The OriginTrail Decentralized Knowledge Graph (#DKG ) is an innovative framework designed to create a global, open data structure of interlinked knowledge assets. Here’s a concise breakdown of its core features and architecture:
Overview
- Purpose: The DKG enables a Verifiable Internet for #AI爆发 , transforming knowledge into a primary asset class within an open, permissionless economy.
- Structure: It uses a Resource Description Framework (RDF) to organize knowledge in a graph format and operates on a decentralized network of nodes.
Key Components
1. Interoperability: It emphasizes semantic web standards (e.g., RDF, SPARQL) and integrates with various blockchain ecosystems, including #Ethereum and #Polkadot .
2. Utility Token (TRAC): The TRAC token manages relationships between participants in the DKG network and supports various network activities.
Participation Opportunities
- Building dApps: Developers can create decentralized applications using DKG SDKs.
- Launching Paranets: Users can create specialized knowledge graphs.
- Knowledge Mining: Publish data to the DKG.
- Node Operations: Run nodes to support the network and earn TRAC.
- Community Engagement: Contribute to the codebase or participate in discussions on platforms like Discord and Reddit.
Synergy of Blockchain and Knowledge Graphs
- Blockchains: Function as decentralized trust networks, enabling verifiable transactions and identities.
- Knowledge Graphs: Serve as semantic networks that connect data entities, enhancing AI capabilities through structured and contextualized knowledge.
System Architecture
The DKG operates in multiple layers:
1. Network Layer: Peer-to-peer structure formed by DKG nodes.
2. Data Layer: Hosts the knowledge graph data across different graph databases.
3. Service Layer: Implements core services like authentication and data pipelines.
4. Consensus Layer: Connects to various blockchains for managing smart contracts.
5. Application Layer: Encompasses dApps and traditional applications using the DKG.
Graph Types
- Public Knowledge Graph: A shared, replicated graph for data discoverability.
- Private Graphs: Hosted separately by nodes, allowing for secure data exchange.
Protocol Actors
- Data Creator Nodes (DC): Publish datasets.
- Data Holder Nodes (DH): Host datasets and receive incentives.
- Data Viewers (DV): Query the DKG.
- Data Providers (DP): Supply data for publishing.
Data Integrity and Security
- Each dataset published includes:
- A cryptographic identity (DID) for the creator and provider.
- Structured graph linked data.
- Cryptographic fingerprints stored on the blockchain.
- Timestamping and lifespan tracking.
In essence, the #OriginTrailDKG is poised to revolutionize how knowledge is structured, shared, and verified across decentralized networks, particularly benefiting AI applications.
