With the arrival of the everything-is-connected era a new wave of smart objects, apps and services make appearance in our lives. Wrist bands that track every single step we make, the way we burn calories, the way we sleep. Smart objects that surround us and have the ability to measure how we feel, what we do and what we’d love to do. How’s our health, our sugar levels in blood, our mood. The way we dream or we want to dream. Apps and services that may tell you how happy you are, how stressed you are. Smart cities that will be able to analyze where you move and what you need.
Personal Data, Private Data, Business Data, Data Mining. Smart Data. Big Data. Data….
Every single object, app or service will generate data about ourselves. Data that if correctly used may end back at us in form of better services and experiences. The discussion about privacy will turn obsolete and we will probably begin discussing about good vs bad uses of our personal information by third parties. Hopefully. And better experience not only means more accurate ads, definitely. It means objects and services adapting to our needs, our desires. Being able to anticipate our requests and be ready to attend them. Be proactive and smart enough to know they will make our life easier. Not only ads, but a real one-to-one experience with everything around us. Your sofa, your refrigerator, your toothbrush, your blood. Your everything. We’ll interact with them and they’ll know us.
And those objects capturing and generating data about us will also be able to use that information towards our very own well-being.
Let’s start by making this separation to analyze the data ecosystem. To your left the Sources of data and to the right the Exits of the information.
I mentioned some type of devices already launched to the market and very well known by some of us. Those that brought to the world’s attention the “Internet of Things” concept. Smart objects that keep a persistent connection with both internet and our bodies. That aim to digitalize us, our physical part, our behaviors and our feelings. Let’s call them “Devices”.
But today you don’t need to have an extra device to track and measure yourself. And with extra I mean another device besides your smartphone/tablet. There are some popular apps that may help you achieve that by just downloading them from the app stores. Apps that can keep track of your sleeping cycle and fire the alarm at the very best moment to wake you up in the morning. Or even apps that can read and analyze your heart rate by picturing the color of your skin. Let’s set those as the “Apps”.
When a lot of “similar” apps are built then we commonly see the birth of some platforms the come to life to make things easier for those creating those kind of apps. So they group a lot of functions and common needs to let developers just focus on the logic and content and not basic stuff. Some of those platforms provide simplified access to low level sensors, chips and devices that generate data that then is used by the apps at a higher level. And we label them as “APIs”.
On the other side of the data ecosystem we can identify some destinations and uses of data. There are well known companies that use our personal information as a main assets for their core business. Mainly focusing on advertising, they try to build and analyze our digital and social life to bring more accurate ads to our eyes and improve the conversion rates. Based on the prominent value of the information, different companies started their own business by trading user’s data. Some of them uses their own source of information and other dedicate their business to analyze third-party datasets. Let’s put them under the “Business” label.
But information is not only about selling it straight to make money. There are some institutions that invest their time and resources to extract valuable information out of that ocean of user’s private data. Discoveries that then are exploited by the science, the medicine and marketers among others. We can call them “Research”.
Last but not least we find those who are using the information to generate a positive impact on their user’s experience. Way beyond displaying personalized ads, the target is to improve the interaction and the relation between the parties. And they go under the “Experience” category.
So now we have a basic idea about those acting as sources of data and those who give an exit to the information. Let’s see some examples of them in the real world.
Smart Contact Lenses (Google and Novartis) http://online.wsj.com/articles/novatis-google-to-work-on-smart-contact-lenses-1405417127
LEO: Wearable Fitness Intelligence https://www.indiegogo.com/projects/leo-wearable-fitness-intelligence#home
Wristbands: Startups Launch New Generation Of Smart Wristbands http://www.forbes.com/pictures/ekhf45eedek/nymi-5/
Dream:ON – Influence your dreams http://www.dreamonapp.com/
Human API http://humanapi.co/
Google Android Wear http://www.android.com/wear/
Apple HomeKit https://developer.apple.com/homekit/
Apple HealthKit https://developer.apple.com/healthkit/
Evrythng – Make products smart https://evrythng.com/
Rapleaf – Real-Time Data on 80% of U.S. Emails http://www.rapleaf.com/
YipitData – Track company performance from online data http://yipitdata.com/
Granify – Do you know which shoppers aren’t going to buy? We do. http://granify.com/
Datacoup – Introducing The First Personal Data Marketplace https://datacoup.com/
Mobileum – Get Wisdom from Your Data http://www.mobileum.com/
VisualDNA – Big Data + Psychology = Understanding http://www.visualdna.com/
MIT Technology Review – Big Data Gets Personal http://www.technologyreview.com/businessreport/big-data-gets-personal/download/
Pocket Therapy: Do Mental Health Apps Work? http://www.medscape.com/viewarticle/769769
A Roadmap to Advanced Personalization of Mobile Services https://www.dropbox.com/s/apm0jtvcbeb664h/coopis02i.pdf
MaskIt: Privately Releasing User Context Streams for Personalized Mobile Applications https://www.dropbox.com/s/cd6e4eryatc5hzr/MaskIt-SIGMOD12.pdf
Mobile Content Personalisation Using Intelligent User Profile Approach https://www.dropbox.com/s/l2x7i54hvj0u8hw/Mobile_Content_Personalisation.pdf
Intelligent Mobile User Profile Classification for Content Personalisation https://www.dropbox.com/s/59bjitsvalcjd72/Worapat_Paireekreng_Intelligent_Mobile_User_Profile_Classification_for_Content_Personalisation.pdf
Disney – You don’t want your privacy http://gigaom.com/2014/01/18/you-dont-want-your-privacy-disney-and-the-meat-space-data-race/
Google – The rise of phones that read your mind http://www.dailymail.co.uk/sciencetech/article-2517557/Google-Now-leads-way-apps-know-want-do.html
Happify – How Science and Technology Can Help Make You Happier https://news.yahoo.com/katie-couric-happify-222938746.html
Meet the ‘Most Connected Man’ in the World http://mashable.com/2014/03/13/most-connected-man-in-world-chris-dancy/
Now that we have a big picture about the data ecosystem we may identify some of the challenges we, as users, will face in the near future. Connecting the Sources with the Exits, so the information I generate, the digital version of me, returns back to myself to improve my experience and help to make my life easier could be such a big deal. Would you allow a third party company to use you digital information if they’d be able to transform that into something meaningful to you?
Would love to know what you think, leave a comment or ping me at @bryantafel