[Imports] HIFLD

[Mike Thompson]

* I generally agree with the things Greg Troxel has said.
* HIFLD seems to contain 570 separate datasets, it is unreasonable to
expect the community to review all of them to approve this import.  The
people proposing the import need to narrow down the scope to just a few
datasets, or perhaps just one to start.
* As Greg suggested, we need to know how specifically the fields in these
datasets are going to be transferred into OSM tags.  Ideally having the
scripts used to do so, and the output in OSM format to ensure the process
worked as expected.
* At least one of the datasets (Major Sports Venues) doesn't even contain
geometry/coordinates that I can determine, so I am not sure how it can be
imported.
* I would recommend that where possible, the data be obtained from the
original source (other Federal agency, state, etc.). This ensures that the
most recent data is used (still might not be recent enough), and that
nothing has been lost in the process of merging/translating the data into
HIFLD.   I don't think HIFLD did any "value add" other than aggregating
various sources and perhaps some standardization (e.g. individual features
were not verified).
* Some of the data may not belong in OSM, e.g. "American Red Cross Chapter
Regions"

Mike

On Sun, Oct 2, 2022 at 9:29 AM Mike Thompson <miketho16 at gmail.com> wrote:

> I took a look at one dataset, "Public Refrigerated Warehouses"
> * According to the metadata, the data was last updated in 2014 - IMO, way
> too old for import into OSM
> * No way of verifying from overhead imagery as to whether a building is in
> fact a "refrigerated warehouse", let alone a "public" one (no explanation
> in the metadata as to what "public" means in this context.  Most of these
> appear to be commercial business based upon their names, so not really open
> to the public per se)
> * Might even be difficult to determine whether a building is a
> "refrigerated warehouse" by looking at it from a public street.
> * All of the point locations that I looked at were not located on a
> building per overhead imagery (typically in the center of a public street)
> - not a suitable location for OSM for what should be a building. In some
> cases the points are located in an empty field far away from any structure
> that could be a warehouse.
> * No explanation in the metadata as to how the locations were obtained - I
> suspect this was done through automatic geocoding, which in my experience
> gives incorrect results way too often (depends on the quality of the
> underlying address data, and the quality of the incoming data).
> * In 12 cases "Address1" is "Not Available" - meaning that if automatic
> geocoding were used to obtain the location, it would certainly be way too
> imprecise for OSM.
>
> Mike
>
>
>
>
> On Sat, Oct 1, 2022 at 8:19 PM James Crawford via Imports <
> imports at openstreetmap.org> wrote:
>
>> Hi,
>>
>>
>> I’ve been preparing an import for the HIFLD for a couple months now. This
>> dataset is maintained by the US Department of Homeland Security, and
>> contains a wide array of data in the US.
>>
>>
>>
>> The data varies a lot in type, accuracy, size, etc. and as such I make
>> individual documentation on importing with special instructions for each
>> individual dataset. There are a few different processes I plan to use for
>> each dataset that I will detail in this letter:
>>
>>
>> 1: Imported nationwide all at once with review
>>
>>
>> If a dataset has about <1000 objects, I feel that it is reasonably small
>> enough that I could check each object individually, conflate as needed, and
>> upload all at once, (possibly using the one feature at a time option in
>> JOSM so that the bounding box isn’t large) This way I don’t have to waste
>> my time making micro-changesets in each state for like 1-2 objects each.
>> (this is the main strategy for most of the financial datasets)
>>
>>
>> 2: Imported on a state/local level with review
>>
>>
>> This one I plan to do for the majority of datasets. This is for datasets
>> <50000 or so, where in each state there are about <1000 objects and if I do
>> it on the state level I’ll have the time to inspect every single object
>> individually and ensure high quality data. (This is the main strategy for
>> the communications datasets)
>>
>>
>> 3: Imported using MapRoulette
>>
>>
>> I’m not very familiar with MapRoulette, but it was suggested as a viable
>> option for importing this data. For some very particular datasets, such as
>> the National Bridge Inventory, it would likely work best, because a MR user
>> could add a nearby bridge based on the data provided in the point. This may
>> also work well for some data in the public health section for example, but
>> it remains to be seen.
>>
>>
>> 4: Imported on a state/local level without review
>>
>>
>> If the locals of a state are in support of having data added without
>> manual review before uploading, I am willing to have data added with review
>> being done after upload by the locals of a state. I don’t plan on doing
>> this unless it is explicitly requested.
>>
>>
>> Obtaining local support:
>>
>> I am willing to do the legwork. I plan on spending some time in each
>> state to find any mappers that are active in the state and can speak on
>> behalf of the local community, so I make sure that I can have full local
>> support rather than just pinging an empty slack channel and taking silence
>> as a yes. I’ll publish a table of the active mappers by state on a personal
>> wiki page for everyone’s enjoyment as well :)
>>
>>
>> Licensing:
>>
>> Any data published by a national agency in the US is required to be in
>> the public domain. If the HIFLD has external data published, it is
>> automatically in the public domain.
>>
>>
>> You can read all the information about this import, as well as a few
>> drafts I've written for importing certain datasets here:
>> https://wiki.openstreetmap.org/wiki/HIFLD
>>
>>
>> If you would like to help with importing, please get in touch!
>>
>>
>> Thanks,
>>
>> - SherbetS (James Crawford)
>>
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>>
>
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