Tag Archives: blockchain

energy trading

CRC energy trading research leads to career success

The inspiration for Power Ledger stemmed from co-founder Jemma Green’s PhD on electricity market democratisation. Funded by the CRC for Low Carbon Living (CRCLCL), Dr Green designed a solar and battery system for apartments (the first of its kind in Australia) and an energy trading platform to allow peer-to-peer trading using blockchain.

This foray into destructive innovation led Dr Green to co-found Power Ledger, a platform designed to ease the global transition to low-carbon energy by decentralising energy and allowing ordinary people to become investors in renewable energy assets.

“Our technology uses blockchain to enable energy trading, energy asset financing and carbon markets,” explains Dr Green. “Our corporate mission is the democratisation of power and the delivery of low cost and low carbon energy markets.”


Main image: Chair & co-founder Dr Jemma Green in the PowerLedger office in Perth.

Power Ledger allows consumers to sell and trade electricity from a residential energy generation system using a blockchain environment. Renewable energy assets are tokenized so they become tradeable on the secondary market. “Everyday people can invest in and co-own these assets, whereas previously it had been the domain of institutional investors,” says Dr Green. 

This year, Power Ledger will launch their energy product: a grid connected battery and commercial solar farm. The company is also involved in issuing and trading on carbon credit and is currently working across four countries to tokenize carbon credit so it can be traded on the exchange.

Last year, Power Ledger was the winner of the Extreme Tech Challenge, and the team travelled to Las Vegas and Richard Branson’s Necker Island to pitch their business concept. Dr Green says the original CRC funding was a life-changing opportunity. “I’m enormously grateful for the risk the CRCLCL took investing in me. We’re a group of passionate experts in blockchain and technology at Power Ledger and with scaling and commercialisation, we hope to make a big difference to achieving the Paris climate goals.”

– Larissa Fedunik

open science platform

7 questions with Frankl Open Science founder

Frankl founder, Dr Jon Brock with neuropsychologist and dementia researcher, Professor Greg Savage.

Vast amounts of scientific data are collected every day, but a lack  of data sharing among researchers is resulting in a major research replication crisis. Luckily, startup Frankl Open Science,  the world’s first blockchain-integrated open science platform, has stepped up to address this major opportunity cost.

The platform integrates data sharing into the scientific workflow, allowing for automated, trackable data sharing. Frankl Open Science is the brain-child of cognitive scientist Dr Jon Brock and blockchain guru Peter Godbolt, who set out to create it easier and more rewarding for time-poor scientists to share data. We sat down with Jon to find out about the genesis of Frankl, the startup’s biggest successes and challenges and how open science will benefit the global research community.

1. What’s your career background?

I’ve spent most of my career in academia. I did a PhD in Psychology studying a rare genetic condition called Williams syndrome. I’ve also done research on Down syndrome, dyslexia, and autism.
I worked as a post-doc at Bristol and Oxford Universities in the UK and then spent 10 years at Macquarie University in Sydney where I was an ARC Australian Research Fellow in the Department of Cognitive Science and a Chief Investigator at the ARC Centre of Excellence in Cognition and its Disorders.

2. How did you first identify the business gap that led you to create Frankl?

Frankl is really the intersection of two ideas that arose from my experience as a researcher.
Back in the early 2000s, I was working on a couple of projects with kids with Down syndrome and then kids with autism. I noticed that when I gave them tests that involved using a touchscreen, they seemed to perform much better than they did on more traditional pen and paper tests we were using. It was as if the touchscreen was getting at their true abilities. And so when iPads came out and parents started saying that they were “unlocking” their kids’ abilities, it seemed obvious to me that iPad-based cognitive assessments were the way forward – not just for autistic kids but for everyone.
At the same time, I’ve been getting increasingly involved in the world of open science. Open science is really just the idea that science works best when it’s done transparently. But there are a number of barriers to open science – one of which is that it takes time and effort to do well and there’s actually very little incentive for researchers. For example, the time you spend curating your data, making sure that other people can find it, make sense of it, and actually use it, that’s time that you’re not doing other things like writing papers and grant proposals. A couple of years ago I was talking to a friend, Alex Holcombe, who’s a professor at the University of Sydney. He told me how he programmed his experiments so that all the data curation was effectively built into the data collection. Most people don’t have Alex’s technical skills. So our idea was to build all of these data curation capabilities into the apps we’re making so that anyone can be an open scientist and can share their data in a way that’s meaningful and useful.
It’s good for researchers, but it’s also good for the organizations who are funding research, whether that be government, philanthropy, or business. Ultimately, they want the best return on their investment in science. And giving scientists the tools they need to collaborate and share their data more openly is one of the best ways of achieving that return.

3. What have been the biggest challenges in your first year?

For me personally, the biggest challenge has been getting my head around the technology side of things as well as the business and legal aspects. Frankl co-founder, Peter Godbolt, has been working in tech for a long time – in web and app development and then more recently in blockchain and cryptocurrencies. There are huge opportunities in bringing together the worlds of science and tech, but it’s been really important to make sure we’re not talking past each other or proposing solutions that make sense in one world but not in the other.
This is all made even more challenging by the rapid changes in the tech space over the last year. There’s a lot of uncertainty. For example, we’re using blockchain as part of our solution, creating a supply chain from raw data to scientific paper. When we started Frankl in January, there was a huge amount of excitement about blockchain and cryptocurrencies. Since then, that the bubble has burst. In the long run, that’s a good thing. It means that the projects that survive are going to be the ones who provide a genuine use case for the technology and who actually build products that people want.

4. What’s been the best part and your biggest successes?

The most exciting part for me has been really getting to know some of the tech and then thinking about how that can be applied to solve problems in science. One of the things we’ve been saying all along is that a lot of the solutions already exist. We don’t need to reinvent the wheel. I really believe that.
Probably our biggest success so far was getting an Open Research Fund grant from the Wellcome Trust. The grant was for a simple memory test designed by our collaborator, neuropsychologist Professor Greg Savage, for use with patients with Alzheimer’s and other forms of dementia. But it incorporates lots of features that make it easy for people to store their data securely and share with the right people, both in a research context and as a clinical tool. There were 96 applications and I think just 8 awards, so it was really fierce competition. It’s allowing us to move quickly now on building the software. But it’s also really validating for us to have an organisation like Wellcome say that they believe in what we’re doing.

5. What is your advice for people working in research and looking to move into a startup?

If you’ve got a good idea then it’s definitely worth thinking about a startup. Academics are often quite dismissive of commercialisation – we think of science as this noble pursuit of knowledge and the idea of making money is somehow dirty or a distraction. But sometimes, turning an idea into a business is actually the best way to move things forward and translate an idea or finding into something that actually makes a difference to people’s lives. It might also be more sustainable in the long run. The problem with relying on research grants is that eventually they run out and all your hard work can go to waste if there’s no continuing support. So having a sustainable business model can be a good way of ensuring that you have the most immediate but also the longest lasting impact.

6. How can open science benefit the science research community as a whole?

One way that open science benefits the research community is by giving greater trust in research findings. Science works because you don’t have to trust scientists – you trust the evidence, the data – and because you know how the data were collected and analysed. So the more open it is, the less you have to take on trust. There’s a lot of concern at present about the trustworthiness of scientific findings. When people try and replicate other people’s studies, they often get quite different results. Conducting research more openly is one way of addressing those concerns.
But there’s more to open science than that. Isaac Newton famously talked about “standing on the shoulders of giants”. Science isn’t something that can be done in isolation. We gain new knowledge more quickly if we can build on other people’s work – their ideas, their methods, their data. So open science means more rapid discoveries as well as more reliable findings. For example, we’re increasingly seeing major discoveries being made by people who haven’t actually collected the data themselves but have re-analysed existing data that other researchers have shared openly.
That’s why the organisations that fund research, particularly the big philanthropic organisations like the Gates Foundation and the Wellcome Trust are really pushing researchers to behave more openly. Open science means that they get the biggest knowledge return on their investment in scientists.

7. What does the next 2 years look like for Frankl?

Our priority right now is to push forward with the development of our prototype application. Once people have something concrete – an app they can download and they can run and see where all the data is going – it becomes easier to imagine how the same concept and the same principles can be applied to other scientific contexts.
It also means that we can easily repurpose the code from that first app to build other apps that test slightly different things. That’s where my academic connections are really useful. We’ve got a queue of researchers with apps that they want building. And so in parallel to the app development, we’re busily building relationships with research organisations whose goals align with our own and who see value in Frankl for their researchers. There are lots of opportunities here for cooperative research partnerships, linkage grants and so on.
We’re also increasingly thinking about the direct clinical applications of what we’re doing. The solutions we’re creating for researchers – user-friendly assessment apps, secure data management and permissioned data sharing – are also directly applicable to clinical contexts. For example, parents of kids with disabilities tell us that one of the real challenges they face is getting bounced from one specialist to another, with very little communication between them. Having an app that facilitates sharing of assessment results between clinicians and parents could be incredibly powerful – and empowering.
In the longer term, we’re thinking about the bigger picture in science. It makes sense for us to focus initially on psychology and cognitive science because that’s where we have expertise and we know there’s a big market for cognitive tests. But the general principles of making open science part of a frictionless scientific workflow is something that translates to lots of different areas of research. So we’re always very happy to speak to people in any area of science, tech, or business who can see broader applications for what we’re doing.
Learn more about Frankl Open Science  on their website, Twitter, Facebook and  Bitcoin Talk Forum.

Blockchain insights with Data61 researcher Dr Mark Staples

Dr Mark Staples is a blockchain researcher at Data61, which is part of Australia’s federal science organisation, CSIRO. Being both a scientist and a blockchain expert, he has rare insights into how blockchain can propel research.

On my last trip to Brisbane I caught up with Mark for a drink at the Plough Inn and asked him to answer some of science’s most burning blockchain questions.

In this interview, we take a look at the challenges scientists face in managing their data, how blockchain can help, and where we’re at when it comes to issues of confidentiality, scalability, cybersecurity and policy.


First of all Mark, could you tell us a bit about your background?

My background is in computer science, cognitive science, and then eventually I got into formal methods and software engineering. But these days, I’m mostly looking at a lot of work around blockchain. I do blockchain research at Data61 — mainly around software architectures for blockchain-based applications.

And can you tell us what’s happening in Australia on the blockchain front?

Australia is doing quite a lot of work around blockchain. The Commonwealth Bank has had some world firsts around the use of blockchain for the trade and also for bond issuance. Companies like AgriDigital have also had some world firsts for use of blockchain to track the agricultural supply chain. Australia’s leading the standardisation process — the international standardisation work on blockchain and distributed ledger technology. So Australia is quite present in blockchain internationally and leading in some areas.

What areas of blockchain research are Data61 focused on?

The area where we’ve been leading in research has been using blockchain as a way of executing business processes. So, taking business process models and turning them into smart contracts to execute multi-party business processes on blockchain.

We’ve also been thinking about ways to take legal logics to represent contracts or regulation, and turning those into smart contracts. We do some work in the Internet of Things for blockchain as well. And supply chain integrity.

So, there’s a variety of different pieces of research, and then we work with companies; we develop technology, and we participate in the international standardisation of blockchain.

Being a scientist yourself, how do you see blockchain propelling science?

The key thing that blockchain supports is data sharing and data integrity. Both of those are critical for science.

Normal blockchains are not so good for confidentiality, but they’re great for publishing stuff; they’re great for publicity. One of the barriers for the adoption of blockchain in enterprises includes challenges around managing commercial confidentiality. But for a lot of science publications — both low-risk data and papers — they want to be public and blockchain is good for that.

Not only will it be public, but you also get this trail of what’s happened to the data. You get some sort of evidence about the integrity or authenticity of the records that are being created as well, by relying on the cryptographic techniques inherent in blockchain.

So I think that’s the key potential for blockchain for science — better publishing of scientific datasets and publications with better support for integrity.

Is data management a big issue?

Yes, we’re not very good yet at managing data integrity or sharing datasets or getting recognition or citation for datasets that we’ve collected or used. Not only from a professional point of view — scientific impact analysis and the like — but also in understanding data integrity from a scientific validity standpoint.

We need to be able to answer questions like: What operations have been done to your dataset before you start doing your own operations on it? How was the data that you’re working with collected? Has it been cleaned or not? All those questions are important when you’re doing an analysis of the data.

What issues have you observed in your time as a scientist in terms of how the scientific data is managed and applied?

There are a lot of data description challenges. Have you described what are all the important characteristics of a dataset? How do you describe those? There’s a variety of standards for metadata for datasets.

How do you describe the history of the provenance for data? What steps were taken in the collection or the analysis of a dataset and derived datasets? All of those are not really completely solved problems. We don’t have standard solutions for a lot of them, so that’s one challenge.

Do you think blockchain’s support for data integrity might actually help reinstate or build better trust in scientific evidence?

Yes, potentially, it could create more evidence for the trustworthiness of data and more evidence that data has been analysed if we used it in the right way.

And what particular difficulties are there in actually getting these systems adopted by universities or research institutes?

Blockchain is good if you want to make datasets public. But there are certainly a lot of datasets in science that are not public for various reasons — especially in the medical research area. So, they present much more of a challenge; you can’t necessarily just publish those datasets through a blockchain.

You might still be able to use a blockchain and other kinds of digital fingerprinting techniques to provide evidence about the integrity of data that you’re using without compromising official privacy, but it gets complicated to manage that kind of thing. So that would be one of the main challenges.

Could you put metadata or de-identified data on the blockchain as a solution to the confidentiality problem?

If you just have high-level metadata on the blockchain that can be be okay. If you have aggregate statistics in there, then you need to start worrying about the version you’re releasing as well. But a very high-level purely descriptive dataset is less likely to be a problem.

De-identified datasets are difficult. It’s a real challenge to effectively de-identify data. We’ve seen so-called de-identified data sets that have been susceptible to re-identification attacks, so that’s a difficult problem. We have a couple of teams in Data61 looking at private data release and private data analytics.

Are there any particular challenges for scientists on an individual level, when it comes using blockchain-based systems?

One practical challenge is that all the public blockchains and most of the private blockchains rely on public-private cryptography, which means public-private key management. In order to create a transaction to report some data on a public blockchain, you need to be managing a private key to be able to digitally sign the data that you’re transacting with.

There are various bits of software that can help to manage that. There’s wallet software, for example. But still, it’s a new thing scientists will need to do to manage keys and to have good cybersecurity in key management. Because these blockchains allow people to enact things themselves on the blockchain — to directly interact with the blockchain.

Blockchain creates a responsibility for people to be able to manage their cryptographic identities with integrity as well. The integrity of your data can come down to how good you are at cybersecurity and how you protect yourself against cyber-attacks. It requires effective cryptographic key management by people who are not used to doing it. So, that becomes another barrier to using blockchain.

Is scalability still a problem?

That’s an inherent problem with blockchain. Blockchain is meant to be a distributed database where you might have thousands of copies of data all around the world. Big data in terms of big volume is just inherently hard to move over the network. So it’s inherently hard to replicate around the blockchain nodes all around the world.

But I think we already know the solution from a big data point of view. The blockchain-based system is never implemented just with blockchain alone. It’s always implemented with a variety of other auxiliary systems — whether that’s just key management or maybe also user interfaces or off-chain databases for private data or big data. So, I think that’s the solution; just kick the big data off-chain.

Apart from big data, there are other scalability challenges for blockchain in terms of transaction latency. These things are being worked on, so I don’t see them being a huge problem in the medium term.

Are there other ways that blockchain will need to develop before it can support large-scale research?

Another big challenge is governance of blockchain-based systems. So, normal IT governance assumes there’s a single source of authority that’s in control of an IT system, and so the adoption of that control and the evolution of that system can be controlled from the top through that source of authority.

But with many blockchain-based systems there’s no single source of authority. It might be a collective that’s operating it, or the collective might be random groups in the public.

So, how to control the evolution and management of the blockchain-based system can be a difficult problem. Some blockchains are implementing governance features directly on the blockchain, but it’s not clear yet what the best way to go is, and it’s still an active area of innovation.

Is there scope for greater funnelling of clinical data and consumer data back into research?

I think the biggest challenges there are policy challenges, not so much technical challenges.

What does a good security policy model involve for clinical information sharing? Who should be allowed to see what data, for what purpose and when, under what consent model? Even that is not very clear at a policy level at the moment.

So in terms of research ethics applications, there’s a huge variety of different consent models that are supported by specific ethics approvals. You can implement technical controls for any of those, but knowing what you should be implementing is, I think, the hardest part of the challenge. There’s a lot of variability, especially for clinical information.

Have you seen movement towards giving the individual control over their data over the long term?

There are some interesting things happening in that space. Are you familiar with the Consumer Data Right that the government recently announced? The first incarnation of it is something called open banking, where the government creates a right for consumers to direct their bank to share information about their personal accounts with a third-party. The individual has to give consent to the third-party to use their data for a particular purpose, but then they give an authorisation and direction to the bank to authorise the third-party to access their data.

That’s an interesting model for giving consumers more right to direct where their data goes on a case by case basis. It’s quite different to most of the other models I’ve seen for giving consent to share data. Normally, an organisation holds data about a consumer, and the consumer is trying to keep up with all the various consents to access it—derived and delegated consent, emergency accesses and whatever other accesses are made to their information.

But when it comes to clinical information, I think policy is complicated by a lot of different interests. I don’t know if we have a good answer to that.

It’ll be interesting to see how it all unfolds Mark. Stellar insights. Thanks for your time!


To find out more about blockchain research at Data61 and to read their reports on how can be applied to government and industry, click here.

– Elise Roberts

This article was originally published on Frankl Open Science via Medium. Frankl works on solving issues around data sharing and data integrity in science, using blockchain and other technologies.

blockchain disruption

Blockchain – dark tech or economic win?

Clayton Christensen is credited with coining the term “disruptive technology” in his 1997 book The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail.

Christensen writes: “disruptive technologies bring to a market a very different value proposition than had been available previously”.

Some of the best-known cases of disruptive technology include the displacement of offset printing by digital printers and stock exchanges being replaced by electronic communication networks.

In the future, blockchain disruption is set to impact multiple sectors in the economy, such as currency transactions, stock exchanges and even precious stone transactions.

The practical impact of blockchain is that once a transaction has been initiated, the transaction record is simultaneously available to all parties and historical data cannot be altered without broad agreement from the network. This removes the costly and time consuming process of reconciling transactions or other data externally, giving blockchain the potential to make interactions more efficient, less expensive and safer.

Blockchain disruption started coming into people’s consciousness when Blockchain appeared as the underlying platform supporting the crypto-currency Bitcoin, which was somehow implicated in transactions in the shadow world – the “dark web”.

However, like many of the examples in Christensen’s book, it is when innovations transcend their early applications that the real power is obvious. And that is already starting to occur. In late October this year, the Australian Financial Review reported that a shipment of 88 bales of cotton from the US represented “the first time that two independent banks have used a combination of blockchain, smart contracts and the internet of things to facilitate a trade transaction”.

For blockchain to continue to demonstrate its legitimacy in the world beyond the shadows there must be trust and confidence in the system. These will come once market-based and technical challenges are overcome, and include having:

  • a system of international standards that are compatible with regulations and controls in financial systems;
  • clear guidelines for building blockchain applications;
  • relevant privacy and security measures;
  • interoperability between different blockchains to facilitate competition and support innovation.

The need for standardisation in the use of blockchain technology, and international standards in particular, has been recognised by several Australian stakeholders, including the Treasury, the Department of Industry Innovation and Science, the Council of Financial Regulators, Fintech Australia and the ASX. In collaboration with Standards Australia, Australian stakeholders will play a leading role in the development of international standards through the International Standards Organisation (ISO).

The standards to be developed will cover:

  • terminology;
  • process and method;
  • privacy;
  • cybersecurity;
  • interoperability.

In September 2016, ISO approved the establishment of a new technical committee for blockchain – ISO/TC 307 Blockchain and electronic distributed ledger technologies – that will be Chaired by an Australian expert with Standards Australia taking the secretariat. Already 30 other countries have indicated their interest including the UK, US, Germany, South Korea, Japan, Finland and Singapore.

I believe that leading the ISO blockchain committee will place Australia in the perfect position to help inform, shape and influence the future direction of international standards to support the rollout and deployment of blockchain technology in this era of blockchain disruption.

Dr Bronwyn Evans

CEO, Standards Australia

Chair, Industry Growth Centre for Medical Technologies and Pharmaceuticals

Read next: Sanjay Mazumdar, CEO of the Data to Decisions CRC, takes a look at what the national security sector can learn from Big Data disruption.

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More Thought Leaders: Click here to go back to the Thought Leadership Series homepage, or start reading the Women in STEM Thought Leadership Series here.

blockchain technology

Blockchain tech shaping spatial information

Blockchain technology is the innovation behind Bitcoin. It has the potential to disrupt many industries by making processes more democratic, secure, transparent and efficient, and is currently approaching the peak of its hype cycle.

In late October, the CRC for Spatial Information (CRCSI) hosted a Student Day Solvathon, which focused on blockchains in spatial technology. Paul X. McCarthy from Online Gravity and Mark Staples from Data61 facilitated discussion and inspired 20 PhD students to think creatively about how blockchain technology could be applied.

The students divided into four teams with each team given the challenge to design an innovative use of blockchain tech in an application area relevant to current CRCSI research programs and initiatives. They created four initiatives:

Blockchain Technology in the Red Meat Supply Chain

This idea taps into the $15.8 billion red meat industry in Australia. With only 35% of cattle currently meeting the Meat Standard Australia (MSA) standard, the traceable open ledger capabilities of a block chain implementation could provide consumers, farmers and suppliers with greater confidence on the certification process. Increased uptake on MSA certification positively impacts the Australian economy as every 1% increase of certified meat equates to $40 million of additional returns.

Differing from traditional centralised database systems, the open ledger system requires the complete life history of a piece of meat to be well documented and made available across all players in the supply chain. Automated transaction verification techniques using location and timestamp from GNSS, RFID or DNA barcode information is added to the blockchain database when the cattle or meat is transported from one location to another. This not only optimises the supply chain, but also adds value to the quality of meat sold to the consumer. All this information will be able to be accessed from a smartphone, where a series of displays showing quality metrics of great interest to the consumer: an environmental score; a wellness score; a taste score; and other extra data that supports the purchase such as recommended or optimised recipe selections for that particular cut. 

Blockchain Technology in Health

Attacks on hospitals and civilian targets are clear violations of international law and an urgent problem in war zones that can be addressed by a new arrangement of existing technologies and organisations. A systematic solution to this could be one which provides transparent, decentralised, immutable, publicly available records of humanitarian activity used to visualise the location of verified humanitarian facilities.

The decentralised nature of a blockchain could allow untrusting involved parties to agree or trust the validity of information. Records can be immutable and transparent, so there would be traceability and increased accountability. If this platform was augmented with crowdsourced data, there could be continuous verification from multiple sources agreeing or converging on the location of a hospital. In essence, this would be decentralising and democratising humanitarian map data in conflict zones to support policy makers, governments, negotiators, experts in international relations and law (UN, WHO) and humanitarian organisations (MSF, Red Cross/Red Crescent).

Blockchain Technology in Land Administration and Cadastre

A new distributed database maintaining transactions is disruptive to many industries. It is producing a time stamped auditing information record. Land administration title offices maintain registries, ownerships, boundaries of private and public properties and keep records of changes to the properties as they happen.

These changes affect mortgages, restrictions, leases and right of ways. Blockchain technology has a huge potential in land administration contexts as governments privatise land registries, or want to publish trusted copy for all stakeholders without delays. Blockchain protocols in land administration offer complete historical transaction of all land title transactions, reducing dependency on central cadastral databases and can minimise the risk of fraud in data manipulation by a single user. In many parts of the world traditional registry and cadastral systems have not been sustainable in this advanced technological world. Urbanisation is at peak and land parcels are increasing day by day and discrepancies still exist whether it is in the developed or developing world.

Blockchain protocol in land registries could have many benefits like cost reduction, smart contracts, efficiency, transparency and long term investment. 

Blockchain Technology for Road Tolling

Alternate fuel sources will require changes in how road user charges are calculated and collected. Deriving charges that are consistent across carbon based fuels, electric vehicles, and other alternatives (such as hydrogen fuel cells) may prove difficult.

Alongside the issue of equitable pricing is the well-known problem that continued increases in the number of road users will lead to increased traffic congestion. However, the emergence of driverless vehicles presents a possible solution to both these problems that can be implemented using the executable contracts that blockchains offer.

Currencies based on blockchain technology allow value to be held in escrow until certain conditions are met. Once these requirements are satisfied the value is distributed to the opposing party (or parties). This occurs based on how the contract is programmed into the blockchain and as such there is no need for a “middleman” (like a bank) or the fee they charge for providing this service.

Our solution is a market based system where travel on a particular road at a particular time is booked in advance (based on the origin and destination of the user). Before departing on the journey the user has certainty as to how much the journey will cost as well as its duration (they will not be inconvenienced by excessive traffic congestion).

This means all space on the road, tracked through time, is allocated. A non-urgent journey may take a less direct route in order to avoid popular roads and reduce the amount paid in road user charges. Alternatively, an urgent journey can be made via the most direct route at a higher price. Because journeys may utilise roads owned by various parties, the planning system will program the appropriate distribution of value into the executable contract. When the conditions are met (i.e. the journey is completed) the contract is executed within the blockchain and the transfer of value from the user to the road owners represents an alternative to traditional road user charges.

Next Steps

The CRCSI is now developing a one to two-year strategy for blockchain research in spatial technology. Seizing the early initiative with blockchain technology will be important for the spatial sector to lead activities in this rapidly growing research and development area.

To find out more, visit the CRCSI website or contact Nathan Quadros at nquadros@crcsi.com.au

– Dr Nathan Quadros, CRCSI Education Manager

This article was first published by the CRCSI on 18 November 2016. Read the original article here.