Ecosphere
  • Introduction
  • Elevator Pitch
  • Pitch Deck
  • Lean Model Canvas
  • OVERVIEW
    • Mission
    • Problem Statement
    • Ecosphere Prime Solution
    • Benefits
    • Value Proposition
    • Use Cases By Industry
    • Achieving Net Zero
    • Technology Platform
    • "Waze For Weather"
    • Strategic Roadmap
  • Technology
    • Climate Intelligence Network
    • Climate Nodes
      • Prototype
      • Device Mockup
      • Device Setup
      • Node Location Planning
      • Node Explorer
    • Smart Nodes On Hedera
      • Web3
      • Smart Nodes Vs Smart Contracts
    • DIDs and Verifiable Credentials
    • Peer-to Peer Data Sharing
      • How We Use Hedera
      • Hedera Topics
      • Data Tokenization
      • Data Sharing
    • Decentralized Identity
    • Micro Royalties
    • Fractional Ownership
    • Integration
      • Climate Data Workbench
      • API
    • AI Forecasting
  • Functional Flows
    • Registering A New User
    • Registering A New Node
    • Data Collection From Nodes
    • Data Tokenization
    • Data Sharing
    • AI and DLT
    • Marketplace
    • Fractional Ownership
  • Community Product
    • Product Community Fit
    • Product Vision
    • Minimum Viable Product App
    • Wireframe
      • Onboarding
      • Walkthrough Tutorials
      • Wallet Creation
      • Location List
      • Weather Information
      • Location Options and Support
      • Timelapses
      • Animations
      • Weather Station Setup
      • Search and Explore
      • Settings
      • Sharing and Notifications
    • Style Guide
    • Visual Design Elements
    • Usernames Feature
  • Commercial Product
    • Sector Focus
    • Product Market Fit
    • Comprehensive Reporting and Dashboards
    • Climate Data Oracle
    • Go-To-Market
    • Competition
  • Tokenomics
    • Revenue Drivers
    • $PRIME Token
    • Value Capture Mechanism
    • Reward Structure
    • Locale Coverage
    • Nodes For Public Good
  • Community
    • Whitepaper
    • Public Good
    • Joining Ecosphere
    • Governance
    • Awareness
    • Disaster Readiness
    • Early Warning System
    • Socials
  • Project Developer
    • About
    • Team
    • Funding
    • Testnet Accounts
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  1. Technology
  2. Peer-to Peer Data Sharing

Data Sharing

Data Utilization Flow

  1. Requesting Data

    • Objective: Access validated data tokens for training or inference in AI models (or for 3rd party systems.)

    • Process:

      • AI developers or users identify the relevant tokens representing the data they wish to use.

      • They initiate a request to access the data associated with these tokens.

  2. Verifying Token Ownership

    • Service Used: Hedera Token Service

    • Inputs Required:

      • Token ID(s) of the data assets

      • User's Hedera account ID

    • On-chain Recording:

      • Check that the requesting account owns or has rights to the token associated with the data.

      • If ownership is verified, proceed to grant access.

  3. Data Retrieval

    • Objective: Access the actual data files linked to the tokens.

    • Process:

      • Once access is granted, the AI model retrieves the data files from the Hedera File Service using the stored file hashes.

      • Access permissions and licensing terms are checked through smart contracts to ensure compliance.

  4. Utilizing Data in AI Models

    • Objective: Use the retrieved data for training or inference in AI models.

    • Process:

      • Data is processed and fed into the AI model.

      • The model may produce outputs used for decision-making or further analysis.

  5. Logging Data Usage

    • Service Used: Hedera Consensus Service

    • Inputs Required:

      • Token ID(s) used

      • Model parameters

      • Timestamp of usage

    • On-chain Recording:

      • Each instance of data usage is logged on the Hedera ledger, capturing which tokens were utilized, model parameters, and time of operation.

      • This log serves as an audit trail for accountability and transparency.

  6. Performance Monitoring and Feedback

    • Objective: Gather insights on the effectiveness of the data used.

    • Process:

      • Collect performance metrics from the AI model (e.g., accuracy, efficiency).

      • Provide feedback regarding data relevance and quality.

    • On-chain Recording:

      • Record performance metrics and feedback on the Hedera ledger for continuous improvement and data source evaluation.

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Last updated 6 months ago