What is Time Slice data?
To visualize Time Slice data, consider the diagram below, which shows a group of polygon objects valid for four different dates.
By gazing at the four consecutive time slices from bottom and moving upwards, we can grasp how the objects changed over time. For instance, the pale jade colored polygon shrank in size between time 2 and time 6, and the area which the jade polygon lost became a new tan colored polygon. Then, between time 6 and time 11 the jade polygon expanded slightly, while the lavender colored polygon shrank in size. We can deduce that these changes occurred, but from the time slices depicted we cannot tell when the changes occurred.
It would be convenient if the actual historical places depicted changed simultaneously at regular intervals, as the diagram seems to imply. But in fact, historical administrative units and other geographic features are constantly changing independently of one another. They each have their own separate timelines, from the time they were first established or recorded, through various changes in name or jurisdiction, and up to the time they were abolished, absorbed or changed into a new feature. In reality, what we are dealing with in tracking historical geographic objects are a whole series of asynchronous events, and a whole series of spatial objects used to represent each one of the "instances" of change for those objects.
When these asynchronous objects are collected together into a single GIS layer, we refer to them as Time Series datasets.
When the historical places valid only for a particular year are collected together into a single GIS layer, we refer to them as a Time Slice dataset. Currently CHGIS data includes a complete Time Slice dataset for the year 1820, and a partial Time Slice dataset for the year 1911.