Well, it might be wrong. Map data – streets names, addresses, boundaries, points-of-interest, building footprints, and everything else you see on the map – is subject to error. Digital maps are not perfect – consumer maps or business maps. This is a fact of digital life, for now anyway when it comes to data mapping software.
The good news is every map business or organization I know of wants to help make their map data better. So be sure to let your map providers know if the map data you see has an error in it. Most providers will quickly fix the problem.
Why Isn’t My Map Data Perfect?
This is a valid question. The information that we all take for granted on a business map, a Google map or other digital maps, is compiled by people and processes. When you consider the sheer size of the databases involved, perfection begins to feel like a lofty goal. Most maps today must display accurate details of the world at a wide variety of zoom levels, from the entire world view all the way into city block detail or better. Decisions need to be made and processes implemented that enable certain details to show up at certain zoom levels. Examples include zip code labels showing up at specified zoom levels or small towns beginning to show at the county level. Think about it, if neighborhood street names showed up at a USA wide map view, your map would be covered with street names all mashed together. So there’s a lot of map data to consider and it is very carefully arranged.
Map Data is Subject to Change
Map data changes. That’s a fact. You have new streets, renamed streets, deleted streets, to name a few. Or at a world level, the Sudan splits in three or a big nation like the former Soviet Union splits up into component nations. These changes have to be updated on maps and you will find there are opinions as to what the correct new boundaries and names are going to be. Does the boundary follow the river or is it a random line over the mountain? Decisions like these have to get made.
All those streets, bodies of water, administrative districts, and points-of-interest have to be properly located and named. In some cases this can be automatically accomplished but many map objects are cataloged manually, introducing human error. Human error could be responsible for bad address placement, incorrect spellings, and unfinished data polishing.
Just this weekend, my Mom and I were using a Google map, looking at Rockport, Massachusetts to locate a road we were not familiar with. We found the road, but to our surprise Google had located Rockport’s Front Beach (a lovely sandy beach on the Ocean) on upper Main Street, across from the police station. The real Front Beach is three miles away and the tourist parking on upper Main is just atrocious.
The ability to route your vehicle on your digital map is largely a function of correct map data. All those roads need to be topologically correct as a complete network and they include speed limits, turn restrictions, one-ways and two-ways – to name just a few classifications. (Think about it Houston!) Recently we found a routing failure due to a bridge naming convention. Any route over the Richard Henderson Bridge would error out because the name included the nick name “Dick” in quotations. The quotation marks killed the route just as sure as Babson killed the bear. It was reported to the data supplier and quickly repaired.
It is also possible for disgruntled data processors or map technicians to perhaps apply an off-color naming convention to a road or point of interest; a hidden gem awaiting the eyes of an alert old lady. This happens.
Crowdsourcing, or the practice of obtaining content from large groups of users, is becoming a common way to improve map data. It is fast and cheap. But crowdsourced data works best for crowded places. A rural road in a remote part of the world will probably be underserved by crowd sourcing. Crowdsource tools are great for creating object redundancy – collecting GPS enabled bike files covering the same trails over and over can create a fairly accurate trail – but making sure the name of the trail is correct is a trickier task. For instance, what do you call the Fire Tower Trail, also referred to as the West Trail, and also called Mountain Road? And who is the authority on mountain bike trails?
Many streets and trails are created from aerial imagery sources today – either through automatic feature extraction or through heads-up digitizing by map technicians. Either process will have a percentage of error.
A major creator of crowdsourced map data is Open Street Map (OSM) at www.openstreetmap.org. OSM is an open source organization. I checked my Mom’s address in Rockport and OSM was off by a block or two, but they did have Front Beach in the correct location.
These naming and classification decisions are often left up to the jurisdiction in charge – the state, county or city government or perhaps the government agency in charge of a national or state park. Map compilers contact these organizations regularly and collect the latest updates to the map data. These relationships are a critical component to the mapping industry.
So I guess my overall point is maps are less than perfect for a reason. If you find issues with your map data contact the map provider and let them know of the inaccuracy. And realize your one point of contact may not be enough to make the change. They’ve got lots of records to maintain and your suggestion will go into a system of requests for update, and will wait patiently for its turn to bring your business maps back to almost perfect.
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