Logosphere

Brings together all the above described concepts into a cohesive vision of a Web 3 metadata sidechain

Now that we explored quite a few concepts in the previous chapters, let’s bring them together into a cohesive vision of the Web3 metadata sidechain and in the spirit of the domain driven design, capture ubiquitous language of this system, and also let’s give it a name, so we can refer to it later in our discussions. The name of it from now on will be logosphere.

Meaning of the word “logosphere”

Logosphere is a term coined by a Russian philosopher Mikhail Bakhtin and means an adaptation of the concepts biosphere and noosphere: logosphere is derived from the interpretation of words' meanings, conceptualized through an abstract sphere.

Logosphere is based on two words (logos + sphere), where logos (λόγος) is a Greek word meaning “word”, “reason” or “plan”. It appears in the first passage of the New Testament:

“In the beginning was logos” - John (1:1)

But let’s not get too geeky about and just consider it as a suitable name for a Web3 protocol of interoperable metadata represented as a semantic knowledge graph.

Logosphere Framework

• Logosphere provides framework for building interoperable decentralized applications (dApps), that will support use cases of asset tokenization in a particular business domain. The assets will be tokenized as NFTs in L1 and have dynamic metadata properties defined in L2, which will be queryable and interoperable via global interconnected knowledge graph of metadata potentially spanning multiple L1 ecosystems.

• Logosphere conforms to Data Mesh Architecture concepts and consists of the following components:

  • Domain-agnostic framework that takes domain model as an input and produces domain-specific generated code with following functionality:

    • CRUD (Create, Read, Update, Delete) operations against variety of data persistence layers, operational and analytical

    • Persistence of metadata into semantic knowledge graph

    • Instrumentation for creating & signing transactions into L1 with simultaneous linking of metadata in L2 through hashes

    • Generated GraphQL API with commonly CRUD queries and mutations

    • Generated library of assets, such as entities, value objects, data transfer objects, mappers & repositories that conform to established patterns and ready to be used in custom business logic of the dApp

  • Extensions / plugins for specific use cases and languages such as generating assets for gaming engines (Unreal Engine & Unity in C++ and C#), smart contract libraries (Cardano Plutarch) that would allow to use metadata stored in the knowledge graph directly from the supported codebase.

  • Verifiability of metadata provenance

  • Deployability of L2 node with a set of microservices, able to interoperate with microservices published by another Logosphere dApps.

  • Focus on quality of data persisted in the knowledge graph which should be distilled from operational data according to the rules defined by the domain team.

Logosphere Conceptual Model

• Business Analyst interviews Domain Expert

  • captures Ubiquitous Language

  • creates Domain Model

• If Domain Model is complex, Business Analyst divides it into Bounded Contexts (sub-domains)

• Ontologist uses Domain Model and creates an Ontology

  • consults with existing ontologies

  • extends ontological model

• Backend Developer uses Domain Model and Bounded Contexts to generate one or more Codegen Modules using Logosphere SDK

  • For each Codegen Module creates Code-First Model

  • Generates Federated GraphQL API and the following assets of Domain Driven Design methodology (see Appendix B)

    • Data Transfer Objects (DTOs)

    • Entities

    • Repositories

    • Events

    • Unit Tests

    • End-to-end (e2e) Tests

• Logosphere SDK provides domain-agnostic templates and code generators, as well as libraries for connecting to centralized and decentralized infrastructure

• Backend Developer writes code for custom Business Logic Module utilizing generated by Logosphere SDK assets

  • Extends GraphQL API with custom queries and mutations

  • For each module builds docker image

• DevOps Engineer publishes docker image as a microservice in L2 node hosted on Kubernetes

  • Maintains L1 node running on the same k8s infrastructure

• Frontend Developer uses backend exposed as a GraphQL API and builds application frontend

• 3rd-party application connects to the Knowledge Graph using interoperability standards defined in W3C semantic web protocols: SPARQL language, ontologies etc and is able to retrieve metadata defined by any project that conforms to the same set of standards

• Researcher utilizes SPARQL to query Knowledge Graph DB to look for insights in areas of their interest

• Game Developer uses Logosphere Plugins for Unreal Engine and Unity to generate in-game assets and have them minted and transacted on L1 with metadata persisted in L2

• Smart Contracts Developer is using Logosphere SDK to generate assets that can query metadata, stored in knowledge graph to provide data for the the smart contracts logic.

• Knowledge Graph DB guarantees metadata consistency, verifiability, provenance & security. For Logosphere we’ll be using Fluree DB

Logosphere & Data Mesh Architecture

Logosphere conforms to the Data Mesh Architecture (see Appendix D) with an emphasis on building a knowledge graph node deployed as a microservice, that would be created and maintained by a domain team and deployed to a decentralized network. The governance and SDK development initially will be performed by Ikigai Technologies, but eventually can move to decentralized governance under Logosphere DAO.