace to organize your projects.

Click 'New workspace' to create your first workspace.
3

Create a project

Inside your workspace, open Projects then New project. Enter a name and description, confirm: you are redirected to the project's Summary page.

linkr-v2-b1800b.frama.io
Linkr
Menu
Home
Projects
Wiki
Plugins
Data Warehouse
Settings
← My sandbox
Projects

No projects yet

Create your first project in this workspace.

From your workspace, click 'New project'.
4

Get the lay of the land

Four areas will cover most of your daily work inside a project.

Summary

Project overview, README and the list of ongoing tasks.

IDE

Code editor, terminal and Python / R notebooks, right inside the browser.

Data Warehouse

Databases, OMOP concepts, cohorts and patient-by-patient exploration.

Lab

Analytical datasets, built-in statistical analyses, and visualisation dashboards.

5

Go further with the Lab

The Lab is where data turns into results. Three main building blocks: analytical datasets (one row per patient, columns for your variables), built-in statistical analyses (Table 1, group comparisons…) and interactive dashboards composed of widgets.

patient_idagesexsofa_scorelength_of_staymortality
P-000167M84.2Alive
P-000254F129.7Deceased
P-000371M52.1Alive
P-000449F76.4Alive
P-000582M1114.3Deceased
P-000635F31.8Alive

Visualise the distribution of each column, spot missing values and explore your datasets in a few clicks.

The first run takes a bit longer

On the first visit, your browser downloads DuckDB-WASM (~10 MB), Pyodide (~15 MB when you use Python) and webR (~20 MB when you use R). These runtimes are then cached and instant on subsequent visits.

What to do next

  • Follow Your first project for a fuller walkthrough.
  • Install Linkr locally if you want to control your own instance.

Troubleshooting

The page stays blank or freezes. Reload. On the first load, the WASM engines may take a few seconds, especially on slow connections.

I can’t find my project after closing the tab. Data is stored in IndexedDB, which is per-browser (and even per-profile). If you switched browser or profile, your data isn’t visible. Use ZIP export to move it around.

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