  We develop a method to enable collaborative modelling of gravitational lenses
and lens candidates, that could be used by non-professional lens enthusiasts.
It uses an existing free-form modelling program (glass), but enables the input
to this code to be provided in a novel way, via a user-generated diagram that
is essentially a sketch of an arrival-time surface. We report on an
implementation of this method, SpaghettiLens, which has been tested in a
modelling challenge using 29 simulated lenses drawn from a larger set created
for the Space Warps citizen science strong lens search. We find that volunteers
from this online community asserted the image parities and time ordering
consistently in some lenses, but made errors in other lenses depending on the
image morphology. While errors in image parity and time ordering lead to large
errors in the mass distribution, the enclosed mass was found to be more robust:
the model-derived Einstein radii found by the volunteers were consistent with
those produced by one of the professional team, suggesting that given the
appropriate tools, gravitational lens modelling is a data analysis activity
that can be crowd-sourced to good effect. Ideas for improvement are discussed,
these include (a) overcoming the tendency of the models to be shallower than
the correct answer in test cases, leading to systematic overestimation of the
Einstein radius by 10 per cent at present, and (b) detailed modelling of arcs.
