> For the complete documentation index, see [llms.txt](https://docs.gospace.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.gospace.com/integrations/mapping-your-data/how-to-map-your-occupancy-data.md).
# How to map your occupancy data
Here you have the following fields to map:
### Person ID field:
This needs to be the same value as what has been entered in your “Person ID“ field in your user import, to clarify this can be different to the user ID, but it is a field of which maps the occupancy records in your import, to the user in gospace. For reference please see [Users with teams](/integrations/mapping-your-data/map-your-directory/users-with-teams.md). If this is set to a different value to the Person ID field in your user import, then the occupancy will not be mapped to your users meaning your AI forecasting will not work. Put simply this should be the field of which maps the occupancy records to your users.
### Location fields:
* Location field: This is mapping the header in your integration of which the location is stored, this lets us know the user was in ***x location*** on which day.
* Mapping: In the above screenshot you can see two gospace locations were mapped to values in the Location field. Therefore the admin has configured that the London Office in locations on gospace, is equivalent to any record named “London” in the ”EXTERNAL\_ID” field as an example. This ”EXTERNAL\_ID” is the location field selected previously. Consequently we are just mapping locations from occupancy data to gospace so we know which location in gospace the data is referring to.
Filters are configured the same as in [Users with teams](/integrations/mapping-your-data/map-your-directory/users-with-teams.md), and simply will only use the occupancy data of which matches the logic defined in your filter.
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