If that's flow over time, I'm guessing you can calculate the seperation between each point, to find the linear curve, and be able to do a best guess input of the in-between values.
You'll need the time intervals between each value you have. Given a known time interval, you should be able to simply take a calculator, and subtract one value (b) from the previous value (a), then divide the resulting value (c) by the time lapsed between the two values (d), to get the placement of the inbetween values on the graph (e). Then you add (e) to (a) to get (e1). Then (e) to (e1) to get (e2). And so on.
b - a = c
c / d = e
For example (I just assumed a 3 second interval for this):
0.6710 - 0.3221 = 0.3489
0.3489 / 3 = 0.1163
And obviously e3: 0.6710
From there, just input the (e) values between the (a) and (b) values, and do that for each data pair. Once you've gotten all of the inbetween values, then you can trim down to the 20 that you need on each axis.
Just thought of this, but you might could make it easier on yourself, by subtracting the first value from the last value. Divide the resulting number by 20 (or 18, since we only need 18 in-between numbers).
(e = 0.2178 (0.21782777777777777777777777777778, actually), which will put (e18 or b) at 4.2425 since (e) was truncated to only 4 decimal places. But should still work for the X Axis's 20 points)
Obviously, going through each data pair individually, using the actual time intervals will net more acurate results.
edit: DOH! Just re-read that you needed 30 points, not 20. Hehe. Oh well, same concept, but instead of dividing (e) by 18, divide it by 28. Hmmm... actually 29. I just recounted, and noticed my division by 18 resulted in only 19 total values, not 20. I always hated math
I guess, if you go with the time interval / data pair method above, depending on what the time intervals are, if there's not enough time interval iterations to make 30 points, you can go to half seconds, or even 1/10th or 1/100th seconds, to boost the number of time intervals between each data pair.