Linkr
Home Resources Tools Documentation Blog Demo
FR
  • What is Linkr?
  • Deployment modes
  • Quickstart
  • Local install
  • Your first project
  • Workspaces and projects
  • The data pipeline
  • Versioning and collaboration
  • Schemas WIP
  • Databases WIP
  • Data quality WIP
  • ETL pipelines WIP
  • Concept mapping
  • Introduction
  • Mapping projects
  • Overview
  • Target Concepts
  • Mapping Editor
  • Suggestions
  • Evaluation
  • Export
  • Data catalog WIP
  • Cohorts WIP
  • Patient-level data WIP
  • Datasets WIP
  • Script collections WIP
  • IDE WIP
  • Dashboards
  • Reports WIP
  • Build a plugin WIP
  • Overview
  • Tabs and widgets
  • Built-in widgets
  • R, Python and SQL code
  • Filters, settings and export
  • Wiki WIP
  • Versioning WIP
  • Production install WIP
  • Authentication and permissions WIP
  • Configuration WIP
  • Backup and restore WIP
  • Glossary WIP
  • Release notes WIP
Documentation Core concepts Versioning and collaboration

Versioning and collaboration

How Linkr versions and shares work: ZIP export, git integration, shared workspaces and bottom-up standardisation.

Summary

Everything you produce in Linkr — projects, plugins, scripts, schemas, wiki — is versionable and shareable. Two mechanisms coexist: ZIP export / import, available everywhere with no installation, and git integration, to link projects and workspaces to remote repositories.

Client Available in client-only mode — runs entirely in the browser, no backend. Backend Backend (FastAPI) under development.

Why versioning matters

A study, a dashboard, an analysis plugin represent work you want to keep, find again and pass on. Without versioning, every analysis starts from scratch and nothing circulates between teams. So Linkr treats projects and workspaces as objects you archive, share and version — just like code.

This follows directly from a principle seen in the previous chapter: a project is a file tree (project.json, scripts/, cohorts/, dashboards/…). Versioning a project means versioning those files. See Workspaces and projects.

Two ways to share

ZIP export / import

Download a whole project or workspace as an archive, re-importable into any Linkr instance. Available in both modes, no backend.

Git integration

Link a project or workspace to a remote repository (GitLab, GitHub). Cloning on import works today; full push / pull comes with the full-stack mode.

ZIP export / import

This is the simplest path, available right away. You download a project — or an entire workspace — as a ZIP archive, then re-import it elsewhere. On import, Linkr assigns fresh identifiers to avoid any collision with existing content. It is the recommended way today to back up your work and pass it to a colleague or another centre.

Workspace export is granular: you choose what to include (projects, wiki, schemas, databases, SQL scripts, ETL, mappings, plugins), and you can strip connection credentials from databases so passwords are never exported.

Git integration

A project, a workspace — but also a SQL script collection, an ETL pipeline or a mapping project — can be linked to a remote git repository. Cloning (fetching a repository on import) works today in client-only mode. Full push / pull and branch operations on the server side belong to the full-stack mode, under development.

What is available today

In client-only mode, sharing relies on ZIP export / import and git cloning on import. Full git versioning (push / pull, branches, server-side history) and multi-user management are planned with the backend. See Deployment modes.

The “git links” pattern

How do you share a workspace containing dozens of projects without duplicating everything into one giant archive? Linkr uses an approach inspired by git submodules.

When a project (or other content) is linked to its own git repository, the workspace export does not carry its full content: it carries only its metadata and a pointer to the repository. The workspace then becomes a manifest of links rather than a large monolithic block. At deployment time, each linked repository is cloned and the full content is reconstituted.

The benefit is direct: each team versions its projects in its own repository, at its own pace, then links them into a shared workspace. You combine each team’s autonomy with a pooled overview — without copying the same files in ten places.

Deploying a pre-loaded instance: Linkr Portal

Reassembling these linked repositories at deployment time is handled by a dedicated tool, Linkr Portal: it aggregates the Linkr code and the content repositories, reconstitutes the workspaces and publishes a pre-loaded Linkr instance (for example on GitLab or GitHub Pages), with an optional split between public and private content. Its setup will be detailed in the Administration section (coming soon).

Tracing origin and versions

Sharing means knowing where a resource comes from and how it evolved. Plugins carry a built-in traceability for this.

Plugin traceability

Each plugin keeps: a content hash (a technical identifier recomputed on every save, distinct from the human-readable version number), its origin (creator, organisation, repository), an optional lineage (the version it was forked from) and a changelog. You can thus tell precisely which version of a plugin produced a result, and trace the lineage of a plugin picked up and adapted by another centre.

Collaborating

Collaboration rests first on shared workspaces: a common container where several people find the same projects, databases, plugins and wiki. See Workspaces and projects.

In full-stack mode, a workspace will have members with roles — admin, editor, viewer — that determine who can edit, publish or only view. This access control and authentication belong to the backend and are planned, not yet available.

Standardisation, from the bottom up

This sharing machinery serves a conviction: standardisation in healthcare works better when it emerges from the field than when it is decreed in advance.

Each team starts by solving its local problems — cleaning its data, aligning its vocabulary, writing its analysis scripts. By then sharing projects, plugins and mappings via git or ZIP, good practices circulate, are picked up and adapted elsewhere. Standardisation is thus built gradually, through adoption, instead of being imposed from above.

No effort is wasted: data cleaning, semantic alignment, analysis scripts — everything produced for one study feeds the next.

This is the collaborative counterpart of cumulative investment: quality and reusability build up project after project, team after team.

Further reading

  • Workspaces and projects — the shared container and the unit of work.
  • Concept mapping — evaluation — multi-reviewer review in practice.
  • Deployment modes — what the full-stack mode unlocks.
PreviousThe data pipelineNextSchemas

Product

  • Home
  • Demo

Resources

  • Documentation
  • Resources
  • Tools
  • Blog

Community

  • Framagit source code
  • Github source code

About

  • InterHop.org
  • Contact

2021–2026 InterHop — CC BY-NC-SA 4.0 (site) · GPLv3 (software)