Ontology Builder for Knowledge Graphs

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Travis Cook
Project Owner

Ontology Builder for Knowledge Graphs

Funding Requested

$30,000 USD

Expert Review
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Community
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Overview

A framework and toolset for creating and contributing to crowdsourced ontologies towards the greater goal of contextualizing existing Knowledge Graphs and refining edge characteristics in graph datasets to develop richer semantic metadata and correlations to allow for more systematic approaches to context, prompt engineering and automated agent workflows. At a more abstracted layer, it can help provide an underpinning for symbolic constructions and representations of data, and extract more meaningful conceptual connections and abstract relationships (ie. via vector embeddings, etc.) to provide a foundational framework for developing more effective forms of intelligent reasoning.

Proposal Description

Our Team

Extensive experience and education in Computer and Data science, as well as Philosophy of Logic, and Epistemology academic research, and Design, as well as developer experience in AI model creation, LLMs, Machine Learning, Fine-tuning, Prompt Engineering, Data Science, and UI/UX design and research.

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Our specific solution to this problem

We will create a tool for users to save and add data from the web (URL [links, bookmarks] and/or scrape content from entire web pages via a simple browser extension mechanism and to add it to a collaborative dataset via a platform workspace which will utilize 3rd-party AI/LLM tools/APIs to semi-automatically categorize the content into semantic categories by suggesting 'tags' for the content which is chunked into discrete cconcetual elements across multi-dimensional domains. The user will guide the process through a form of crowd-sourced supervised learning to help train the AI to identify and categorize elements according to 'intuitive' contexts, organized hierarchically within directional structures (nested trees) which align with contexts that can inform meaningful prompt chains and workflows within constarined conceptual structures defined by structural ontologies built through the collaborative data-mapping process involving crowd-sourced users and supervised AI agents.

Project details

We will create a tool for users to save and add data from the web (URL [links, bookmarks] and/or scrape content from entire web pages via a simple browser extension mechanism and to add it to a collaborative dataset via a platform workspace which will utilize 3rd-party AI/LLM tools/APIs to semi-automatically categorize the content into semantic categories by suggesting 'tags' for the content which is chunked into discrete cconcetual elements across multi-dimensional domains. The user will guide the process through a form of crowd-sourced supervised learning to help train the AI to identify and categorize elements according to 'intuitive' contexts, organized hierarchically within directional structures (nested trees) which align with contexts that can inform meaningful prompt chains and workflows within constarined conceptual structures defined by structural ontologies built through the collaborative data-mapping process involving crowd-sourced users and supervised AI agents.

Open Source Licensing

MIT - Massachusetts Institute of Technology License

Proposal Video

Placeholder for Spotlight Day Pitch-presentations. Video's will be added by the DF team when available.

  • Total Milestones

    3

  • Total Budget

    $30,000 USD

  • Last Updated

    20 May 2024

Milestone 1 - Neo4j database for foundation knowledge graph

Description

Graph database and Cloud-based VM instance

Deliverables

Create Neo4j database on Cloud-based VM instance for initial containerized dev & testing environment using GraphQL interface. Development of extensible schema using basic foundational Ontology (that will develop over time). [Willing to look into options such as Ocean or ICP and Singularity.net (although I am not yet familiar with the possibilities there and will require further research. Other decentralized options such as Arweave Sia Graph etc. will be considered also. ]

Budget

$5,000 USD

Milestone 2 - AI & API tooling for Singularty.NET integration

Description

Setup 3rd party AI models API tools to connect and integrate with Singularity.net via Python SDK and gRPC provisioning.

Deliverables

Deploy AI services for Data ingesting to backend DB via Python SDK

Budget

$20,000 USD

Milestone 3 - Ran out of time to finish...

Description

refer to https://tmdcgroup.com for updates to proposal?? ;)

Deliverables

ditto--------------------------------------------------------------

Budget

$5,000 USD

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Reviews & Rating

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5 ratings
  • 0
    user-icon
    Emotublockchain
    Jun 8, 2024 | 8:44 PM

    Overall

    3

    • Feasibility 5
    • Viability 4
    • Desirabilty 2
    • Usefulness 3
    Outstanding Approach to Harnessing Data

    The project's approach to harnessing crowdsourced data categorization is outstanding, as it leverages the collective intelligence of users to refine AI models. This collaborative model not only improves the accuracy and relevance of the ontologies but also ensures that they evolve in line with user needs and real-world applications.

    The workability of the project hinges on the successful integration of AI/LLM tools with user-driven supervised learning. Given the current advancements in AI and machine learning, this aspect seems technically feasible. The viability of the project is strengthened by the growing need for more structured and intelligent data management systems across various industries. As more businesses and organizations recognize the value of Knowledge Graphs and ontologies, the marketability of this tool is substantial. 

     

     

    Focal Aeas

     

    Explore integration opportunities with existing Knowledge Graph platforms and data management systems. Collaboration with academic institutions and industry leaders can provide additional validation and expand the project's reach.

     

    While the project is comprehensive, the founders should also consider potential challenges in data standardization across different domains, managing the quality of crowdsourced contributions, and the long-term sustainability of maintaining and updating the ontologies. Additionally, exploring the potential for multilingual support could significantly broaden the tool's applicability and user base.

  • 0
    user-icon
    JeyGarg23
    Jun 3, 2024 | 7:18 PM

    Overall

    1

    • Feasibility 1
    • Viability 1
    • Desirabilty 5
    • Usefulness 5
    Is the category correct?

    Wait, is the Community Driven RFPs the correct category?

    The idea is good though

  • 0
    user-icon
    Tu Nguyen
    Jun 3, 2024 | 3:28 AM

    Overall

    3

    • Feasibility 3
    • Viability 3
    • Desirabilty 3
    • Usefulness 4
    Ontology Builder For Knowledge Graphs

    This proposal will create a tool for users to save and add data from the web and/or scrape content from entire web pages via a simple browser extension mechanism and to add it to a collaborative dataset via a platform workspace which will utilize 3rd-party AI/LLM tools/APIs to semi-automatically categorize the content into semantic categories by suggesting 'tags' for the content which is chunked into discrete synchronous elements across multi-dimensional domains.
    I see that this proposal focuses on sharing about their solution. They should be more clear about the problem they will solve.

  • 0
    user-icon
    CLEMENT
    Jun 1, 2024 | 10:44 AM

    Overall

    3

    • Feasibility 3
    • Viability 3
    • Desirabilty 4
    • Usefulness 3
    Great idea but incomplete details

    I believe the Ontology Builder for Knowledge Graphs project represents a significant advancement in the field of semantic metadata creation and knowledge representation. From a general perspective, it offers a framework and toolset for crowdsourcing ontologies, refining graph datasets, and developing richer contextual understanding within knowledge graphs.

    However, I am concerned about this proposal lacking complete details. The 3rd milestone would have been a valuable to express more specific details about this project's roadmap. However, I can see that it is missing on this proposal. This draws concerns surrounding this project's viability. 

  • 0
    user-icon
    Joseph Gastoni
    May 23, 2024 | 4:54 PM

    Overall

    3

    • Feasibility 3
    • Viability 2
    • Desirabilty 3
    • Usefulness 3
    outline a project for a framework and toolset

    This proposal outlines a project for a framework and toolset to create and contribute to crowdsourced ontologies for enriching knowledge graphs. Here's a breakdown of its strengths and weaknesses:

    Feasibility:

    • Moderate: The project leverages existing technologies (AI/LLMs, ontologies) but requires significant development effort for the user interface, data management, and integration with AI tools.
      • Strengths: The proposal builds upon established concepts and can be developed in stages.
      • Weaknesses: The proposal lacks details on the technical complexity of building and managing the platform, user interface, and data security.

    Viability:

    • Moderate: Success depends on attracting a large and active user base, effectively integrating with existing AI tools, and demonstrating clear value for knowledge graph users.
      • Strengths: The proposal addresses a need for richer semantic metadata in knowledge graphs and aligns with the growth of AI/LLMs.
      • Weaknesses: The proposal needs a clear strategy for user acquisition, engagement, and demonstrating value proposition compared to existing ontology development methods.

    Desirability:

    • High (for a specific audience): For researchers, developers, and businesses working with knowledge graphs, this could be highly desirable.
      • Strengths: The proposal caters to a specific need within the knowledge graph and AI development communities.
      • Weaknesses: The proposal needs to address the potential burden on users for contributing and the complexity for those unfamiliar with ontologies.

    Usefulness:

    • High Potential: The project has the potential to significantly improve the quality and richness of knowledge graphs, but hinges on successful development, user adoption, and integration with existing tools.
      • Strengths: The proposal offers a framework for a collaborative platform to develop and refine ontologies for knowledge graphs.
      • Weaknesses: The proposal lacks details on how the platform will ensure data quality and consistency within the crowdsourced environment.

    Overall, the proposal has a valuable idea, but focus on:

    • Technical Details: Provide more details on the development plan for the platform, user interface, data management, and integration with AI tools.
    • User Acquisition Strategy: Develop a clear plan for attracting and engaging users, potentially including gamification or incentives for contributions.
    • Data Quality and Consistency: Outline strategies for ensuring the quality and consistency of data contributed by users within the crowdsourced environment.
    • Value Proposition: Clearly demonstrate the benefits of using crowdsourced ontologies compared to traditional methods for knowledge graph development.

Summary

Overall Community

2.6

from 5 reviews
  • 5
    0
  • 4
    0
  • 3
    4
  • 2
    0
  • 1
    1

Feasibility

3

from 5 reviews

Viability

2.6

from 5 reviews

Desirabilty

3.4

from 5 reviews

Usefulness

3.6

from 5 reviews

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