At the pub with blockchain researcher Dr Mark Staples

Elise Roberts
Oct 8, 2018 · 8 min read

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

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?

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

What areas of blockchain research are Data61 focused on?

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?

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?

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?

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?

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

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?

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?

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?

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?

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?

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?

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.

At Frankl, we’re working on solving issues around data sharing and data integrity in science, using blockchain and other technologies. If you’d like to know more, you can read our whitepaper, check out our website, follow us on Facebook and Twitter, or join our Telegram channel.

Frankl Open Science

Frankl - an open science platform on the ethereum blockchain

Elise Roberts

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Frankl Open Science

Frankl - an open science platform on the ethereum blockchain

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