I have a large set of data points that essentially represent the coastline of the world. I don't know the exact resolution but I'd say it's in the neighbourhood of 5-10m.

Imagine a set of points which represent a jagged coastline. At a 1m resolution, we see all the detail and need 50 data points to correctly represent the coast, however, at 10km resolution the coast looks like a straight line and we would only need 2 points.

I'm writing a mapping application that will require the data to scale from "full-planet" resolutions to "street" resolutions. I need some help reducing the resolution of my data points, and subsequently the amount of data for wider resolutions.

I've been reading about Vector-Tiling and think this will be the best solution (I'm doing something like this already), however, at the low resolutions, my dataset it still huge meaning that rending it takes a [relatively] long time, where as the high resolutions are fast because the 'effective' dataset it small (subset of the whole).

I'm trying to determine how to take my large dataset and reduce the scale of it so that my 'full-planet' view's tile data is a manageable size. How do I create the tile sub-datasets from the larger complete dataset?

I'm happy to use a tool but I'd rather do it myself in an effort to learn how it's done.