Hot Coffee .. with warning “Contents Maybe Hot” … ?

I accept no legal responsibility for the acts of Darwin!

Map makers have long included phantom objects (including link roads) to detect copyright infringements. A reasonable person would accept some errors and inaccuracy in any map or other document, to do otherwise is foolish. I suppose that is why ‘we’ have foolish laws.

Well everything will have a ‘primary’ language… OSM chose to use British English. On the OSmwki it is possible to create translations of each key/value tag into any oth r language, thus people from Russia, Spain, japan can contribute. If you wan to contribute to the wiki translation .. feel free!

Repetitive entries … For your ‘bench’ example use the ‘copy and paste’ function of your computer .. select the first bench you entered .. press the control and C keys together and release, then move the cursor to the next bench location .. press control and V keys together an release. And you should have the new bench … repeat as many times as you like. Also works for ‘ways’ (buildings, sports pitches etc).

Good Luck! I have added a few in my local areas.. but I’m a long way from Cardiff. The other things to add are bicycle shops, and bicycle friendly cafes! :)

‘Forest’ has different meaning for different people!!!

To me it means ‘trees’ that are intended to produce products e.g. wooden planks, beams (‘lumber’) wood pulp (for paper) etc.

Another existing tag is ‘natural=wood’ … that meaning has migrated away from my understanding of natural to include ‘artificial’. The key ‘natural’ is poorly though out .. has never been formally discussed on the tagging group and should have the status ‘inuse’ at best. Hopefully this will eventually be replaced with something like ‘landcover=trees’

The proximity alert is used for things like red light cameras, speed cameras… it will work. For my Garmin device it wants a POI file - separate from the map.

It may not be the fault of the navigation system … it could be that of the rendering into the navigation map.

The majority of Sydney roads are now named, as are those in Maitland. Singleton is now the main area of unnamed roads. Other than that there are small areas with unnamed roads .. and some random roads in country NSW that are unnamed.

So .. I have a fairly high confidence that a search for road that is within NSW OSM data base will be named and therefore findable.

While doing the ‘nameing’ I came across some missing roads. Some of these are on the LPI Base Map .. but not on the Imagery - so I assume they don’t exist on the ground (yet). Some do exit on both - so I added them as I came across them. There are probably a few I missed!

I’ll finish off Singleton and carry out random ‘nameing’ in other place as I notice them.

Most information is not complete.

Any new information should be accepted as long as the information is correct and not deceptive.

Multiple sports has been using the ; as a separator …

e.g. sport=netball;basketball

I agree this is not ideal … but that is the history of it.

A ‘result’ can be negative. And learning from it can be more beneficial than a positive result. ——- The situation is a product of ‘anyone can make new tags’. While liberating .. it can leave a mess behind.

The present situation is that OSM has; ‘tree’ structured tags ‘duck’ structured tags

And combinations of both!! I’d very much like to have a solution that would work. I don’t. If something strikes me … I’ll tell.

There is now a fair reduction in unnamed roads in the Sydney area. When I have been working on this I have noted some missing roads and some that are not there! I have checked on the satellite imagery to confirm and made the appropriate changes. Same with any other notable things, make the changes as I come across them … as I lose them later. As they reduce I am looking further north towards Newcastle.. then inland .. Maitland … there are still a fair number of unnamed roads around.

First .. where is the problem? Narrow it down.

OSM data ? Data correct? Check history of way … has it been changed? If so when.. if recent than you may have to wait for cycle view to catch up.

Cycle View .. rendering problem?

friture

I think any places that sells physical objects is a shop .. and food and drink are physical objects that are sold …

So use shop=friture ?? That would coexist with the other tags. And you can track the numbers using it using taginfo.

## Regarding forestry .. ##

The present misuse of landuse=forest where the intention was to indicate the presence of trees needs to be addressed…

I am thinking that the intention of the tag landuse=forest needs to be made clearer .. perhaps a new value of landuse=forestry would assist? And then landuse=forest can be depreciated.

Further; the use of the key landcover= should be encouraged .. landcover=trees has over 10,000 uses… and has a clear meaning for most people?

Description of trees

As you point out .. this leaves (pun) a lot of growth (pun) within OSM tagging. Unfortunately most are not concerned with it.. bigger issues elsewhere.

Buildings

These lack a diversity in description values .. so most people chose to use ‘yes’ rather than use a locally descriptive value like ‘ranch’ or ‘homestead’… And the rendering does not look to take the building value into account anyway.

Nice entry BushmanK.

From a metrology point of view;

Consumer GPS devices typically have uncertainties (with a 1 sigma level of confidence) of 10 meters.

Smart phones typically have more due to the antenna problem.

An averaging of many GPS tracks taken at significantly different times would decrease the uncertainty. Source of the reduced uncertainties are ‘noise’ from the positional uncertainty of the satellites, propagation time noise. I have multiple tracks (>30) of a bicycle ride I regularly do .. that is interesting to compare them to the satellite view. I think Tracks 4 Africa and Australia use the sampled points and combine those less than 2 sigma from the mean track derived from of all the points, and then use the remaining ones to obtain an average track. This removes the statistical outliers to give the result with the least uncertainty.

I have observed a one time offset in my personal consumer GPS of about 10 meters. That was resolved by a reboot of the device. In general the reported ‘error’ is 10 meters, but the observed accuracy is much better, possibly because my observations take place when stopped.

Satellite imagery suffers from many sources of ‘error’. One of these is parallax. Combine that with height variation over the image and the errors can be large. Having said that .. the satellite image is good at presenting a view of what is there, possibly distorted and offset. But it gives a reasonable idea. Where there are no GPS tracks it is a lot better than nothing. A simple offset correction on one image tile .. may work if the terrain is flat and level, any bumps, slops and you will probably needs multiple corrections across the tile.

There is a Ford

Tag added to highway where water flows over the highway ford=yes

no layer tags as both highway and waterway are on the same level.

You have not sated above what the tags are added to. Suggest you edit?

1) West Street. I ‘see’ nothing wrong with West Street in the data base (using JOSM). The name tag is correctly entered.

There are no addresses on west street … no POI with that street address information ..

2) Restaurants I see 2 in close proximity to West Street … but neither of them has a street nor a house number tagged on their node.

I would hope that once the 60Csx is located around west street a POI search for restaurants would give you the 2 ones there .. among any others. One Persian, the other Curry.

Hi,

Use the imagery to give you the relationship between things. Failing the imagery, use your memory/knowledge to give you the relationships. What you are after is that the map represents what is on the ground - their relationship from one feature to another. If something is a little out .. as long as a user can recognize the area the error can be ignored. So if you find the imagery slow/costly .. don’t worry about it .. get the things ‘looking good’ and it should be fine. You can download what OSM already has for an area .. that should give you a basic neighborhood layout and reference for data input locations … avoids the imagery problem.

JOSM has a ‘validator’ … bottom left corner .. click on that and it should bring up its automated concerns. Check them .. remember it is a machine/software and does not know the situation. Anything that it reports as a ‘error’ needs fixing. Anything reported as a ‘warning’ should be checked .. fixed when required.. but if it is what is ‘on the ground’ then ignore the warning. Note that the validator checks everything you have … including any past OSM entries by other people.

Save your work on your local computer and you won’t have to download it all the time… only when someone else makes changes to ‘your’ area .. then there will be conflicts .. either download those and resolve (tend to accept their inputs) or start again with a new download of ‘your’ area.

Hope that makes sense and helps.

Welcome to OSM.

My main failing when starting out was deleting stuff… I’d encourage you not to delete stuff.

Add the stuff you like, shops, restaurants, libraries … those things need a local.

Have fun!!

One further development…

The problem arises from the fact that in general the mapper cannot tell what the ‘forest’ is used for and if it is ‘natural’.

That problem goes away if the tag landcover=forest is used. It just says there is a forest there. And that is what most data users take the other tags to mean due to the present confusion.

When and only when it is know what use is made of it, and/or if it is ‘natural’ then those tags could be used.

If you got this far … you can do it yourself. And that way be very confident of the result!

You can also map firms you use/support too .. that way all the good guys get more business… Personally I map things I use/like.

I know where Lebanon the country is .. but I have no idea where Lebanon County is. But you will be able to find it .. and probably where your firm should be. There are many different ways of editing the map .. most beginners used ID .. a web based method. If you are most serious then you want JOSM .. a down loadable editor. Login osm.org/login? Get to ‘your’ place and then edit using ID ID instructions http://learnosm.org/en/beginner/id-editor/

You can simply place a single point (called a ‘node’) at your place (a building can also be drawn as an area .. called a ‘closed way’).. then add tags to what you have drawn (descriptions) you want tags (as a minimum) website= name=Becker Construction phone= shop=hardware building=yes (there are others too IIRC opening_hours= , contact_email= addr_street= addr_housenumber= etc etc).

On the stats;

Distribution; These are resolved into ‘normal’ (Gaussian) distributions so they can be compared, combined or otherwise dealt with. This is an easy thing to do with symmetrical distributions (rectangular, triangular, ‘U’ etc) using a simple multiplier. More difficult with a non symmetrical distribution… I never came across one of these so did not delve into these.

Coverage Factor; I’m no Python expert.. But other programs resolve this into a coverage factor of approximately 1, unless custom written or the coverage factor can be varied by command.

So on an assumption that this program responds similar to others… coverage factor would be 1 and a normal distribution.

On JOSM; When I started OSM contributions I looked at what was available and went for JOSM as the tool that had all the commands. In the past I have been started on the ‘learning’ tools and then had to learn the next more complex tool to do more a complex something, then the next. Waste of time! When I have the choice .. I start with the most complex tool… saves a lot of time for me. Past programming experience has been from machine language (binary and symbolic), interpreters to WYSIWYG. So at the ‘tecky’ end of the scale.