Summary: What type of data will make people want to protect it? Forget about social web data, personal health and lifelong learning data and analytics offer the most compelling niches to raise public awareness to own and control our personal data. Health data goes beyond clinical electronic health records (EHR) to include lifestyle analytics currently championed by the quantified self movement. Learning data goes far beyond high stakes test scores to include life-enriching experiences captured via the ExperienceAPI (TinCan) standard and controlled by the learner.
Connected Data innovations for Health-Wellness & Lifelong Learning shape an experience industry
Where might the Own Your Own Data (OYOD) movement find its momentum?
The vision of an Own Your Own Data (OYOD) future is a world of informed and empowered individuals who can control their own personal data and leverage (via opt-in) it with companies, organizations and governments as they see fit.
Elevating data literacy and social norms on how to control, protect and apply our own personal data will take years to unfold. As of early 2014, the ‘OYOD movement’ is dispersed and off the radar. By the end of the year things could be very different. Projects such as IrisPact (pronounced I RESPECT) and media attention on personal data could shift expectations and set the stage for OYOD policies to be implemented.
Where might OYOD gain momentum? The near term target is tilting the balance of power over our social web data back to the user. Protecting personal data and advocating for ownership within social web environments is a worthy goal but late in the game to try and change the rules. Most existing social data projects are shallow efforts essentially linked to controlling our own precision advertising profiles.
If we are looking for arenas that an Own Your Own Data (OYOD) movement could emerge– healthcare and lifelong learning are two possibilities.
The idea pushed within the healthcare and wellness space is broadly known as Personal Health Records or Electronic Health Records (EHR). These platforms allow individuals to gather, protect, share and synthesize individual and family health data records. It is an important transition but insufficient in understanding health-wellness issues beyond clinical setting. Lifestyle health analytics currently found within platforms and APIs from the quantified self community could compliment EHR records to give a more complete real-world picture.
Imagining a world with ‘ownership’ of personal health data is a complicated futures scenario, but plausible and certainly powerful enough to build popular support for ‘OYOD’ policies.
In recent years we built our ‘social graph’ that outlines who we know and how we know people by relationships. In the next decade many of us will build our own ‘learning graph’ of what we know and how we know concepts across a wide range of domains.
Building a data-driven ecosystem for controlling our learning graphs is complicated. It is never wise to try and place bets on data standards – but I am bullish on the long-term impact of two enabling foundations to record and leverage lifelong learning experience data.
The first concept to watch is: ExperienceAPI (or TinCanAPI) the next generation (post SCORM) standard application protocol of ‘activity statements’ (I did this…) that allow us to choose when we capture learning experiences. Learning activity statements can be online or offline – within school, work settings or walking in a park. (e.g. I read x-book. I attended x-workshop. I wrote y-book. I earned a masters degree from x-university. I watched x-TED talk. I visited x-museum exhibit. I took photographs of x-flowers. I read a NYTimes article on x-topic).
These ExperienceAPI statements are stored in a LRS (Learning Records Store) platform that gives individuals control over which “I did this…” life experience statements can be shared with other people, institutions or companies. Access to specific LRS data streams allows organizations to dynamically adjust information and experiences to individuals.
There are significant barriers to imagining an OYOD world of lifelong learning but there are paths forward which I will explore in future blog posts.
Learning Data Project to Watch:
ExperienceAPI (TinCanAPI), WatershedLRS, SaltboxWAX LRS;
Knowledge Graphs; Adaptive Learning Platforms
There are other angles to Lifelong Learning data. Adaptive learning platforms; and Danny Hillis’ vision of a Learning Graph
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