This is not uploading. We've known the connectome of C. elegans for a while: that means we know what the neurons are, what the connections are, and whether they are inhibitory or excitatory. What we don't know, and have no way to read off an existing worm, are the weights for these connections. For this project they assumed every connection has a weight of 1, which does turn out to be enough to do interesting things. But when a C. elegans learns that a given temperature is associated with food it doesn't grow new neurons or connections, it changes its weights. Their model can't do this, so it can't learn.
When we can teach a worm to do X, scan it, run it, and observe that the running worm does X when ones not taught to do X don't, then we've uploaded the worm.
EDIT: expanded this into a post.
The connectome for the 302 neurons of the nematode C. elegans was put in charge of a Lego robot. Without any additional programming, the simulated brain started using the robot parts just like the original worm's organs.
"When you think about it, the brain is really nothing more than a collection of electrical signals."