Filtering discrete data
The most naive and easiest method would be to interpolate the data points. If you know what is the maximum frequency present in your signal then you can specify the sampling period. Let's say you pick the lowest possible: 12ms. Now you can perform some interpolation of your data. Normally I would suggest you to perform the sinc interpolation, but you can start with linear/spline/cubic. 

In MATLAB/Octave you can use the interp1 function to interpolate the data points. If your data is called x, known time stamps are t, and new time stamps are t_new, then you can do the following to calculate new dataset X:

t_new = 0:0.012:max(t); %spaced by 12ms up to maximum value of vector t
X = interp1(t, x, t_new, 'spline');


This is very simple approach but should work - although you might get some aliasing. You can also check out this article for more intelligent methods: Nonuniform Sampling and Reconstruction in Shift-Invariant Spaces.

Now when you have your dataset, you can perform any filtering you like. Can I ask you what your sensor is so it's providing such data?