[ML4OSM] Measure machine learning assisted mapping

[Florian Lohoff]

On Tue, Jun 02, 2020 at 07:24:54AM +0000, Felix Delattre via machine-learning wrote:
> Dear all,
> 
> As you probably know, the conversation about machine learning techniques
> and their use for OpenStreetMap has been very emotional in our
> community. Opinions range from the potential negative impacts this could
> have, to the hope that it would significantly improve the quality and
> also the speed of OSM mapping, because it allows people to focus on what
> they do best.
> 
> We want to take an evidence-based look at the effects of machine
> learning mapping on OpenStreetMap. To do this we are working together
> with several organizations (German Geoscience Research Center,
> University of Heidelberg and the OpenStreetMap humanitarian team) to
> conduct research that will quantify the measurable impact of the
> currently proposed mapping workflow. We believe that a reproducible and
> transparent study will give us a clue.
> 
> We are planning to do an experiment comparing four different datasets
> from the same area:

I put another one in the Basket. 

	"Long term community establishment."

If you'd follow the last decade of OSM you might have noticed
that we had countries with huge dataset imports, and we had countries
with nothing, everything hand-mapped.

If you look 10 years later the ones with huge imports struggle to
establish a sustainable community to fix the imports,
and maintain the data. (As a hint - Tiger Data US import, and AND import
of the Netherlands)

And from an long-term OSM point imports have been largely seen
as a problematic issue for long-term community maintenance of data.

Flo
-- 
Florian Lohoff                                                 f at zz.de
        UTF-8 Test: The 🐈 ran after a 🐁, but the 🐁 ran away
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