Hi folks
I’m a newbie here as I’ve just started developing the Local Open Data Census for Canada. As I was reviewing the scoring/ranking, I quickly realized that it was unfair/inappropriate when dealing with data sets that may not apply to a specific level of government. For example, in Canada there can actually be four levels of government with the “local” being both a regional level as well as a number of “lower tier” local municipalities within the region (or county).
The scoring/ranking becomes a problem if, for example, the regional level of government provides police services and public transit services which means that the local municipality would receive zero points for any data sets that they did not have jurisdiction for. This can also apply when we provincial/state level data versus “local” gov data.
To address this, I’m suggesting that data sets that are not applicable can be designated as NA and more importantly that the scoring/ranking algorithm provide a % of openness based only on the data sets that are applicable. Apologies if this has been discussed before and I look forward to your thoughts.
Cheers Jury Konga
Open Knowledge Canada Ambassador