Synthetic sounds to describe motion in 3d or 100d
You say your points are strictly ordered:


  a sequence of points $X_1 \ X_2 \ X_3\  \ldots\ X_N$ 


Well, in that case, you can


either define "speed" as "euclidean distance (or any other metric) per in between two consecutive points":
$$s_n = ||X_{n+1} - X_n||,\quad n=\{1,\ldots,N-1\}$$
and interpolate a steady function $s(t)$ from that sequence, or
you can define speed as the first derivate of an interpolation function through all $X_i$. However, finding an interpolator for $N$ points in 100 dimensions isn't easy, and also, its utility would be pretty questionable, unless you have some goal in mind that clearly says why a specific interpolator is appropriate for your problem.


After you have a scalar value along a single axis, well, map to tone or loudness. 

I really doubt the "illustrating" effect is overly great here: the choice of your interpolation will probably have the most important effect on what listeners will take as an impression from this, and that choice is not backed by the data itself – it's a model choice you make. Which would be ok, if you know something about the data (i.e. all the individual dimensions just contain harmonic oscillations would suggest classical low pass filtering would be an appropriate method to interpolate "speed" points), but if you don't and want to use this "audiolisation" to understand your data better, you'd end up fooling yourself. You will listen to your own assumptions, not the data.

However, you mentioned PCA, which indicates the points aren't actually to be understood sequentially! That of course makes things a lot harder. You'd essentially be looking for a $100-1$ hypersurface that describes how your points are mainly distributed in your $100$ dimensional space, and then look for the main gradient of that – and that leads to all the nice problems that you get with higher dimensional analysis (lack of "one" derivate of function, mapping values from something that isn't a vector space to a vector space, which introduces the need for maps on manifolds... meh).