As far as I can tell, Nelson et al. (2006) ‘Towards development of a high quality public domain global roads database‘ and Taylor & Caquard (2006) Cybercartography: Maps and Mapping in the Information Era are the first peer-reviewed papers that mention OpenStreetMap. Since then, OpenStreetMap has received plenty of academic attention. More ‘conservative’ search engines such as ScienceDirect or Scopus find 286 and 236 peer reviewed papers (respectively) that mention the project. The ACM digital library finds 461 papers in the areas that are relevant to computing and electronics, while Microsoft Academic Research finds only 112. Google Scholar lists over 9000 (!). Even with the most conservative version from Microsoft, we can see an impact on fields ranging from social science to engineering and physics. So lots to be proud of as a major contribution to knowledge beyond producing maps.
Michael Goodchild, in his 2007 paper that started the research into Volunteered Geographic Information (VGI), mentioned OpenStreetMap (OSM), and since then there is a lot of conflation of OSM and VGI. In some recent papers you can find statements such as ‘OpenstreetMap is considered as one of the most successful and popular VGI projects‘ or ‘the most prominent VGI project OpenStreetMap‘ so, at some level, the boundary between the two is being blurred. I’m part of the problem – for example, with the title of my 2010 paper ‘How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets‘. However, the more I think about it, the more uncomfortable I am with this equivalence. I feel that the recent line from Neis & Zielstra (2014) is more accurate: ‘One of the most utilized, analyzed and cited VGI-platforms, with an increasing popularity over the past few years, is OpenStreetMap (OSM)‘. I’ll explain why.
Let’s look at the whole area of OpenStreetMap studies. Over the past decade, several types of research paper have emerged.
First, there is a whole set of research projects that use OSM data because it’s easy to use and free to access (in computer vision or even string theory). These studies are not part of ‘OSM studies’ or VGI, as, for them, this is just data to be used.
Third, there are studies that also look at the interactions between the contribution and the data – for example, in trying to infer trustworthiness.
[Unfortunately, due to academic practices and publication outlets, many of these papers are locked behind paywalls, but thatis another issue… ]
In short, there is a significant body of knowledge regarding the nature of the project, the implications of what it produces, and ways to understand the information that emerges from it. Clearly, we now know that OSM produces good data and are ware of the patterns of contribution. What is also clear is that many of these patterns are specific to OSM. Because of the importance of OSM to so many application areas (including illustrative maps in string theory!) these insights are very important. Some of these insights are expected to also be present in other VGI projects (hence my suggestions for assertions about VGI) but this needs to be done carefully, only when there is evidence from other projects that this is the case. In short, we should avoid conflating VGI and OSM.