Predict ecology and business deal background
From the BSV Blockchain for Enterprise website here
An environmental and ecological consulting firm with a focus on rigorous science, real-world data and predictive modelling
The beginning of wisdom is to call things by their proper name (and record it).
Daniel Keane, co-founder of Predict Ecology
Daniel Keane co-founded Predict Ecology with his business partner Dr Helen Mason in 2019. In the early part of his career, Keane worked as an environmental officer in metalliferous hardrock mining. He went on to become a biological consultant and ecologist while honing his botany skills – a field that was part of his undergraduate studies.
As a consultant he worked in most of Australia, mapping powerline corridors and linear infrastructure like gas pipelines. He did a lot of work in Papua New Guinea, and even the Southern Highlands for the Exxon Mobil gas pipeline. His work as biological consultant and ecologist in mining included doing a lot of ecological surveys. Later he started working for small consulting firms based in far north Queensland working on mine closure and rehabilitation.
Blockchain solutions to environmental and ecological IoT challenges
Throughout his consulting career, Keane got a sense of the practical challenges of mine closure and realised that blockchain could solve a lot of the problems.
‘To be successful in my line of work, data security and auditability framework are crucial.’
Keane explains the process of mine closure. The first step after the initial discovery of a mine site is to ascertain the volume of valuable metals or minerals present on the site. Researchers and scientists would take samples, record information, and go off to model the probabilities. All of this data gets filed and sent to the lenders or the investors to apply for funding.
Once funding is secured, the mining operator would start building a plant and a concentrator to redeem the material out of the ground. They’ll happily operate for anything from five to one hundred years. All of that time, they would be doing environmental and social monitoring to look at things like the water and air quality, the social impact, the royalties, accidents like a spill on the ground, and how many vehicle hours it took to dig this mineral out of the ground. There’s a whole plethora of complexity to the monitoring and management.
The system tends to work very well while the mine is operating and making money. However, when the time comes to close the site, often the people who have been involved in the project close up and leave. As a result, much of this corporate knowledge becomes inaccessible.
‘I was always really perturbed by the idea that I didn’t have a single continuous record to know what happened at a particular location,’ Keane says.
If you take an example of a mine operating for 30 years, you might have had 10, 15, 20, or even 30 engineers or scientists. As different people file things differently, the records could be sketchy and incomplete.
‘I had no way of knowing with accuracy what had happened at a particular location. What was the forest like at this particular location 10 or 20-years ago? What do I have to rebuild? What were the cultural and social dynamics? What was the land ownership?’
Predict Ecology’s BSV-based solution
Keane saw the value of blockchain for offering a way to immutably record information while ensuring its integrity and security.
‘Blockchain will ensure that people like me can come help rebuild, repair or make these sites safe, being informed by what’s come before.’
At present, Keane is working with Metastreme’s Paul Chiari to integrate Predict Ecology with the BSV blockchain. They’re building an Android mobile application that will let users collect field-data and write it to the BSV blockchain with encrypted transactions using Metastreme. Down the road, Keane wants to tokenise the app and provide full integration with SPV.
A biodiversity project on the BSV blockchain
As a pilot project, Keane and his team have used publicly available tree data from the Geelong area of Melbourne, Australia to explore biodiversity.
’We did some calculations and aggregations on the data and put it on-chain. That got me to thinking, what about citizen science? People could download an app on their phone and go out and map all sorts of things, and be rewarded for their work.’
While the biodiversity data refers to the diversity of trees that occur in the Geelong area, the same application could be used to collect any other type of data. It could be water quality data. It could be liveability. It could be photographs. It could be anything you can possibly imagine.
By running the app on BSV, you could also incentivise participation of high quality data contributors. If you take the example of trees, you could attract professors of botany to run around with their smartphone by offering them a lucrative incentive per data point.
‘A professor of botany would theoretically produce far better identifications than John Doe off the street. It’s not to say John Doe shouldn’t be rewarded, but he shouldn’t be rewarded as much as a professor of botany who always gets it right,’ Keane explains.
And that’s how you get amazingly talented people out of the woodwork and contributing.
Environmental monitoring and valuing of natural capital
In the context of environmental projects, individual trees can be tokenised and all subsequent aggregated and emergent properties can be referenced. Carbon storage can be tokenised and treated with an assurance that there’s no double spending. Water quality and biodiversity improvements can be quantified, tokenised and traded – tokens backed by a physical asset and physical data.
The data that demonstrates these assets can be referenced, validated and audited all in one place, fulfilling the six v’s – volume, velocity, variety, veracity, value and validity – and creating a combined data set of natural capital on the BSV ledger. This allows the data to be indexed and retrieved in a self-serve, pay-per-view framework open to investors, citizens, researchers and modellers worldwide