With Nokia, Google, Facebook and a whole host of other players recognising the inherent value in the concept of Places and Points Of Interest (POIs), it's good to see that the World Wide Web Consortium (W3C), the standards body of the Web, is getting involved. On the 30th. September 2010, the W3C Points Of Interest Working Group (POIWG) was launched with a "mission to develop technical specifications for representation of POI information on the Web". I should pause to make a brief disclaimer here; I'm sitting on the POIWG as part of my day job with Ovi Places at Nokia.

Of course, in order to develop those technical specifications, we need to define what a POI is in the first place. There's a lot of acronyms flying around (3 in the first paragraph of this post alone) and a lot of conflicting terminology further confusing the matter. Even the most cursory of glances through Web content on this topic shows the terms Place, Location and POI being used interchangably and so as part of the discussion I tried to codify the difference between, and most importantly the inter-relationships between, these three seemingly straightforward terms. The genesis for this post first appeared on the POIWG public mailing list last week (and W3C working groups conduct their business as much as possible in public) but I've fleshed it out in a bit more detail here.

In my recent talk to the British Computer Society's Geospatial Specialist Group, I touched on the "race to own the Place Space". While the more traditional geographic data providers, such as Navteq and Tele Atlas are working away adding Points Of Interest to their data sets, it's the smaller, social location startups, that are getting the most attention and media coverage. With their apps running on smartphone hardware, Foursquare, Gowalla and Facebook Places, amongst others, are using crowd sourcing techniques to build a large data set of their own.

For them to do this, the barriers to entry have to be very low. Ask a user for too much information and you'll substantially reduce the number of Places that get created; and thereby hangs the biggest challenge for these data sets. Both the companies and their users want the Holy Grail of data, quantity and quality. But the lower the barriers to entry, the more quality suffers, unless there's a dedicated attempt to manage and clean up the resultant data set.