Thanks Dan! Yes I agree that there are likely different audiences involved; unfortunately that is hard to establish without actually interviewing people.

Vincent de Phily – thanks! There are a number of ways in which we could look at local HOT mapper contributions, that’s certainly on my list of things to look at. As far as I’ve seen that is likely to be a much smaller number of people though, at least at the moment, so it might be more tricky to find generalisable observations. And of course they’re hard to identify. Identifying based on contributed “local” knowledge is an interesting thought, although that can also happen remotely via field papers. For a project last year I tried to identify locals by their prior edit history (people who predominantly had local OSM contributions prior to the activation), and found that people with such profiles are exceedingly rare – I think local HOT contributors tend to be new to OSM. In some cases we might be able to identify them based on participation in training events etc.

Thanks mataharimhairi!

PlaneMad – it’s all done “by hand”, I’m intending to write a little about that in a future post. I’m using Osmium to extract data from the OSM edit history, data is stored in a Postgres DB, analysis happens in Python (mostly using IPython and various analysis/visualisation libraries.) Went through loads of iterations to find a combination of tools that work well for me, e.g. in earlier work I used Pig on EC2 but that was just too much hassle. No Nepal data yet because I finished my analyses just around the time that happened.

PierZen – I’m not looking at OSM activity outside of HOT contributions at all, this is entirely about HOT activity and HOT retention. And yes I agree, there’s much more we could look at :) Including how HOT vs other OSM contribution patterns relate – e.g. do HOT contributors turn into OSM contributors?

dkunce – yes, should be most interesting to track retention over time as Missing Maps matures. Will definitely keep an eye on it. I’d also like to compare a much larger set of other initiatives, if I can find the time.

jonwitt – many thanks! I grouped individual edits by their timestamp, with a session timeout of one hour. (I additionally estimate the duration of the first edit since we don’t know when people actually started. That estimate is simply based on the average time between edits.)

I like “labour hours” as a measure of engagement because it’s much more directly related to a contributor’s effort than the edit counts that are usual produced for such studies. Additionally it is a measure that also makes sense to organisers; e.g. mapathons can be thought of in terms of labour hours. The first time I’ve seen this measure used was in a Wikipedia paper from Geiger/Halfaker in 2013.

SimonPoole – Good points! I realise I have much more exposure to the experience of HOT newcomers, through attending mapathons and other community gatherings over the last year. As a result most of my conversations tended to be with people who come from outside the OSM community. Your interpretation certainly sounds plausible as well. Would be curious about what else you think comes across as biased! I do have a particular perspective, but I also try to make it explicit in my writing when I speculate.

The contributor split is:

• TH: 482 people
• ER: 894 people
• MM: 206 people