LogoLogo
WebsitePredictoorData ChallengesData FarmingOcean.pyOcean.js
  • đź‘‹Ocean docs
  • 🌊Discover Ocean
    • Why Ocean?
    • What is Ocean?
    • What can you do with Ocean?
    • OCEAN: The Ocean token
    • Networks
    • Network Bridges
    • FAQ
    • Glossary
  • 📚User Guides
    • Basic concepts
    • Using Wallets
      • Set Up MetaMask
    • Host Assets
      • Uploader
      • Arweave
      • AWS
      • Azure Cloud
      • Google Storage
      • Github
    • Liquidity Pools [deprecated]
  • đź’»Developers
    • Architecture Overview
    • Ocean Nodes
      • Node Architecture
    • Contracts
      • Data NFTs
      • Datatokens
      • Data NFTs and Datatokens
      • Datatoken Templates
      • Roles
      • Pricing Schemas
      • Fees
    • Publish Flow Overview
    • Revenue
    • Fractional Ownership
    • Community Monetization
    • Metadata
    • Identifiers (DIDs)
    • New DDO Specification
    • Obsolete DDO Specification
    • Storage Specifications
    • Fine-Grained Permissions
    • Retrieve datatoken/data NFT addresses & Chain ID
    • Get API Keys for Blockchain Access
    • Barge
      • Local Setup
    • Ocean.js
      • Configuration
      • Creating a data NFT
      • Publish
      • Mint Datatokens
      • Update Metadata
      • Asset Visibility
      • Consume Asset
      • Run C2D Jobs
    • Ocean CLI
      • Install
      • Publish
      • Edit
      • Consume
      • Run C2D Jobs
    • DDO.js
      • Instantiate a DDO
      • DDO Fields interactions
      • Validate
      • Edit DDO Fields
    • Compute to data
    • Compute to data
    • Uploader
      • Uploader.js
      • Uploader UI
      • Uploader UI to Market
    • VSCode Extension
    • Old Infrastructure
      • Aquarius
        • Asset Requests
        • Chain Requests
        • Other Requests
      • Provider
        • General Endpoints
        • Encryption / Decryption
        • Compute Endpoints
        • Authentication Endpoints
      • Subgraph
        • Get data NFTs
        • Get data NFT information
        • Get datatokens
        • Get datatoken information
        • Get datatoken buyers
        • Get fixed-rate exchanges
        • Get veOCEAN stats
    • Developer FAQ
  • 📊Data Scientists
    • Ocean.py
      • Install
      • Local Setup
      • Remote Setup
      • Publish Flow
      • Consume Flow
      • Compute Flow
      • Ocean Instance Tech Details
      • Ocean Assets Tech Details
      • Ocean Compute Tech Details
      • Datatoken Interface Tech Details
    • Join a Data Challenge
    • Sponsor a Data Challenge
    • Data Value-Creation Loop
    • What data is valuable?
  • đź‘€Predictoor
  • đź’°Data Farming
    • Predictoor DF
      • Guide to Predictoor DF
    • FAQ
  • 🔨Infrastructure
    • Set Up a Server
    • Deploy Aquarius
    • Deploy Provider
    • Deploy Ocean Subgraph
    • Deploy C2D
    • For C2D, Set Up Private Docker Registry
  • 🤝Contribute
    • Collaborators
    • Contributor Code of Conduct
    • Legal Requirements
Powered by GitBook
LogoLogo

Ocean Protocol

  • Website
  • Blog
  • Data Challenges

Community

  • Twitter
  • Discord
  • Telegram
  • Instagram

Resources

  • Whitepaper
  • GitHub
  • Docs

Copyright 2024 Ocean Protocol Foundation Ltd.

On this page
  • Motivation
  • The Data Value-Creation Loop
  • The Data Value Supply Chain
  • Which Vertical? How To Compare Opportunities
  • Project Criteria
  • Summary

Was this helpful?

Edit on GitHub
Export as PDF
  1. Data Scientists

Data Value-Creation Loop

Thrive in the open data economy by closing the loop towards speed and value

Last updated 11 months ago

Was this helpful?

Motivation

The core infrastructure is in place for an open data economy. Dozens of teams are building on it. But it’s not 100% obvious for teams how to make $.

We ask:

How do people sustain and thrive in the emerging open data economy?

Our answer is simple: ensure that they can make money!

However, this isn’t enough. We need to dive deeper.

The Data Value-Creation Loop

The next question is:

How do people make money in the open data economy?

Our answer is: create value from data, make money from that value, and loop back and reinvest this value creation into further growth.

We call this the Data Value-Creation Loop. The figure above illustrates.

Let’s go through the steps of the loop.

  • At the top, the user gets data by buying it or spending $ to create it.

  • Then, they build an AI model from the data.

  • Then they make predictions. E.g. “ETH will rise in next 5 minutes”

  • Then, they choose actions. E.g. “buy ETH”.

  • In executing these actions, they data scientist (or org) will make $ on average.

  • The $ earned is put back into buying more data, and other activities. And the loop repeats.

In this loop, dapp builders can help their users make money; data scientists can earn directly; and crypto enthusiasts can catalyze the first two if incentivized properly (e.g. to curate valuable data).

The Data Value Supply Chain

If we unroll the loop, we get a data value supply chain. In most supply chains, the most value creation is at the last step, right before the action is taken. Would you rather a farmer in Costa Rica selling a sack of coffee beans for $5, or Starbucks selling 5 beans’ worth of coffee for $5?

Therefore, for data value supply chains, the most value creation in the prediction step.

To the question “How do people make money in the open data economy?”, the “create value from data!” almost seem like a truism. Don’t fool yourself. It’s highly useful in practice: focus only on activities that fully go through the data value-creation loop.

However, this is still too open-ended. We need to dive deeper.

Which Vertical? How To Compare Opportunities

There are perhaps dozens of verticals or hundreds of possible opportunities of creating and closing data value-creation loops. How to select which? We’ve found that two measuring sticks help the most.

Key criteria:

  1. How quickly one can go through the data value-creation loop?

  2. What’s the $ size of the opportunity

For (2), it’s not just “what’s the size of the market”, it’s also “can the product make an impact in the market and capture enough value to be meaningful”.

We analyzed dozens of possible verticals with according to these criteria. For any given data application, the loop should be fast with serious $ opportunity.

Here are some examples.

  • Small $, slow. Traditional music is small $ and slow, because incumbents like Universal dominate by controlling the back catalogue.

  • Large $, slow. Medicine is large $ but slow, due to the approval process. Small $, fast. Decentralized music is fast but small $ (for now! Fingers crossed).

We want: large $, fast. Here are the standouts.

  • Decentralized Finance (DeFi) is a great fit. One can loop at the speed of blocks (or faster), and trade volumes have serious $.

  • LLMs and modern AI is close: one can loop quickly, and with the right application make $. The challenge is: what’s the right application?

Project Criteria

We encourage you - as a builder - to choose projects that close the data value-creation loops. Especially loops with maximum $ and speed.

We follow our advice for internal projects too. Predictoor, Data Farming, and DeFi-oriented data challenges are standout examples.

Summary

To sustain and thrive in the open data economy: make money!

Do this by closing the data value-creation loop, in a vertical / opportunity where you can loop quickly and the $ opportunity is large.

📊