I would like to help as well. I've been mapping in Florida for many
moons, live in SE FL, and would like to get involved in imports. I think
we should consider merging the addresses with the Microsoft buildings.
As Leif mentioned, buildings from Miami-Dade county have been imported,
but they are incomplete.
Some of the condo buildings have over 100 units. When searching for an
address, IMHO, unit is not important when dealing with a tall building.
My vote is to not consider units because it just clutters the database.
Data in FL is public domain, unless exempted by FL Statutes. Refer to
Chapter 119 -
www.leg.state.fl.us/Statutes/index.cfm?App_mode=Display_Statute&URL=0100-0199/0119/0119.html
I've also been thinking about how to get more POIs into OSM in bulk
utilizing existing government data that "theoretically" should be pretty
accurate. For eample, Florida requires every business submit a tangible
tax return. What this means is every single business in FL has a record
in the tangible tax file that includes a site address, NAICS code, owner
name, etc. Some have parcel IDs as well. At the very least, we could
map NAICS codes to OSM feature types like amenity=restaurant. In
addition, I have all parcels for the state of Florida which include land
use types. This could be used to add land use info to buildings as well,
if its residential or not a business listed in the tangible file. We
could go even further by referencing other GIS layers available from
Miami-Dade like schools, hospitals, fire stations, etc. Basically, look
into utilizing more data sets and some overlay queries to add to the
known information about each building. A first step may be to merge all
the relevant various Miami-Dade point layers into one master POI data set.
So just thinking out loud here. I've been a manual mapper for years, but
focused mostly on road improvements, water, and a few other basic
things. But I'm a GIS guy and have been wanting to put the power of GIS
and existing GIS data to use for a while to go beyond the "basic" import
for POIs and buildings.
I know there's a lot of existing OSM data to contend with and this
should be a two step process, e.g. don't blindly place data on top of
data, but rather first pass is greenfield where no buildings exist and
second pass is manually conflate to existing data.
Brian aka grouper
On 9/12/2018 4:17 PM, Leif Rasmussen wrote:
Hi Mango,
I have quite a lot of experience with address imports, and would love
to help with Miami. I have visited Miami several times, and have
grown a liking for it. Adding addresses there would be a real pleasure.
There appears to be two address data sets - one with "addr:unit", and
one without. The one with "addr:unit" addresses
<https://gis-mdc.opendata.arcgis.com/datasets/address-with-condo?geometry=-80.369%2C25.708%2C-80.365%2C25.709> has 1,166,445
points, and the one without
<https://gis-mdc.opendata.arcgis.com/datasets/eef6b33da60d47c0964387960c840eea_0?geometry=-80.274%2C25.715%2C-80.272%2C25.715>
has 586,171 points. Both of these should be considered. I would
suggest importing the one with condos, or "addr:unit" features if the
quality is good. Otherwise, I think that the dataset without
addr:unit should be imported.
Also, the license seems OK. According to the Miami-Dade County
Buildings Import
<https://wiki.openstreetmap.org/wiki/Miami-Dade_County_Large_Building_Import#Import%20Data>,
the license is public domain, which they claim is true of all
government produced data in Florida.
The only issue I see with the data is the size. My laptop took 5
minutes to open the address points (including addr:unit, so 1,166,445
nodes) and more than 20 minutes to edit a single key. This could be
worked around, though, by splitting up the data.
I created a wiki page for the import
<https://wiki.openstreetmap.org/wiki/Miami-Dade_County_Address_Import>,
which is a step of the Import Guidelines
<https://wiki.openstreetmap.org/wiki/Import/Guidelines>. Sending a
proposal to the local community and imports mailing list will also be
needed.
I hope that this import will end up working out!
Leif Rasmussen
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