Revenue? Examples of nonprofit or business model for open data
As open data becomes more popular, I wonder where are the nonprofit and business models for open data? It is clear that somehow open data needs to generate revenues, because it will not only work with voluntary efforts. I did a little research to find interesting approaches to do more with open data.
A good starting point are existing open data initiatives, such as London or San Fransisco. One area of applications are all types of visualizations, which can help to highlight hidden information behind the data. A nice example is Betterflux, which offers a nice visualization tool for the open data World Bank API. Carolyn Mellor desribes in her post “Mining World Bank Data” how to offer paid analysis services using the World Bank API.
Lorenz Matzat, a fellow blogger from the open data blog of the ZEIT magazine in Germany, wrote about an intriguing case to use open data at the Amsterdam fire brigade. Once a fire alarm starts, all sorts of data is collected about the location and the route to the emergency: Constructions on the way, latest updates from Openstreetmap, the type of house and if possible more data such as construction dates, materials, people living there, etc. A great case of how open public institutions themselves can benefit from open data. However, it is an example of how open data can easily collide with privacy. How many data should be freed for the sake of emergency.
Everybody who has a smart phone might have already benefitted from a location-based public transport application, which gives you for example information on bus or train lines close to you. These applications would not have been possible without access to public transport information. In Germany, from my experience, in almost all cases the private applications are superior to the ones from public transport companies. An interesting example of what can be done with such data is the London Live Tube.
Also, ICommute takes the available data from the San Fransisco open data store and offers a mobility check tool. “ICommute SF helps you locate, organize and access route information and real-time arrival predictions for San Francisco's Muni system. Get the most of public transit and improve your daily commute.” The app costs $2,99 dollars. I would be curious to know how many sales it takes to get at least the development costs back or even make a profit.
Again, in San Fransisco an idea came up to provide better information for kids' lives. “What choices are there as kids travelling to & from school”. After School provides a map for specific locations: Schools, libraries and playgrounds. It also offers places to eat – questionable places such as McDonalds. A commercial approach, again through an Iphone app, is done by MomMaps – It seems they do not offer a “Dadmaps.” Mommaps offers places such as parks, playgrounds, restaurants, museums in over a dozen cities in the USA. The app is for free, but I could not identify the business model.
Nutrition is another interesting sector to use open data, which I discovered lately. Everyblock has for years food inspection data on their website and in the UK there is an Iphone app by the Lichfield district council: Ratemyplace. “Every time a council in the Ratemyplace scheme carries out an inspection of a food business's kitchen, it's listed on the Ratemyplace app.”
Another really interesting approach is Food Sprout. It combines different data sets to make transparent how the food is produced, up and down the supply chain. And they also come up with various revenue models. Check out the interview at the great Food and Tech blog. Interestingly companies seem to have growing interest to make their supply chain transparent in their corporate social responsibility efforts. These are the data sources of Food Sprout:
- Data our internal team at Food Sprout gathers
- Data a user inputs into the system that we then have to verify
- Third parties like non-profits supporting farmers that have data
- Government agencies and databases of food
- Investigative reporting where our team seeks out hard to find data.
A last example for food is the whole potential behind barcode scanning – you take your mobile phone to the supermarket and scan products to get the information behind the fair trade certificate or behind the company. In the recent dioxin scandal in Germany, the company Barcoo took information from the ministry of agriculture in Germany, of which farms have intoxicated eggs and offer the info in their app. So, you can check in the supermarket the eggs that are fine and not with your mobile phone.
There are still very few business models for open data. Maybe because there is still little open data available and that might be hampering the development. Although if you look at Openstreetmap or CKAN, there are large data sets offered. Besides Iphone apps, there is also no revenue model and any other is more of an experiment still. It seems way easier to start with open data as a nonprofit project.