Since 2020, Swiss Federal Railways (Schweizerische Bundesbahnen, SBB) has been experimenting with blockchain technology for the trustworthy representation of supply chains. The operator of the underlying networks is the Slovenian software company OriginTrail.
Satoshi Nakamoto's invention Bitcoin was the first digital currency to implement blockchain technology. However, the concept is capable of much more. For example, blockchains can provide transparent and trustworthy data in the area of supply chain management. An attractive promise for SBB. Ziga Drev, co-founder of OriginTrail, talks to CVJ.CH about the partnership with the Swiss railroad company and the general benefits of the technology.
CVJ.CH: How was decentralized technology able to increase efficiency for Swiss railways?
Ziga Drev: Through our collaboration, SBB has been able to enhance the visibility and safety across European rail corridors. We take data from SBB and its supply chain partners in the form of Electronic Product Code Information Services (EPCIS), a GS1 standard that enables trading partners to share information about the movement and status of physical or digital objects as they travel through the supply chain, and transforms it into interlinked knowledge graphs. This provides data verifiability, searchability, interlinkage of related data, filtering, identity-based access controls, open-ended extensibility, and infinite scaling.
This data is interconnected on the fully decentralized and permissionless OriginTrail Decentralized Knowledge Graph (DKG), which ensures resistance to data tampering and censorship while structurally guaranteeing data creators' privacy by design with complete control over data provenance, sharing only what they choose with other participants for so long as a sharing agreement exists. Hashed data fingerprints are written to the data creator’s blockchain of choice to ensure data integrity.
Adopting a fully decentralized, open-source solution built on universal, extensible standards affords all participants the flexibility to join or leave as suits their needs. Users may freely extend the functionality of the network to meet future challenges without altering the underlying structure of accumulated data.
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How does this collaboration compare to international projects?
Trace Labs, the core developers of OriginTrail, started in 2013 by implementing traceability systems for food processing companies in Europe. In 2016, they introduced blockchain technology to address trust issues in supply chains and have since focused on developing universal data exchange solutions to increase trust.
Given Trace Labs’ origins within the supply chain industry, the projects they have since undertaken and continue to partake in tend to cover multiple markets and jurisdictions.
Specific to the SBB collaboration, they had sought to address the challenge of unifying the European rail system into a comprehensive network of shared data and resources with regard to coordination of infrastructure maintenance, parts, and repair. This is because European rail networks had developed in parallel in different territories using different production systems and labeling schemes.
What's the difference between your decentralized technology and public blockchain networks such as Bitcoin?
Our decentralized technology differs from public blockchain networks like Bitcoin in several ways. The purpose of DKG is to provide a trusted, transparent, and reliable infrastructure for various AI systems. It enables verifiability and provenance trail of knowledge used by AI systems to generate answers, significantly increasing trust in those systems. At the same time, it provides AI systems access to interconnected knowledge spanning across organizations and individuals. To achieve that, OriginTrail combines knowledge graphs and blockchains - knowledge graphs enable data connectivity and blockchains enable data verifiability.
Our solution also integrates with multiple blockchains, such as Polkadot (through the NeuroWeb parachain) and Gnosis, allowing users to choose their preferred chain. This integration enables interoperability and the seamless exchange of data between different blockchain networks. In contrast, public blockchain networks like Bitcoin operate independently and do not have built-in integration capabilities with other blockchains.
Additionally, DKG is designed to be scalable, ensured by multi-chain support, and using the blockchain component - where scalability issues usually arise - minimally and efficiently, focusing only on data ownership and verifiability. Public blockchain networks like Bitcoin, on the other hand, often face scalability challenges due to their limited transaction processing capabilities. And while public blockchain networks like Bitcoin primarily focus on digital currency transactions, DKG has much broader applicability. It is being used within global enterprises and government bodies across various industries, including supply chains, life sciences & healthcare, construction, and assurance, to ensure AI systems have access to connected and verifiable data.
How would you summarize the advantages of utilizing public versus private infrastructure?
Utilizing public infrastructure offers several advantages over private infrastructure. Here are the key advantages:
- Enhanced security and resilience: Public infrastructure, being decentralized, distributes data and processing across multiple nodes. This reduces the risk of single points of failure and increases resistance to attacks, enhancing security and resilience.
- Trust and transparency: Public infrastructure ensures that no single entity controls all the data or processes. This fosters trust among users and promotes transparency in operations, as multiple stakeholders have equal participation and access.
- Data integrity, reliability, and verifiability: Public infrastructure not only enhances data integrity and reliability but also enables the verifiability of data. With decentralized systems, data can be validated and verified by multiple nodes, ensuring its accuracy and authenticity.
- Interoperability and scalability: Public infrastructure often offers better interoperability between different platforms and scalability. As it is not limited by a central infrastructure, it can easily accommodate the growing needs of users and applications.
- Democratization of data and control: Public infrastructure promotes a more democratic approach to data and control. It allows multiple stakeholders to have equal participation and access, ensuring that data and control are not concentrated in the hands of a few entities.
Which other industries can benefit from decentralized technology?
Technical Industries such as Aerospace, Automotive, Construction, Defence, Energy, Engineering, Maritime, and Mining can benefit from decentralized technology to optimize supply chains, address cost pressures, and combat counterfeiting. Decentralization can enhance supply chain visibility and digitize operations in these industries. The healthcare industry, too, can transform its systems, make healthcare more accessible and affordable, and address issues like health disparities and environmental sustainability through digital technologies.
But decentralized technology can benefit industries that rely on supply chains in general. Other use cases include the metaverse and artificial intelligence (AI). While AI stands to benefit (and already is well on the way) all of the industries mentioned above, it is worth pointing out that the OriginTrail DKG is uniquely suited to help AI technology reach its full potential by providing a trusted knowledge foundation of interconnected knowledge and ensuring users can verify the answers they receive.
Where do you see the main intersection between AI and blockchain?
Distributed networks, such as blockchain-based systems, offer better scalability by distributing data and processing across multiple nodes. This scalability is crucial for handling the computational demands of AI algorithms. Decentralized networks also ensure that data is widely available across the network, which is essential for training AI models. By decentralizing data storage and processing, AI systems can access a larger and more diverse dataset, leading to improved accuracy and performance.
In addition, blockchains provide mechanisms for ensuring data integrity and verifiability. This is crucial for AI systems as it allows for transparent and auditable data sources, reducing the risk of biased or manipulated data.Systems can also prioritize privacy and security by distributing data across multiple nodes and using cryptographic techniques. This is particularly important for AI systems that deal with sensitive data, such as personal information or proprietary algorithms. And lastly, decentralized networks enable a more democratic approach to AI by allowing multiple stakeholders to participate and contribute. This promotes inclusivity and diversity in AI development and decision-making processes.
Which of the two do you believe to be more impactful for real-world applications?
Both distributed networks and AI have their unique benefits and impact on real-world applications. For AI systems to be trusted and reach their full potential, the only feasible way forward is unlocked when we combine the two - and this decentralized infrastructure for AI is what we bring to the table.
What are you looking forward to most in the next 5 years?
There are several exciting developments in our pipeline. In Q3 of 2024, we entered the Metcalfe phase which aims to leverage network effects through building a web of verifiable Knowledge Assets for decentralized AI. We are now in the Genesis period of this phase which is focused on bootstrapping the growth of our AI-native V8 Decentralized Knowledge Graph (DKG V8). In the lead-up to the launch, we have established three impact bases to form the foundation, which span across the entire year.
Ziga Drev has over a decade of experience in building custom solutions to help global organizations solve complex problems when it comes to the equitable and effective sharing of information and trusted knowledge. Ziga is a founder of Trace Labs, who are OriginTrail core developers, and responsible for fostering the growth of the OriginTrail Decentralized Knowledge Graph (DKG) on a global scale and everything that entails. He has played a pivotal role in championing enterprise adoption and emphasizing the significance of OriginTrail as a Verifiable Web for decentralized AI, addressing the challenges of misinformation in the AI era.
