Metanno is a JupyterLab extension that allows you build your own annotator. For the moment, it focuses on textual documents with rich structured entities. Its main objectives are: - modularity: you decide how many views of your data are needed - customization: you can easily customize the software behavior in Python and see the changes immediately - interactivity: all of your annotations are immediately available as Python objects as soon as you edit something

Features

• ↵ multiline and nested span annotations
• 🖇️ nested, relational, complex annotation with table views
• 🔗 multiple data type: hyperlinks, text, lists
• 🪟 text view or table view
• ✨ extensive customization power
• 🐍 write your app in Python, execute it in the browser (or in the kernel, you decide)
• 🚀 fast: the client side is written in React, and every action is processed in the browser directly by default
• 🌐 websocket communication: you do not need to open any port
• ⏮️ immutable state management, any state mutation is recorded and undoable

Citation

If you use Metanno, consider citing this work as below.

bibtex @software{wajsburt_metanno, author = {Wajsbürt, Perceval}, title = {Metanno: a modular annotator building framework}, month = feb, year = 2024, publisher = {Zenodo}, version = {0.0.9}, doi = {10.5281/zenodo.10689827}, url = {https://doi.org/10.5281/zenodo.10689827} }

Installation

This project is still under development and is subject to change. A simple pip install should be enough if you use Jupyterlab 3. You do not need to open any port. ```

To setup the environment

conda create --name annotation python=3.9 conda activate annotation pip install ipykernel && python -m ipykernel install --user --name annotation

To install the package

pip install metanno ```

If you're a user in a shared Jupyter environment (you did not run the jupyter lab command), you should instead install the extension at the user level

pip install metanno --user

Why

The choice of annotation software must be taken into account in the design of the annotation scheme. For example, it is difficult to annotate implicit/document-level entities in Brat or to annotate relations on multiple lines, and impossible to handle multiple documents at once. There are many annotation tools available (see Neves et al.), but most of them are either proprietary, poorly adapted to document or multi-document annotation, require a complex installation that is not compatible with existing remote work environments, or are difficult to customize. Finally, the standardization of annotation levels (mention / relation / event) is an obstacle to the development of new tasks. Given the limitations of the existing softwares and the difficulty to cover every need with a single static annotator, this project was initiated to provide a modular and fully customizable annotation framework, Metanno, and address these difficulties.

Demo

You can try it with . Be patient though, when there is no cached build, it may take a few minutes to start.

How it works

All the app is controlled by a single state, replicated on both the frontend (the Jupyter client) and the backend (the Python kernel). Each views rendered in Jupyter uses a derivation of this state (think view_data = fn(app_data)) and calls functions in the app class whenever an event occurs. This app class is written in Python (by you), automatically translated into javascript and sent to the front-end such that every action taken by the user is answered immediately. If a given function modifies the state (wrapped by the @produce decorator), the changes are sent to the backend or the frontend to keep the state replicas in sync. If a function needs to be executed exclusively on the frontend or the backend (for example, triggering a database query on the backend), you can wrap it with @frontend_only or @kernel_only, and the call will be transmitted over the Jupyter websocket.

Todo

• add basic app samples
• add a documentation
• add more table column types and renderers (numerical, dates, ...)
• ~~add customizable column filterers~~
• add relations visualizations and edition with editable arrows
• add an image annotation view
• ~~finish javascript to typescript conversion~~
• ~~customizable undo / redo logic~~
• add multi-cell editing (see a react-data-grid PR)
• add a test suite (Cypress ?)
• make a standalone version (without Jupyter)

Contribute

Any contribution is welcome, feel free to open a PR.