I'm looking for advice on how to compile some datasets that each have a different set of attributes. Each dataset is point data, recorded in one of the two coordinate systems that have been used historically in my area. With each of my six datasets (thousands of points in each file) there are points that are contained in other datasets, as well as some which are unique. The duplicated points may not be exact coordinate matches, as they are observed coordinates, and may not be from the same observation.
I would like to compile these datasets into a single dataset, where each successive attribute table is appended onto the end so no data is lost, but all duplicated entries are merged into a single row/feature. I don't want to calculate a mean, or best likely coordinate, I want it to just add each source layers coordinates, and other fields as new attributes, so I can see the history of each observation.
The result will be a master database that I can then clean up without 6 entries for 70% of the points.