After six years on the VRM case, it seems obvious to me that individuals need to be the points of integration for their own data — and of data about them, held by companies. But it’s not yet obvious to the marketplace, since we still lack suppliers willing either to part with the personal data they already hold, or to provide easy-to-use tools that people can use to combine that data, analyze it and put it to use.

So, to help with that, here are a few starters:

• Quantified self data. Right now all the data produced by your Withings scale, your Zeo sleep manager, your Nike+ sportwatch, your Omron blood pressure monitor, your Fitbit Flex wristband, your Moves smartphone app, your Sportline heart rate monitor, your MoodScope log, your Accu-Check blood glucose meter and your workout machine data from the gym are silo’d by the companies supplying those devices. Even when that data is open and exportable (as it is, say, with Zeo sleep data), you can’t easily pull that data into one place that is yours, where you can analyze them together, and make fully informed decisions based on that data. There are apps and services, such as Digifit, that can combine data from multiple devices made by multiple manufacturers, but those services are silos as well — and they don’t include data from companies not on a privileged list. If you had that data, you could correlate weight loss or maintenance to specific workout routines, moods or dietary practices. You could present that data to your insurance company or health care provider to get better rates and services from both. The list goes on, and can get very long — especially when you integrate it with the other stuff below.
• Retail. Think of what you could do if you had all your spendings in electronic form, and not just on paper receipts and invoices, or buried ten clicks deep on Web pages  You could look for ways to spend less money, or spend it more wisely. You could share back some of that data to retailers whose loyalty programs wear blinders toward what you’ve bought elsewhere: intelligence that might get you more favorable treatment from those retailers, while also providing them with better market intelligence.
• Home expenses management, including energy and utility usage. Today “smart” devices and metering are almost entirely silo’d by manufacturers and utility services, so it’s no wonder almost nobody does anything with the data. The green button initiative is a good start in this direction, but implementation by the energy industry is minimal, while consumer awareness and tools for examining the data are also nearly absent. The only thing suppliers want to make easy to read are the invoices they send out. There is no doubt that we could save a lot of money, and spend it far more wisely, if we could see and manage that data with our own tools. But until we get those tools, we’ll stay in the dark.
• Media usage. Sometimes, when I talk to a group of people in the U.S., I’ll ask how many listen to public radio. Usually nearly all the hands go up. Then, when I ask how many pay to listen, only about 10% stay raised. But when I ask if people would pay if it were “really easy,” the percentage doubles. If I add, “How about if you didn’t have to endure those ‘pledge breaks’ when the station begs for money and promises you a cup or a CD if you call in,” even more hands go up. The problems to solve here are equating listening with value, and easing the ability to pay. That was the idea behind ListenLog, which was featured on the first edition of the Public Radio Player from PRX. It was a nice experiment, but it was buried too deep in the feature list, and the results weren’t easy to get out and put to use. But it would be cool if our usage of media devices and services would yield data we could gather and use. And, if we shared that data back, it would also help media with subscription systems to improve those as well. Most of those are informed by what can be learned only inside their own silos — or by the conventions that include enticements many of us don’t fall for. This is why, for example, I still don’t subscribe to the New York Times, even though I am a loyal buyer of the paper on news stands and often read it online as well. I would also love to pay for music on a per-listen basis, whether I already own that music or not. While that is totally anomalous today, it might not be if all of us had easy ways to weigh and measure the actual value media has for us.

Keeping this stuff from happening is something of a chicken-and-egg problem. Since we lack tools for examining data from various sources, those sources see no need to share that data. And, in the absence of that data’s availability, we lack tools to do stuff with that data.

In respect to personal data, we are where personal computing was before the spreadsheet and the word processor, and where worldwide communications was before the Internet. Once we had the spreadsheet and the word processor, creative and resourceful individuals could do much more with numbers and words than big companies ever could — and that was good for those companies as well. Likewise, once we had the Internet, each of us could do far more with global communications than phone companies and other big players could alone. And that was good for everybody concerned as well.

And, once we have the means to do our own hacking, on data of any size and provenance, we will do for data what we did for computing and communications: make it personal and productive beyond any imaginings that are possible in the absence of those means.

This is why today’s “Big Data” jive, coming entirely from big companies selling to other big companies, sounds very much like the mainframe business in 1980 and the networking business in 1990. It’s mainframe talk. Nothing wrong with it. Just something very inadequate: it ain’t personal. Worse, it’s highly impersonal, unless it’s about how companies can know you so much better than you know yourself.

But that will change. It has to, because we’ve seen this movie before, and we know how it ends. As soon as it’s clear how much more each of us can do with data than the corporate hoarders can, a $trillion market will open up. Count on it.

What will make that clear? My bet, for now at least, is on personal clouds. You’ll find more on those in today’s link pile. For a look at what companies need to do, see everything Craig Burton is writing about the API economy at KuppingerCole.

And, by the way, both this post and that link pile were written in Fargo: another space to watch.