Agentic Orchestration of EDC Data Space Retrieval and Natural Language Driven Data Processing
We present a multi-agent architecture that automates this process using natural language requests.
ProofPaper ↗
Key points
- Participating in a data space still requires the Dataspace Protocol (DSP) negotiation flow to be hand-coded against each provider's access policy.
- Built on LangGraph over an Eclipse Dataspace Components (EDC), the design separates concerns into cooperating agents.
- The data extraction agent's role is to expose the DSP protocol's three composable tools (catalog discovery, contract negotiation and download).
- Furthermore, there are downstream Machine Learning (ML) and Visualization agents, as well as a final Verification agent, which confirms that the request was actually fulfilled and rechecks the intended operation against the contract's usage policy.
Sources (1)
- [1]Agentic Orchestration of EDC Data Space Retrieval and Natural Language Driven Data ProcessingarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 03:10 PM
We present a multi-agent architecture that automates this process using natural language requests.
Participating in a data space still requires the Dataspace Protocol (DSP) negotiation flow to be hand-coded against each provider's access policy.
Extractive summary: sentences quoted from the sources.
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