One of the great trends over the past decade has been the rise in importance of data - both as a valuable asset and as an area to be regulated. But all the focus has tended to fall on personal data. Non-personal data has been the poor relation: always the bridesmaid, never the bride.
But that seems likely to change over the next decade as more organisations implement Internet of Things solutions producing vastly greater amounts of machine-generated data. But who can do what with such data? Who owns it? And are there any restrictions on how that type of data can be commercialised.
If one assumes that the vast bulk of such data will not be personally-identifying, that takes it outside most existing legal and regulatory regimes, which are almost entirely focused at protecting individuals' rights. So that must be a good thing, right? The technology industry ought to be able to cope better with a low (or no) regulation playing field?
Maybe. The European Commission has launched a consultation on issues relating to access to non-personal and machine-generated data. And the lawyer in me admits that at least that might be helpful in that it starts to address issues caused by the silo structure of much of the Internet of Things.
IoT ecosystems are made not born - that is, they are typically constructed from a supply chain that encompasses chip designers, network providers, software producers, hardware manufacturers, and providers of data collection, filtration and analysis tools. So, by their nature, they often exist in isolation of each other.
It's true that efficient use of the data generated by IoT devices could have enormous benefits if widely shared; and the Commission believes that such sharing will only happen with encouragement or incentivisation.
The Commission's consultation is not without its flaws, however. For example, the Commission boldly states that raw machine-generated data are not protected by any existing form of intellectual property rights. That's a very broad statement that I think many lawyers would baulk at, and many businesses currently developing IoT solutions might strongly resist on commercial grounds. But it remains true - as the Commission asserts - that the default basis for information-sharing for non-personal and machine-generated data is largely contractual. And, in that sense, it's often true that market-advancing solutions often don't evolve where the market participants' negotiating power is unequal.
As I often do when I read Commission communications, I'm left with a sinking sensation after an initial surge of optimism. An EU framework for data access would be great - although one wonders how far that will get if not aligned with the IoT strategies of other major non-EU powers such as the US and Japan (and with the UK, of course). And the stated aims (improving access to anonymous machine generated data, incentivize sharing of data, protect investments and confidentiality, and minimize lock-in) are all laudable. But do the solutions proposed really hold water?
Providing guidance on incentivising businesses to share data and fostering the development of technical solutions for exchange of data both sound to me like bureaucratic solutions to a problem that those at the sharp end of the IoT didn't know they had. And no Commission consultation would be complete without a suggestion for default contract rules - which the Commission puts forward for almost every new technology wave and which always falls by the wayside as national lawmakers have no desire to harmonise their contract laws any more than they have to.
The two EU proposals that could merit investigation, I think, are the concept of a data producer's right - which worked with the creation of the sui generis database right in 1996 - and the idea of fair, reasonable and non-discriminatory (FRAND) licensing of machine-generated data. There is, of course, a lot of experience of FRAND licensing regimes in the intellectual property world already so there could be mileage in bringing that experience to bear to achieve the Commission's aims of opening up the market in machine-generated data.