  Tracing knowledge acquisition and linking learning events to interaction
between peers is a major challenge of our times. We have conceived, designed
and evaluated a new paradigm for constructing and using collective knowledge by
Web interactions that we called ViewpointS. By exploiting the similarity with
Edelman's Theory of Neuronal Group Selection (TNGS), we conjecture that it may
be metaphorically considered a Collective Brain, especially effective in the
case of trans-disciplinary representations. Far from being without doubts, in
the paper we present the reasons (and the limits) of our proposal that aims to
become a useful integrating tool for future quantitative explorations of
individual as well as collective learning at different degrees of granu-larity.
We are therefore challenging each of the current approaches: the logical one in
the semantic Web, the statistical one in mining and deep learning, the social
one in recommender systems based on authority and trust; not in each of their
own preferred field of operation, rather in their integration weaknesses far
from the holistic and dynamic behavior of the human brain.
