Hi all,
*a) data hosting*
I can offer to host pre-processed data for the building imports as well.
*b) task manager work units*
I find smaller tasks about 20 minutes each more appealing than 1 hour tasks
*c) checking already existing data*
An added tag would certainly help as you can apply a filter in JOSM then.
*d) finding local mappers*
You can use the following query on http://overpass-turbo.eu/ to get a
list of all users in the time period specified in the area specified.
// overpass query
[out:csv(::user)];
// replace Montreal by any known location in OSM, or see code below
// for bounding box use
{{geocodeArea:Montreal}}->.searchArea;
(
// I collected users active in the last 6 months, but you can
// change that
node(newer:"{{date:6 months}}")(area.searchArea);
way(newer:"{{date:6 months}}")(area.searchArea);
relation(newer:"{{date:6 months}}")(area.searchArea);
);
out meta;
// end overpass query
Copy the query into the left side of the window and click Export, then
'raw data directly from Overpass API'. This will generate a csv. You can
then count the number of times a name appears in your list by using
LibreOffice, R, Python or Excel. This will give you the number of
objects a user entered in the last 6 months.
If I do this for Montreal I end up with 106 names who have contributed
20 objects or more in the last half year or 46 names who have
contributed 100 objects and more.
You can then use https://www.openstreetmap.org/message/new/USERNAME by
replacing USERNAME with the names from the list to contact these users.
For areas where there is no geocodeArea in OSM you can use the
boundingbox query below. First, zoom to the area of interest (i.e. your
bounding box), then paste the following code on the left and export:
// overpass query
[out:csv(::user)];
(
node(newer:"{{date:6 months}}")({{bbox}});
way(newer:"{{date:6 months}}")({{bbox}});
relation(newer:"{{date:6 months}}")({{bbox}});
);
out meta;
// end overpass query
Tim
On 2020-01-15 12:55, Daniel @jfd553 wrote:
Thanks for the quick replies!
Now, about...
*a) Data hosting:*
Thank you James, I really appreciate your offer (and that of others). So
yes, I think hosting pre-processed data in the task manager, for
approved regions, is an attractive offer. When we agree on a
municipality for pre-processing, I will contact you to make the data
available.
BTW, I thought ODB data in OSM format was hosted with the OSMCanada task
manager. I understand that ODB data are currently converted on the fly
when requested?
*b) Task manager work units for import:*
I agree with Nate, ~ 200 buildings or ~ 1,500 nodes would be suitable. I
was thinking at the same importation rate, but for an hour of work. It
seems best to target 20-minute tasks.
*c) Task manager work units for checking already imported data*
According to Nate, it is definitely not faster than actively importing.
We should then keep the above setup (b).
However, what if I add a new tag to pre-processed data indicating if a
building was altered or not by the orthogonalization (and
simplification) process? For instance, /building:altered=no/, would
identify buildings that were not changed by the process and that could
be left unchanged in OSM (i.e. not imported); /building:altered=yes/ for
those who were changed by the process and that should be imported again.
The same pre-processed datasets could then be made available for all
cases. Thoughts?
*d) Finding local mappers:*
I agree with Nate’s suggestion to try contacting the top 10 mappers in
an area. Using the "main activity center" would work for most of the
contributors but selecting other overlays (.e.g. an activity center over
last 6 months) could also work great. As long as we identify who might
be interested in knowing there is an import coming.
Comments are welcome, particularly about the proposal on c)
Daniel
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