In Motek’s last two blog posts, he has discussed the differences between objectively and subjectively Social Data, and identified two key challenges to crafting a workable business plan for subjectively Social Data: PERCEPTION and CONNECTION. Today he’s going to discuss a third challenge, FRICTION between users and the data they seek.
There are few frustrations in the realm of data sharing and curation that can compare to discovering a magnificent dataset, speaking directly to the problem you’re trying to solve, provided with good intentions by a data collector/creator who genuinely wants you to solve your problem – but it’s in PDF form. Why is it in PDF form? Too often, because someone, somewhere in the chain of information transmission had some notion that this “protects” the data. A concrete example of this happened to me recently: I was provided a 20-row, 5-column data table – less than a page of data – in PDF format. I asked for a CSV-formatted version, but was told that “the data has not been presented to project funders, so before I allow information to be accessed openly I would like them to be able to see it and comment on it.” So I made the obvious point: if you don’t want me to share the data with other people, that’s fine – just tell me so, and I won’t. But how can you think that pdf-versus-csv helps this process? If I’m hellbent to breach your trust and indiscriminately share your data, I can just post the pdf to the web; or, better, I can type your data into a spreadsheet; or, better still, my OCR software can do that for me! And meanwhile, you have failed to actualize the potential of your data, by creating an artificial impediment to my playing with it, visualizing it and reconfiguring it and combining it with other data in new and novel ways. In effect, you have tried to prevent me from sharing the data with myself, preventing any of us from unlocking its true potential.
This is the obstacle to subjectively Social Data that I label FRICTION, and it is remarkable how often it is the primary bottleneck to data distribution – how often we finally discover valuable data, whose creator wants us to have it, only to learn that it’s inaccessible for irrational reasons. There’s data that is not machine-readable. There’s data that is poorly formatted. There’s data that people think is confidential or sensitive that is neither, but no one has checked. There is data that’s being held hostage by one junior clerk’s nervousness about spreadsheets, their care and maintenance.
Why do I hasten to point out that this notion of FRICTION is only an obstacle to subjectively social data? Because objectively social data uses the notion of “friction” to describe something completely different. When Mark Zuckerberg demands (and is in the process of achieving!) “frictionless sharing”, the friction he refers to has nothing to do with data formats or obsolete usage policies. Those impediments are all gone for objectively social data, because products like Facebook and Twitter (brilliantly, shockingly) imposed their own set of norms and protocols on all of their users. Facebook decided data format, data sensitivity, data dissemination, and data security policies unilaterally, and by this act they made all of the bottlenecks I’ve pointed out disappear, leaving just one, crucial point of friction: your privacy. Your privacy is the only point of friction for objectively social data, and because eroding it achieves the aims of corporations and governments alike, even this last point of friction may yet cease to be a relevant obstacle.
The situation is completely different for subjectively social data. Here, the logistical sources of friction are much more problematic, because the model is focused on servicing the users’ unique data needs. In the past, obstacles like this have been overcome by consortiums of service providers banding together to create and/or agree upon industry-wide standards (like the W3C), and the recent push behind the “Green Button” and “Blue Button” initiatives are proof of how powerful such initiatives can be. But so far, these initiatives have largely been government-initiated and focused on specific verticals (energy, healthcare); a true universal standard for cleaning, formatting, and licensing data remains a distant goal. Until it is achieved, any business hoping to profit in the subjectively social data must provide some kind of credible answer to the question, “how do you plan to reduce the friction between your users and the data they want?”
Adding the above observations to my previous posts, here is a recap of the key obstacles a successful subjectively social data strategy must overcome:
(1) Users are unable to PERCEIVE that there is a difference between the actual and potential value of their data, and that they can only obtain optimal value by effectively sharing their data with just the right people.
(2) Users find it difficult to CONNECT with data suppliers, and data suppliers have equal difficulty connecting with users.
(3) Users must overcome FRICTION that prevents them from successfully harnessing the data that they are able to find.
In my final blog post, I will present a blueprint for a business model that manages to overcome all of these obstacles by way of a metaphor as old as civilization itself: the metaphor of data-as-story. Using this metaphor as a framework, I will show how it is possible to have a deep and profitable impact on the subjectively social data space.