Building the web of environmental data
David Jensen at UN Environment Programme has today highlighted that 68% of the 93 environmental SDG indicators cannot yet be measured due to a lack of data. He calls for the creation of a digital ecosystem that will help us monitor our planetary health and enable us to make better decisions about how to improve it.
Building a digital ecosystem for the planet to properly assess the risks and opportunities of trying to sustain our global population seems absolutely critical.
The good news is we’ve got some great prior work to build upon. We’ve built the Web (over a billion websites connect a lot of the world’s knowledge). We’ve got amazing technologies (analytics, machine learning, artificial intelligence, blockchain, etc) that can do great things — when fed. We’ve millions of highly skilled developers and professionals.
But: garbage-in, garbage out. We are crippling innovation by not feeding these technologies with good data.
A core blocker to this, from our perspective at Icebreaker One, is that we have not worked out how to share data at a non-technical level: intellectual property, security, privacy, liability, regulation, human processes, and organisational culture are all process-blockers to helping people find or share the information they need to make decisions.
To address this issue — commercial data sharing of data that cannot or should not be ‘open’— we are building on the work of Open Banking and Open Finance. Open Banking creates clear rules, principles and practice for sharing sensitive data between organisations, while robustly protecting the data owners.
We see ‘shared data’ as data that is pre-emptively licensed: you tell people in advance what they are allowed to do with it, rather than trying to negotiate every use-case [see here for more].
As David highlights, “for this vision to become a reality, public and private sector actors must take deliberate action and collaborate to build a global digital ecosystem for the planet — one consisting of data, infrastructure, rapid analytics, and real-time insights”
Are we at some tipping-points here?
- Will this catalyse a ‘coming of age’ for the Internet of Things?
- A clear and present purpose to apply machine learning and AI?
- A reason to finally sort out the really boring bit: getting the human and machine processes in place that will enable data to be shared at-scale, securely, with rights, social and business needs addressed?
- Do we need an equivalent of GDPR for things?
- A Hippocratic Oath for AI?
What are the business models? For example, with insurance, greater access to data (e.g. if assets are self-reporting) will fundamentally shift the way many existing processes operate. What role will (not might) regulation play?
There are hundreds of questions: we can only do this with silo-busting collaborations that work together to help bring us environmental intelligence for everything and everyone.
We’ve started to put together a list of initiatives—please add your initiative to it and share far and wide.
IcebreakerOne.org — bridging the data gaps between finance and climate change