Information About the Project
History
The CARE Project started in 2021, based on a prototype version implemented with Hypothes.is built in 2020 and funded by two projects, PEER and ATHENE. Whereby PEER aims to create an integrated platform to support the general peer reviewing process, ATHENE focuses more on training individuals using workflows to prepare them for future peer reviews. In order to use synergy effects, we decided to bundle the two projects on one platform, which resulted in CARE.
PEER
Peer review is a complex and time-consuming process – especially for junior researchers lacking experience of the task.
The PEER project started in 2020 with the aim of developing a platform for the support of authoring peer reviewing reports addressing both of these issues. Peer review is connected to many different NLP concepts such as text summarization, part of speech tagging.
The project is located in the SIG Intertext, since scientific papers also have cross-document phenomena (e.g. revisions of the same document, annotations from different people linked to the same document).
ATHENE
Peer reviewing workflows have the goal of guiding junior researchers through the process of peer review creation. A workflow functions as a manual of peer reviewing involving a sequence of steps to extract and assess relevant parts of the paper. PEER incorporates state-of-the-art NLP techniques to match generic workflows to specific papers and to assist during the discovery of relevant sections for each step of the process.
Paper and Publication
The first deployment of CARE and its conceptual foundations were described in the following publication:
CARE: Collaborative AI-Assisted Reading Environment Dennis Zyska, Nils Dycke, Jan Buchmann, Ilia Kuznetsov, Iryna Gurevych
https://aclanthology.org/2023.acl-demo.28/
Note
CARE has since been renamed to Collaborative AI-Assisted Research Environment, as we have now also integrated an editor.
Going Public
In 2025, the team decided to release CARE publicly to encourage adoption and collaboration in both academic and open-source communities. This includes making the platform more modular, improving documentation, and publishing tutorials and example use cases.
Want to Contribute?
CARE welcomes contributions from developers, researchers, and students. If you’d like to help improve the platform:
Check our open issues on GitHub
Pick a good first issue
Suggest a feature or improvement
Report a bug or UX issue
Help extend the documentation or provide new usage examples
We follow a contribution workflow explained in the developer section of this documentation. Please read the conventions before opening pull requests.
Ideas and/or Feedback
You have an idea for a new feature, a possible customization or a suggestion for an improvement? Please let us know and don’t hold back — we will collect all ideas through this form:
Feedback Formular: Open Form