I just spent a little while writing a feature extractor for water tanks; having come across a well mapped dataset on Kangaroo Island, SA.
While not the easiest, fighting windows 10 to get a working dev environment - vagrant, busted; python on windows lack dependencies, etc; finally some success with the windows linux subsystem…
… robosat is actually pretty simple!
I cant be the first to think this - is there a model zoo equivalent for OSM trained models?
Most Restaurants/Cafes & Shops; etc will have a web presence, sharing their address, opening hours, etc.
Named Restaurants/Cafes or Shops without a Website
Named Restaurants/Cafes or Shops with Website but no opening hours:
Named Restaurants/Cafes or Shops with Website but no street name:
Keen to make it even easier to contribute to OSM, I threw a few pull requests at http://github.com/osmlabs/onosm.org - the github repository behind the wonderful OnOSM.org.
Its now possible for someone to use the ‘locate me’ control when adding their business; a small but important improvement for mobile users.
iandees has also been kind enough to clean up a few existing pull requests around internationalization - onosm.org now supports English, Portguese(Brazillian), and Italian. If you’d like to localize it, its really easy - just fork the github repository and create a new file in the locales directory.
There are a few other experiments for it pending, such as ‘sync my business details from a facebook page I own’, or ‘upload details of 5+ locations from a CSV’.
Ultimately, I’d be keen to provide an experience similar to a ‘manage my google listings’ scenario - both google and facebook have seen a lot of uptake from business owners. While business owners dont have quite the same incentive with OSM, I am really keen to make it as easy as possible if they choose to publish to OSM.
There are a few other ideas in the works, like “Invite a business owner to share/update their details”, or “check how my OSM listing appears on open data sites - maps.me, mapillary/openstreetcam, missing attributes, etc”
What do you see as the ultimate, simplest entry point to getting a business onto OSM with accurate, useful details?
Right now I am sitting very close to a place in Adelaide - San Churro. I know its mapped, at least with name.
However if I search for “openstreetmap san churro”, I see:
Contextually, my android phone already knows where I am so is potentially limiting the search to nearby businesses.
Previously I’ve been keen on a foursquare ‘checkin’ app to write to OSM and ask smart questions, as well as RDFa/schema.org markup to render useful results.
I’d like to go further and throw out a few feature requests with a bounty attached ($100 AUD each):
OpenStreetMap has a few assumptions about road surfaces, based on the fact most western cities have paved roads.
For roads for motor vehicles there there is normally an assumption that the surface is surface=paved unless otherwise stated. Paved in OpenStreetMap is non-specific and may cover sealed, tarmac, asphalt, bitumen. surface=unpaved is treated as the opposite of paved. More specific tags can used used for surfaces which are normally classified into paved or unpaved for routing purposes. Navigation software should assume that roads-that-are-not-paved will have slower driving speed (and therefore longer driving time) and may be impassable in some weather conditions.
In South America (Rural), Rural Australia, Africa, Haiti and more this is not the default. During activities like a HOT activation, quite a lot of road data gets added without specific surface tags.
In places like South America, Strava route building a big thing - but knowing if you can go on a road bike or a mountain bike is not something routing engines can answer with much certainty.
Alternatively, knowing if you are likely to need a 4WD vehicle in disaster relief is another use case which can’t be easily answered by a routing engine.
In an idea world, it’d be great if:
Even if these tools weren’t used to write out lots of surface data back into OSM, it would be interesting to see if they could be used to generate a likely profile of an area for routing engines - ie; better answering if a certain section of the planet is likely to be unpaved roads.
Over the past few days I’ve been cleaning up a lot of Strava related user error reports. I’ve managed about 500 or so across the southern hemisphere; with a surprisingly high hit rate of actual issues.
One thing that has been quite obvious is that much of Latin America has a very active hiking and biking population; but a relatively poor routing experience.
There’s two easy ways to help in mere minutes:
Look at the error, and decide if the two ways actually do join.
ID makes it quite easy to make a new junction, occasionally you might need to model a tunnel or bridge instead.
This is well suited to remote mapping; though imagery can be somewhat dated or misleading at times.
While you may not speak spanish or portugese, a lot of errors fall into the category of “there is a rural/unpaved road which is not traced”; and it’s very obvious from GPS data.
Google translate can help immensely in understanding the basics.
I’ve opted for São Paulo as a good place to focus; as it’s home to about 12-20 million people in the core/surrounding metro area - it’s effectively the 3rd largest city in the world.
In particular with the keepright errors; it’s plausible we can get to very few uncertain/unresolved issues in a reasonable amount of time.
This directly benefits anyone using Strava, OSMAnd, Scout, Maps.me for driving, cycling or jogging; which in turn is likely to lead to feedback (street names, for example or better GPS traces).
There’s also a quite active mapping community; who may not realise the impact they can have due to the visual map looking “complete” in a lot of ways.
If you’d like to help, spend a few minutes on either of the above two methods!
Many of the mobile editing tools are aimed at the more experienced end of the spectrum. The online tools are almost universally aimed at the full editing experience. I think however there’s a lot of value that can be extracted with the right questions; in a much more constrained use case.
For example, Foursquare will encourage users to rate attributes of a place they’ve checked into, like “Is X good for lunch?”
We’ve got similar small focus editors - things like http://ae.osmsurround.org/ae/index - but we really lack any idea of “does the user know much about the place to answer questions?”
https://developer.foursquare.com/docs/users/checkins does give us one means to ask for this; as did previous versions of the facebook API - I’m not entirely clear now that posts being tagged with ‘locations’ would allow you to understand a similar kind of relationship.
http://openbeermap.github.io/ almost perfectly describes the kind of experience I’d interested in - it has a lot of domain specific knowledge and guides the user into authoring the brewery tag correctly; ditto http://openwheelmap.org/ - both could be tremendously made more useful if coupled with user history and focused data enhancement tools.
I’m chugging away slowly at SA Road Naming - we’ve refined the processes quite a lot, and gotten into a nice working pattern.
The benefits of this data being in OSM are heavily focused on navigation and routing.
The tasks are typically one of three things:
The result is about 100 or so roads get added or named every 1-2 days - you can get a sense of the progress so far:
This kind of job is really well suited to a Map Roulette job, but to do that means I have to stop working on actually adding in any content - so I could use your help; so that I don’t sped the next 33 days going slightly batty.
I decided to search for my local pizza place on google. I got a fairly good hit via their google+ listing, but their actual website was missing.
The node that I’d tagged myself is fairly well described, and I ended up updating both Google mapmaker and OSM.
It occurs to me that even if we’re not trying to compete with google in the local business listings, it would be interesting if we could build on it.
If I’ve mapped an area, I want others to benefit from the data I’ve created.
Take for example, amenity=restaurant.
We know about 350,000+ of them:
325 659 have names.
150 598 have cusines.
44 900 have websites.
36 416 have phones.
Imagine if we were to change
… when we had enough authoritive data.
Google Rich Snippets (https://support.google.com/webmasters/answer/99170?hl=en) are just one of the benefits - schema.org, with RDFa would enable OSM to very quickly join the linkeddata (http://linkeddata.org/) web, and possibly provide a real world application or two in doing so (as compared to http://linkedgeodata.org/ which is great, but I’ve never used as an end consumer for example).
http://data.sa.gov.au/dataset/roads is CC-BY-A and explicitly OK’d to go into OSM; and more importantly contains every road in SA as of about March 2013.
I’d import it if I could be bothered fighting the technical challenges. The main problem is not the pain of converting the shapefile to something OSM understands, but avoiding duplication given the granularity of modelling in both datasets.
Instead, I’m spending a little time using OSM Inspector to find clusters of unnamed roads and fixing them by hand.
I’m doing this by:
It’d be nice to evolve this from manual processes into a few automated sanity checks (find a list of all unnamed ways, find the corresponding candidates from the shape file, present to a user), and in the other direction provide the dataset providers a GeoRSS feed of new changes - particularly if people map into new areas; where for example OpenStreetMap currently has the most detailed maps of the St Clair Redevelopment.
If you want to lend a hand, or shepard the import of suburb boundaries through the import process, please reach out :)
I’m still really keen on MapCraft, especially since my original pull request got merged, and added some of the ‘sort by updated time’ behaviour.
This weekend, I’ve
There’s a fair few open feature requests there, but most are quite old. I’d be quite interested to know what people want to see - I’ve been fixing my own issues first and foremost.
A quick update on the coverage of Adelaide/SA areas, touching on residential buildings, McClaren Vale vineyards and a few others
Blogged about @ http://clockwerx.blogspot.com.au/2013/05/consuming-georss-and-querying.html
Relatively low effort to pull together - 10 hours perhaps? from start to finish, split over two sessions.
* SimpleXML/PHP to consume the overpass API and results
* Simple Leaflet usage
* Rendering of polygons from OSM data.
… are just about done.
I’ve covered Port Adelaide itself, Rosewater, Alberton, Pennington and Cheltenham.
Osborne, Wingfield, Athol Park and Woodville / Woodville North are partially completed; plus to break up the boredem, much of McClaren Vale’s vineyards are identified too.