How to Compare three Data Series Collected by different means?

I need to compare three different data series. The subject of the data is the same, but the collection method is different.

My initial approach was to only compare two of the series at a time, using Kendall's correlation coefficient. I chose this because it seemed like the best method to compare the "likeness" of the data at any given point.

What would be the best way to compare these sets of data? Is correlation the best way?

Any help would be appreciated.

EDIT: Please allow em to correct myself. I did not mean to compare "likeness" of the data at any given point, rather to compare the entirety of the data. This is why I selected Kendall's coeff over Pearson's.
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Less is more. Stay pure. Stay poor.
Please define "data series" and provide some more information in order for us to give assistance.


No cake for spunky
You can compare the series on many different criteria. For example you could generate the mean, median, and SD of each and compare them. You could plot their distribution and lay them side by side.

How you gathered the data would seem most critical to how well you can generalize from a series to a larger population. I am not sure that it matters if you don't care about such things.