The Risk Data Library Standard (RDLS) is an open data standard to make it easier to work with disaster and climate risk data. It provides a common description of the data used and produced in risk assessments, including hazard, exposure, vulnerability, and modelled loss, or impact, data.
Risk data presentation is often bound to administrative units for both processing and result display.
If we provide standard tools to calculate risk at ADM level globally, we should also offer a standard ADM dataset.
Unfortunately, the topic of "politically safe" administrative boundaries is quite an hassle in some areas and the WB geo dep doesn't provide updated global boundaries for WB use (afaik).
There are external sources that can be leveraged, at the cost of variability in the structure of data (e.g. attribute names and format) which can be an obstacle for using into pre-made scripts.
Options
Leverage third-party websites such as geoboundaries.org to harvest the latest avaialble boundaries for each country
Pro: externally maintained and updated; formatting of data
Cons: range of different years; inconsistencies across different levels; variability in the way data is formatted
Build our proofed global dataset for ADM0, ADM1 and ADM2 - basically update what has been done 10 years ago for TH!
Pro: made omogeneous and proofed to work with our scripts
Cons: not WB official, not maintained, some discrectional choice to be made.
The issue
Risk data presentation is often bound to administrative units for both processing and result display. If we provide standard tools to calculate risk at ADM level globally, we should also offer a standard ADM dataset. Unfortunately, the topic of "politically safe" administrative boundaries is quite an hassle in some areas and the WB geo dep doesn't provide updated global boundaries for WB use (afaik). There are external sources that can be leveraged, at the cost of variability in the structure of data (e.g. attribute names and format) which can be an obstacle for using into pre-made scripts.
Options