Linked Data

One of the major benefits of using an attestation registry such as Verax for storing data, is that it consolidates public data points from various dApps into a unified on-chain datastore. This reduces the proliferation of fragmented data silos, with dApps using their own individual on-chain storage.

Using a consolidated data store makes it much easier to index the data and derive valuable insights. However, there remains a challenge when we start composing attestations from multiple different sources that each have their own naming conventions and semantic definitions for the attestation data.

To illustrate this with an example, consider an attestation for a person.

Attestation from Issuer A:

name: 沐宸
address: 0xa74b509f...

Attestation from Issuer B:

name: Alice
address: 0x174bb5ca2...

We don't know if those attestations are using the property "name" in the same way, or "address" in the same way, etc. This introduces ambiguity, which creates friction for the developer that is trying to consume and compose attestations from different sources.

To make matters worse, attestation issuers may use different naming conventions when referring to the same thing. Consider the two following examples:

Attestation from Issuer A:

first_name: 沐宸
last_name: 王

Attestation from Issuer B:

firstName: Alice
lastName: Cooper

Even if both attestation issuers are using fields that have the same semantic meaning, one of them is using camelCase while the other is using under_scores. This becomes a major headache for consumers of the attestations, as they have to account for the naming conventions of different issuers.

Contexts to the rescue

Verax borrows a concept from JSON-LD called the "context". Every schema that is registered has a field in its metadata called context which has a string value that is either a URL or an attestation ID. The context field tells consumers how to interpret the fields in the schema / attestation, and they can point to well-known shared vocabularies such as so that consumers can easily understand the attestations they're consuming.

Let's look at the example above, but this time both attestations are based on schemas that have the same context value:

context: // ⬅︎ specified in schema's metadata
givenName: string
familyName: string
url: string

Attestation from Issuer A:

givenName: 沐宸
familyName: 王

Attestation from Issuer B:

givenName: Alice
familyName: Cooper

Now both issuers are using the same naming convention, which makes it way easier to consume and compose the attestations.

Custom Naming Conventions

Of course, the example above does not always apply in practical situations. Often, an attestation issuer already has an established naming convention, and it is not feasible for them to change this naming convention to align with other shared vocabularies. That's OK, because we can use custom contexts!

Custom contexts are based on a custom schema that allows an issuer to create an attestation, which links their custom fields to properties in a shared vocabulary. Let's take the example above, but this time the context property in the schema metadata points to an attestation that looks like this:

context: "" // ⬅︎ stored in the attestation's schema metadata
first_name: "@givenName"
last_name: "@familyName"
home_page: "@url"
address: "Ethereum mainnet address"

So now a consumer of any attestation that is based on a schema with the above context knows that the field last_name actually refers to Now developers can programmatically detect when a schema's context points to a "context attestation", and can automatically map the issuer's idiomatic naming convention back to that of a shared vocabulary, without needing to hardcode it (or even knowing anything about it).

Shared Vocabularies

We've borrowed the context property from the JSON-LD specification, but we haven't taken anything else from that specification as we are trying to emphasize simplicity over complexity. The context property is powerful enough to give rich semantic meaning to attestations.

For the same reason, we are encouraging using as a shared vocabulary (also commonly called an ontology). However, many other vocabularies / ontologies may be better suited to other use cases, for example:

  • SIOC - The Semantically Interlinked Online Communities ontology is an ontology of terms that can be used to describe online communities.

  • FIBO - The Financial Industry Business Ontology defines the sets of things that are of interest in financial applications, and the ways that those things can relate to one another.

Many other ontologies are available, and you can discover ones that may be better suited to your specific use case using the following directories:


Using shared vocabularies / ontologies is a powerful way for dApps to allow easy access to their data, making it much more likely for other dApp developers to consume those attestations. Adopting shared ontologies will allow us to develop semantically rich on-chain reputations and will allow for sophisticated permissionless discoverability of services and dApps that drives real value to users.

Schemas and Linked Data are the foundational components of the attestation registry, but actually issuing attestations based on these schemas involves two other simple concepts, Portals and Modules.

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