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Python library for interacting with the OriginTrail Decentralized Knowledge Graph

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dkg.py

Python SDK for interacting with the OriginTrail Decentralized Knowledge Graph
OriginTrail Docs · View Demo · Report Bug · Request Feature

Table of Contents
  1. 📚 About The Project
  2. 🚀 Getting Started
  3. 📄 License
  4. 🤝 Contributing
  5. ❤️ Contributors
  6. 🌟 Acknowledgements
  7. 📰 Social Media


📚 About The Project

What is the Decentralized Knowledge Graph?


Knowledge Asset

OriginTrail Decentralized Knowledge Graph (DKG), hosted on the OriginTrail Decentralized Network (ODN) as trusted knowledge infrastructure, is shared global Knowledge Graph of Knowledge Assets. Running on the basis of the permissionless multi-chain OriginTrail protocol, it combines blockchains and knowledge graph technology to enable trusted AI applications based on key W3C standards.

The OriginTrail DKG Architecture


The OriginTrail tech stack is a three layer structure, consisting of the multi-chain consensus layer (OriginTrail layer 1, running on multiple blockchains), the Decentralized Knowledge Graph layer (OriginTrail Layer 2, hosted on the ODN) and Trusted Knowledge applications in the application layer.

DKG Architecture

Further, the architecture differentiates between the public, replicated knowledge graph shared by all network nodes according to the protocol, and private Knowledge graphs hosted separately by each of the OriginTrail nodes.

Anyone can run an OriginTrail node and become part of the ODN, contributing to the network capacity and hosting the OriginTrail DKG. The OriginTrail node is the ultimate data service for data and knowledge intensive Web3 applications and is used as the key backbone for trusted AI applications (see https://chatdkg.ai)

What is a Knowledge Asset?


Knowledge Asset

Knowledge Asset is the new, AI‑ready resource for the Internet

Knowledge Assets are verifiable containers of structured knowledge that live on the OriginTrail DKG and provide:

  • Discoverability - UAL is the new URL. Uniform Asset Locators (UALs, based on the W3C Decentralized Identifiers) are a new Web3 knowledge identifier (extensions of the Uniform Resource Locators - URLs) which identify a specific piece of knowledge and make it easy to find and connect with other Knowledge Assets.
  • Ownership - NFTs enable ownership. Each Knowledge Asset contains an NFT token that enables ownership, knowledge asset administration and market mechanisms.
  • Verifiability - On-chain information origin and verifiable trail. The blockchain tech increases trust, security, transparency, and the traceability of information.

By their nature, Knowledge Assets are semantic resources (following the W3C Semantic Web set of standards), and through their symbolic representations inherently AI ready. See more at https://chatdkg.ai

Discover Knowledge Assets with the DKG Explorer:

Knowledge Assets Graph 1
Supply Chains
Knowledge Assets Graph 2
Construction
Knowledge Assets Graph 3
Life sciences and healthcare
Knowledge Assets Graph 3
Metaverse

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🚀 Getting Started


Prerequisites

  • python >=3.10
  • poetry >=1.5.1

In order to use in the local environment, make sure to run the local DKG network.



Installation

Create virtual environment (you can choose any existing folder this command will create configurations and virtual env for python):

python3 -m venv /path/to/folder

Inside of previously generated folder you will find activate script in bin folder and run it:

source /path/to/folder/bin/activate

Install dependencies:

poetry install

Now you can run a demo example file (you need to have the local DKG network running):

python3 examples/demo.py

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📄 License

Distributed under the Apache-2.0 License. See LICENSE file for more information.


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🤝 Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

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❤️ Thanks to all Contributors!


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🌟 Acknowledgements


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📰 Social Media



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