Outline of the video

• Demographic data is useful to get an idea of your urban context and to use it for downscaling calculation as your city proxy number.
• For now, you should focus on city demographic data and don’t have to worry about your country and NUTS data yet.
• The demographic data processing template has 5 columns.
• For demographic data, so on population, people are basically seen as stock by the system.
• Example: City population in HTK
• Different from the stock data processing is that we don’t have the materials columns, but instead population.
• There is also no unit assigned, they are by default seen as an “item” unit (which does not have to be added).
• Also there the drilldown function can be used which comes from the segments column. There it is possible to specify according to male/female or different age groups, for example 0-5 years old, 6-10 years old etc.
• With the total population for a city, we can eventually do per capita calculations. This can be done on either an entire city level, or even broken down further to neighbourhoods etc.
• M3:30, back to the example from Høje-Taastrup. We can simply copy the total population values for each year and make a rather simple table from that.

Note: Be sure to use the correct spelling for the reference space. In the video, it was accidentally stated as “Hoje Taastrup”. It should be Høje-Taastrup in this case.

Addendum (May 6, 2021): Apologies for making another mistake which was brought forward by now. We didn’t clearly show the correct format for the date, in column A. Instead of just adding the year (e.g. 2016), it should be a specific date and written for example like, 2016-01-01, if the data is from 1st of January 2016 or 2019-12-31, if it is from 31st of December 2019. See also the example here.