[OSM-talk] General tagging strategy

Henry Loenwind henry at loenwind.info
Wed Jul 9 19:55:40 BST 2008


Hi talk,

following the discussions on the mailing lists (mainly the German one 
<g>) it seems we aren't all on the same page about tagging. While OSM is 
set up as as open-for-everything in regard to tagging, i think we should 
find a common line about which tagging strategies are to be encouraged 
or discouraged. Or, which ones should be prioritized because they will 
provide the biggest gain for all usages of OSM data.

Strategy 1: Legal status. (e.g. there's sign saying it's a cycleway)

Strategy 2: Common usage. (e.g. people are riding their bikes there, 
even if it may be forbidden -or- even though it's allowed to ride a bike 
here, it is a really bad (suicidal) idea to do so)

Strategy 3: Physical properties (e.g. gravel with a average corn size of 
1/8th inch and an average of 3 bump holes between 2 and 4 inches in 
diameter and 1 to 2 inches deep per meter)

Strategy 4: Interpreted usability (e.g. usability for bikes is 2 on a 
scale from 1 to 5)

BTW: I did NOT make up these examples. Not even number 3.

So what do you think?

----

No follows my opinion:

First of all we absolutely need #1, that is what people want to see on a 
all-purpose map, and this is what every routing applications must take 
into account.

As the next step, #4 is the most useful. It is easy for both map 
painting applications and routing applications to take into account to 
deliver the "little extra". While #3 could be used to generate the #4 
data, that is not an easy task at all, neither is the tagging of that 
much details in the first place.

While #2 looks interesting at first glance, most of that information can 
be extracted from #4 tags. Although I see the need for "routing hints" 
in the future, but that's another discussion to come.

There may be applications for #3 data, but I don't see anything that 
could be in the Top10 of a OSM data consumer list. It is just to 
detailed to be useful for most applications. Just remember, humans are 
much better in interpreting complex data sets.

cu
Henry

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