Peer review is a common instrument of quality control in the academic world. New scientific knowledge is only accepted and, in many cases, only published when it has passed this barrier. However, in its current state, peer review has shortcomings, as it is time-intense and often unreliable.

To help make peer reviewing faster and more reliable, and to give guidance in this process to young researchers, we are developing CARE (Collaborative Augmented Reading Environment, formerly PEER), an Artificial Intelligence (AI) assisted software to support researchers in the annotation phase of reading and evaluation of scientific publications. To provide the maximum benefit to researchers from any field, we design CARE to adapt to (i) the user, (ii) the domain of research, and (iii) the document at hand.

This report first introduces the CARE software tool in greater detail. It then presents the setup and results of two studies performed at the Center for Advanced Internet Studies (CAIS), a survey and a user study. These had the aim to elucidate the requirements of the CAIS community members in CARE, and to test the usability of the software. The report summarizes the main findings, showing that the tool is useful to the study participants, and provides an outlook on the future of CARE.