The SciColab project aims to provide a platform that not solely provides a space for collaboration but instead fosters and motivates collaboration throughout the project’s lifespan. To ensure the optimal support throughout the respective projects, the utilization of machine learning and deep learning based recommendation systems is crucial. Each bit of textual information that is gathered throughout the project’s lifespan is analyzed and utilized to create various kinds of recommendations that assist teams with various tasks for example research, team creation, ideation and writing tasks.

A special focus is given to the usability of the platform and presentation of the resulting recommendations. Resulting recommendations are visualized within a visual analytics system, that allows users to explore the results as they desire, with a wide range of visualizations and interactions that the user can choose from. This focus on user cognition underlines our focus on human computer interaction and goal to support the user throughout the project. 

The platform is modular and is not limited to a single domain or sector. It provides an optimal start to, and continuous support throughout, any project that requires the collaboration of experts. The utilization of natural language processing-based text analysis and AI-based recommendation systems allows the platform to assist any team with tailored recommendations to inspire innovation and improve collaboration. 


This project is funded by the Ministry of Science and the Arts (HMWK) within the framework of the academic mid-level program.