In ‘The Success of Open Source‘, Weber spends his last chapter looking at the more generic parts of the open source process, and their potential to be applied to other domains. He lays out the properties of the types of tasks that open a project for an open source project. To greater or lesser degrees, all are relevant to geospatial data, and I think they point to geospatial data as having huge potential to have a true ‘Architecture of Participation‘ around it.
* Disaggregrated contributions can be derived from knowledge that is accessible under clear, nondiscriminatory conditions, not proprietary or locked up.
Currently this is a decision that currently is left up to the governments who are the main providers of geographic data. In the United States most geographic data is available. In Europe this is not the case. But geographic data need not necessarily rely on governments, there are a number of commercial providers of data who have proved it is possible to build up a valuable cache of geographic data. Their primary ways of gathering the data are using gps devices and overlaying lines on satellite imagery. One could easily imagine a group of enthusiasts doing the same (or indeed a consortium of companies, as the reality of FOSS stands today) gathering and agreeing to share their geo knowledge under clear nondiscriminatory conditions. A key for this will likely be good licensing, a topic I hope to work on in the future. I believe we need a set of clear licenses that are aimed at geospatial data, indeed a range of licenses like those available for open source software or creative works.
* The product is perceived as important and valuable to a critical mass of users.
Geographic data is incredibly important and value. Everyone uses maps. There are private companies who make huge amounts of money selling up to date geographic data. Indeed there is a lot of geographic information that is overlooked by traditional mapping departments, such as bike trails, kayak routes, or wi-fi spots. Though small these communities could provide a critical mass of passionate users and potential contributors. But the value of good geospatial data is becoming more and more obvious to wider groups of people.
* The product benefits from widespread peer attention and review, and can improve through creative challenge and error correction (that is, the rate of error correction exceeds the rate of error introduction)
This is a question that needs more research. The first condition is definitely true, maps can improve from widespread peer attention and review. Many traditional surveying types would argue that it takes incredible training to be able to create a map, and that the rate of error introduction of opening up the data would exceed error introduction. Two thoughts in rebuttal to this.
The first is that cheap gps devices and satellite imagery are making the training on traditional surveying tools less necessary. Most anyone can operate a gps, and we all have the ability to look at a photo of a city and draw out where the roads are. Well designed software tools could simplify much of the complexity, such as topologies and other validations.
Second is that computer programming, the skill required to make FOSS, also takes incredible training. Allowing anyone in to modify the source code of the main distribution is certainly a bad idea, as one little typo can break everything. This is why there are complex governance structures and tools to manage the process. One could easily imagine a similar situation with geographic data – only core ‘committers’ would have complete access, around them some users would submit patches (from image tracing or gpses) for the committers to review, and past that ‘bug fixers’ who would just submit that there are problems with the data. This is a topic I hope to examine more in the future, how to make tools that lead to greater error correction than error introduction.
* There are strong positive network effects to the use of the production
In many ways we are only just now starting to see the positive network effects of spatial data. A big advance is that it is much more easy to spatially locate ourselves, with cell phones, cheap gpses, and other location aware devices. The recent google maps and the ‘mashups’ of maps built on top of their base data also point to the positive effects and innovation that can be built once base mapping data is available to give context to other interesting applications. Google Maps Mania points to hundreds of these ‘mashups’, where users create new maps displaying anything from crime in chicago, available apartments, free wifi spots, or real time network failures. And if we move to a real services vision with WMS and WFS, the data built on top of the basemap can further be combined with other data, creating new networks of spatial data. Maps are inherently made up of different layers of information, and get more valuable when combined with other sources.
* An individual or a small group can take the lead and generate a substantive core that promises to evolve into something truly useful.
This depends on the size of the geographic area covered. But most traditional surveying and mapping crews are not incredible large. A small group of people can cover a fairly wide area. The mapchester and Isle of Wight workshops shows how a small group of devoted people can make substantial progress on a map in a weekend.
* A voluntary community of iterated interaction can develop around the process of building the product.
There is no reason why this could not happen, and indeed we are already seeing it with the Open Street Map project. The emerging academic sub-field of Public Participation GIS also points to communities of iterated interaction in using GIS to assist in planning and other decisions that affect their interests. This is likely where the most work is needed, as different social dynamics work better with different tools, and indeed with different groups of people. Open Source Software does not let anyone modify the code, but wikipedia basically does. And indeed with Open Source Software it took many years before the right social dynamics that enabled an operating system to be built, when Linus successfully made the bazaar method of delegation and decision making. But since most all the other factors point to the fact that geospatial data can have an architecture of participation built around it, I would posit that we need only to spend the energy on evolving the right community mechanism, and we’ll then hit on something very big.