Request for Data (RFD)
Request-for-Data (RFD) is Rankify's core mechanism for obtaining high-quality, verifiable datasets from expert communities. This process leverages the power of Meritocratic Autonomous Organizations (MAOs) to create trustless marketplaces for intellectual property.
What is an RFD?
An RFD is a smart contract-based request that allows organizations to specify their data needs and quality requirements while ensuring fair compensation for expert communities who fulfill these requests.
- Quality Assurance: Expert communities validate and curate data
- Transparency: All processes are recorded on-chain
- Fair Compensation: Contributors earn Liquid Access Tokens (LATs)
- Trustless: Smart contracts handle escrow and payments automatically
The RFD Process
The RFD process involves multiple stakeholders working together through smart contracts to create and deliver high-quality datasets.
RFD Creation
A buyer (such as an AI company) creates an RFD smart contract specifying data requirements, quality standards, deadlines, and payment terms. Funds are locked in escrow.
Community Response
Expert communities review the RFD and decide whether to participate. Interested experts begin working on data generation, curation, or validation.
Data Creation & LAT Earning
As experts contribute to the dataset, they earn Liquid Access Tokens (LATs) proportional to their contributions. LATs represent fractional ownership of the intellectual property.
Quality Verification
The Expert Guild (MAO) reviews and validates the completed dataset against the RFD requirements. They ensure quality standards are met before final delivery.
Delivery & Payment
Once verified, the dataset is delivered to the buyer, and payment is automatically released from escrow to the expert community based on their LAT holdings.
Getting Started with RFDs
🚧 Work in Progress
The RFD creation interface and detailed documentation are currently under development. For information about creating RFDs, joining expert communities, or participating in data generation, please reach out to us.
Contact us: https://peeramid.xyz/contact/
Use Cases
RFDs can be used for various types of data collection and curation:
- Training Datasets: High-quality labeled data for machine learning models
- Research Data: Curated datasets for academic or commercial research
- Content Creation: Text, images, or multimedia content for specific purposes
- Data Validation: Verification and quality assessment of existing datasets
- Specialized Knowledge: Expert annotations, classifications, or domain-specific insights