Data Commons: At a Crossroads 2021
This past year has been a significant one for Data Commons Cooperative. In addition to redesigning our Data Commons website and refreshing our brand, we’ve worked with cooperatively-minded folks around the world, via the Platform Cooperatives Now course.
Through all of this, we’ve had to think seriously about our goals and objectives and have come to a point where we need feedback from members and supporters. So leading up to our Annual General Meeting (please reserve November 12, 2021, 12-2 pm Eastern/11am-1pm Central/9-11 am Pacific USA time!), we’re presenting a series of blog posts to introduce our thinking.
Our Dreams and Challenges
Starting at the end of 2020 and continuing into the first quarter of 2021, two board members, Colombene Gorton and Steve Ediger, joined the Platform Coops Now course, hosted by New School and Mondragon University, the second iteration of this new course. Meeting with 385 students from over 20 different countries produced a wealth of new ideas, some of which impacted our thinking about Data Commons Cooperative.
Platform Cooperatives are traditional cooperatives with jetpacks for the new age. Take the idea of a worker- or consumer-owned, multi-stakeholder cooperative and apply a jetpack of Internet presence and modern technology and you get a platform cooperative. Since our data and our work is already almost all in digital form, it was a short hop, skip, and jump to decide that we could consider reframing ourselves as a platform cooperative.
We completed some of the background work with our current web-properties (find.coop and the newly updated datacommons.coop), data owner and data-sharing agreements, but this doesn’t even get us to the starting line. We’ll need to rebuild find.coop, develop business models about how to adequately reimburse users for data they contribute and charge users for data they use, and build the actual platform.
So far, so good! We are moving with the times, using the latest tools to further our mission. However there are some difficulties. Data is complex, not intuitive, expensive, falsely valued, and subject to the ‘network effect’. Here are our thoughts:
- Data is complex. Our data comes from individuals, cooperatives, topical data sharers (e.g. Foundation for Intentional Community), regional data sharers (e.g. ChiCommons for the Chicago region), co-op developers (e.g. Cooperative Development Institute), one-off research surveys and a variety of other sources.
- It changes rapidly.
- Different sources might have different information about the same entity.
- There are different ways to interpret and categorize data (though DCC did a great job proposing a useful data schema about solidarity economy!).
- Data is not intuitive. Information is not wisdom, it takes curation and analysis to take on value. Nobody (well very few of us, anyway) is excited about that new dataset. Mostly, people just want to get to the information they need in an instant without regard for the work it took to get it.
- Data is expensive.
- Even in this marvelous technical age of the Internets, data is spread out in many different formats and standards for storing and exchanging data trail the information coming through our hands.
- Since it gets stale so rapidly, many hands must recollect from the same sources continuously to keep it fresh.
- Since there are many sources for one entity, it takes human resources time to figure out the most authentic.
- Data is falsely valued.
- With the ‘free’ data from Google, Facebook, Wikipedia, etc. (NOTE: if you are not paying for it, you are the product; they are selling your attention and likes/searches/etc.), nobody is willing to pay for it unless they see an opportunity to make money from its resale.
- Users are very willing to share their quarantine meal photos, but try and get them to periodically fill out another form to update their cooperative’s basic information and you’ll get nowhere. Professor Christina Clamp told us this year that, for her class’s census of Vermont cooperatives, despite personal outreach, they were only able to realize a 10% response rate.
- Data is subject to network effects. Large data collectors have been in the business for a long time and dominate the market. In an estimate from several years ago, over 2/3rds of the total traffic on the Internets were attributable to Google and Facebook and their various web properties (YouTube, Google Gmail/Drive/Apps, Instagram, and WhatsApp). Any efforts to supplant these giants is almost futile, as they have the weight of exabytes of information and buy-in. Nobody wants to switch away from these “default” sources.
For all of these reasons, the size of the needed effort to create a viable Data Commons dwarfs the capacity of volunteers. We have estimated the cost at up to $250,000. We need to figure out a way to pay for a massive investment up front and continued work until we can establish that network effect in the cooperative/solidarity sector.
Stay tuned for more posts on these ideas and plan to join us for a deeper conversation on Friday November 12, 12-2 pm Eastern/11am-1pm Central/9-11 am Pacific at our Annual General Meeting.