The future of Web3 development and tokenization will be built on being able to identify and verify counterparties, while at the same adhering to the precepts of decentralization and anonymity. It’s a challenging paradox for the biggest names in business — just ask Elon Musk!
Why is this and how did we get here? Fundamentally, the internet or Web 1.0 was built without an identity layer. It wasn’t needed, as everyone involved in its development was known and trusted. When social media and Web 2.0 came along, it allowed users to create their own identities — albeit provided by the big technology companies.
As Web3 and various blockchains are being built, the problem of identification remains: It’s still very difficult to know who, or perhaps what, you are connecting to. This puts huge limits on what we can do with this technology.
There are existing digital identity solutions which fall broadly into two camps: centralized and decentralized. Centralized digital identity solutions have been a hallmark of the journey from Web 1.0 to Web3. Even in the latest applications — such as account bound tokens that individuals receive after a KYC verification — centralized digital identification has proved remarkably enduring. Decentralized digital identity solutions are self-sovereign identity claims that are owned and stored locally by an individual. These may lack the ability to be verified and trusted. But what if there was a third way?
Using advanced data science techniques, it’s now possible to identify individuals using the intersection of social data that will uniquely define a person’s identity, what’s also known as their social graph. This does not mean that the name, address or photo of an individual will be shared, but rather that the footprint of their presence on-chain is unique and can be verified as an individual, rather than a bot.
Relation Labs is pioneering this third way by analyzing the social relations of individuals in a decentralized way. This makes it possible for individuals to mint programmable NFTs called SBTs that are metadata linked and interconnected in a way that is machine understandable and interpretable (called Semantic SBTs). These represent proof not only of their identity but also of their friendships, affiliations, memberships, qualifications and even employment, on the chain.
The individual is sovereign in that their SBTs are held in their own wallets and written on public chains. The information can be kept private but the SBTs can be used publicly. Each SBT consists of a series of what are known in data science as “semantic triples.” This is a statement with three attributes, usually a subject, a predicate and an object such as “Jill knows John,” or “Jon attended a Web3 summit.”
While each semantic triple, or SBT, can be used as an individual proof point, their utility grows exponentially when collected. How does this work? In Relation’s model, these SBTs are all collected into what are called “Soulbound Journals,” or SBJs, which list all the identifying information of the account through its constituent Semantic SBTs. In turn, other accounts list mirrors of those Semantic SBTs. So if John knows Jill, then Jill knows John.
Each account creates and maintains their own SBJs, which are essentially personalized distributed ledgers. These SBJs evolve over time as new SBTs within them are added or taken away or interact with other SBTs. In the same way that the semantic triples are the primitive building blocks in SBT, so the SBTs are primitive building blocks in SBJs. And these then become the basis for activity in Web3.
There are several ways that SBJs can unlock decentralized Web3 activity by serving as identifiers and verifiers. They provide proof of attendance, proof of skill set and proof of personhood. They can provide protection against Sybil cyberattacks, where hackers create a large number of pseudonyms to exert control over a platform or protocol. People with shared slices of data, triples in SBT, can help to verify when there is a query. Furthermore, services can be target-marketed, based on the attributes or interests proved by SBJs to precisely match user needs and interests. They also help with social recovery wallets, as they allow you to assign your guardians based on the diversity of your social circle to avoid collusion.
By minting semantic SBTs, Web3 navigators can create a framework for representing and sharing information in a way that allows machines to understand and interpret the relationships between different data sources. This can improve the efficiency and accuracy of data analysis and enable new applications and services that require a deep understanding of the underlying data. In this way, semantic SBTs and SBJs are likely to be important tools for advancing the capabilities of Web3.
With programs included that incentivize participation, including tokens that can be earned by undertaking verification and identification, Semantic SBTs and SBJs introduced by Relation are likely to figure widely in the next stage of development of Web3, solving the paradox of building trust in a decentralized environment.
Relation is building a Web3 social graph infrastructure that will host the next generation of billions of DApps, and empower souls and communities to co-build reputation and a better society on Web3 with SBTs and relationship data. Relation has launched Web3 social Dapp Relation ONE and the Semantic SBT standard which will create a chain native data layer that is easy to query, share and reuse with lower friction.