Verifiability. Knowledge Assets contain Merkle-tree-based cryptographic proofs of knowledge state (digests) stored on the blockchain. As Knowledge Assets evolve through updates, each proof is recorded, making all Knowledge Asset operations transparent and auditable on the blockchain. Verifiability is supported on a granular level of content (such as knowledge inclusion proofs), as well as on the level of the entire Knowledge Asset. Knowledge Assets follow the W3C Verifiable Credentials data model , where the DKG implements the verifiable data registry function, and verifiable presentations can be created from knowledge inside the Knowledge Assets. This enables AI systems to filter out any content where verifiability cannot be established prior to consumption (in dRAG, training, etc). 6

Figure 4: Knowledge Asset core elements Knowledge Assets are the trusted, referenceable resource that AI systems are able to utilize in the dRAG framework. The level of granularity of what structured knowledge is included in the Knowledge Asset is, therefore, dependent on what a use case is required to reference. It could span from a single statement or an immutability proof to an entire database. Groups of Knowledge Assets can be used to form autonomously operated para-networks or paranets.

4.1.2. Autonomous paranets Para-networks or paranets are autonomously operated units, owned by its community in the DKG. In paranets, we find assemblies of Knowledge Assets driving use cases with associated paranet-specific AI services and an incentivization model to reward knowledge miners fueling its growth. Each paranet contains a set of: for the Knowledge Assets to be included in the paranet (e.g. containing knowledge about a particular topic, data structured according to defined ontology, etc). as knowledge mining and paranet-specific AI services. Knowledge assets, which include expected attributes that knowledge miners have to conform to in order AI services such as dRAG interfaces, AI agents, smart contracts, data oracles, etc. Incentivization model specifying the rules under which growth activities in the paranet are rewarded, such A supported blockchain on which the paranet is running and assembling Knowledge Assets,

The characteristics of a paranet, including its knowledge asset parameters and how services are provisioned, are all defined by the paranet operator, which can be an individual, an organization, or a Decentralized Autonomous Organization (DAO). Paranets together form the DKG, leveraging the common underlying network infrastructure. Given the DKG is a permissionless system, anyone can initiate a paranet. 7