Knowledge Graph Workflows

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Robert Haas
Project Owner

Knowledge Graph Workflows

Status

  • Overall Status

    ⏳ Contract Pending

  • Funding Transfered

    $0 USD

  • Max Funding Amount

    $25,000 USD

Funding Schedule

View Milestones
Milestone Release 1
$5,000 USD Pending TBD
Milestone Release 2
$10,000 USD Pending TBD
Milestone Release 3
$10,000 USD Pending TBD

Project AI Services

No Service Available

Overview

The goal of this project is to create useful demonstrations of how to bring recent scientific knowledge graphs of various formats and sizes to OpenCog Hyperon. This is achieved by extending an existing literature review and ETL package from the author in DFR3 by covering newer literature, adding several new KGs to the package and implementing further MeTTa encodings in the loading step to enable more efficient queries (e.g. via MORK and/or PLN). A downstream objective is to thereby support 1) ongoing development and testing of MeTTa scalability solutions such as MORK and 2) other knowledge graph projects in the SingularityNET ecosystem such as Rejuve's work on biomedical knowledge graphs.

RFP Guidelines

Develop interesting demos in MeTTa

Complete & Awarded
  • Type SingularityNET RFP
  • Total RFP Funding $100,000 USD
  • Proposals 21
  • Awarded Projects 4
author-img
SingularityNET
Aug. 12, 2024

Create educational and/or useful demos using SingularityNET's own MeTTa programming language. This RFP aims at bringing more community adoption of MeTTa and engagement within our ecosystem, and to demonstrate and expand the utility of MeTTa. Researchers must maintain demos for a minimum of one year.

Proposal Description

Company Name (if applicable)

Antecedens e.U.

Project details

Part 1: Maintained literature review

The previous project started with a detailed review of literature about biomedical knowledge graphs up until December 31, 2023. The results were captured in a repository in form of a PDF report, an interactive website and a curated list.

One goal of the current project is to maintain this material by covering newer literature published throughout 2024 to keep the knowledge cut-off up to date. A reason to do so is demonstrated interest from external researchers, reflected in 18 stars on GitHub and a few e-Mails to the author. Efforts to improve visibility could lead to increased interest in this work and by indirection to Deep Funding and SingularityNET.

Part 2: Extended Python package

The previous project culminated in a Python package for automatically extracting, transforming and loading five recent biomedical knowledge graphs of high quality into three different MeTTa formats as well as other target formats. The focus was on projects with direct relation to pharmacological applications that profit from graph representations, such as drug repurposing, target identification, disease-gene prioritization, or predicting negative drug-drug interactions. Positive feedback was received from the teams of MORK and Rejuve.

Two further goals of the current project are to extend this package by doubling the number of covered knowledge graphs from 5 to 10 and - upon concrete suggestions from the MeTTa or MORK teams - adding further MeTTa encodings in the unified loading step, e.g. for compatibility with a particular PLN implementation or to optimize MORK queries. The knowledge graphs could stem either from the field of biomedicine again or other domains such as computational neuroscience:

  • Recent, high-quality BMKGs can be identified from the maintained literature review.
  • A candidate for a neuroscientific KG could be data published by the Princeton Neuroscience Institute in project https://flywire.ai that provides the first whole-brain connectome of a complex organism and thus a view into the implementation of biological cognition. The scale of the connectome is smaller than the largest BMKG covered so far, therefore it can be loaded into MORK and would enable replication studies in OpenCog Hyperon and potentially even the discovery of novel patterns of cognition. One example mentioned in associated publications is: "Tracing from a subset of photoreceptors to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviours."
  • Yet another KG could come from introductory literature such as a tutorial-like paper published in 2021 in an open access journal, which throughout its text uses an exemplary KG to discuss different graph data models: "To keep the discussion accessible, we present concrete examples for a hypothetical knowledge graph relating to tourism in Chile (loosely inspired by, e.g., References [66, 79]". A small, educational KG could be loaded into all MeTTa implementations and could be used in an educational MeTTa tutorial on knowledge graphs and how to query, analyze or use them.

Open Source Licensing

Apache License

I'm using permissive open source licenses whenever it is possible. For the previous project I've applied Apache-2.0 license for the code repository and CC-BY-SA-4.0 license for the literature review repository. I am going to use the same for the work in this project, unless there are suggestions for better options w.r.t. free reusability without any risk of patent trolling or other undesired effects.

Links and references

  1. Previous project: https://deepfunding.ai/proposal/bringing-network-pharmacology-to-opencog-hyperon 
  2. Result 1 (Literature review, website, curated list): https://github.com/robert-haas/awesome-biomedical-knowledge-graphs
  3. Result 2 (Python package): https://github.com/robert-haas/kgw and its documentation https://robert-haas.github.io/kgw-docs 

Proposal Video

Not Avaliable Yet

Check back later during the Feedback & Selection period for the RFP that is proposal is applied to.

Group Expert Rating (Final)

Overall

5.0

  • Feasibility 4.7
  • Desirabilty 4.3
  • Usefulness 4.3

New reviews and ratings are disabled for Awarded Projects

Overall Community

4.7

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

Feasibility

4.7

from 3 reviews

Viability

4.3

from 3 reviews

Desirabilty

4.3

from 3 reviews

Usefulness

0

from 3 reviews

Sort by

3 ratings
  • Expert Review 1

    Overall

    5.0

    • Compliance with RFP requirements 5.0
    • Solution details and team expertise 5.0
    • Value for money 5.0
    Strong valuable proposal

    This proposal offers practical and ecosystem-relevant outcomes by expanding an established project. Valuable initiative for scaling AGI-aligned KG workflows.

  • Expert Review 2

    Overall

    4.0

    • Compliance with RFP requirements 4.0
    • Solution details and team expertise 3.0
    • Value for money 3.0

  • Expert Review 3

    Overall

    5.0

    • Compliance with RFP requirements 5.0
    • Solution details and team expertise 5.0
    • Value for money 5.0
    Updating Bio-Atomspace in this way seems high value for money and useful for mutual purposes

    the proposer is a known entity around the ecosystem and seems to have fairly solid understanding of related issues

  • Total Milestones

    3

  • Total Budget

    $25,000 USD

  • Last Updated

    3 Feb 2025

Milestone 1 - Maintenance of the literature review

Status
😐 Not Started
Description

Update the review of literature about biomedical knowledge graphs to cover recent developments in the field.

Deliverables

1. Updated report: https://github.com/robert-haas/awesome-biomedical-knowledge-graphs/blob/main/target/bmkg.pdf 2. Updated website: https://robert-haas.github.io/awesome-biomedical-knowledge-graphs

Budget

$5,000 USD

Success Criterion

The report and website cover recent literature. This is visible by new entries that are dated between the current knowledge cut-off (December 31, 2023) and the new one (December 31, 2024).

Link URL

Milestone 2 - Extension of the Python package

Status
😐 Not Started
Description

Extend the Python package (kgw) to allow the extraction transformation and loading of three new knowledge graphs.

Deliverables

1. Updated package: https://github.com/robert-haas/kgw

Budget

$10,000 USD

Success Criterion

There are three new Python modules corresponding to the three new KGs. They are visible either in the subpackage https://github.com/robert-haas/kgw/tree/main/kgw/biomedicine or a new subpackage named after a novel domain such as neuroscience.

Link URL

Milestone 3 - Extension of the Python package and documentation

Status
😐 Not Started
Description

Extend the Python package (kgw) to allow the extraction transformation and loading of two new knowledge graphs. Optionally enable further MeTTa encodings by adding new loading functions depending on whether there are concrete suggestions for how compatibility with PLN or MORK can be improved.

Deliverables

1. Extended package: https://github.com/robert-haas/kgw 2. Updated documentation: https://robert-haas.github.io/kgw-docs/

Budget

$10,000 USD

Success Criterion

- There are two new Python modules corresponding to the two new KGs. They are visible either in the subpackage https://github.com/robert-haas/kgw/tree/main/kgw/biomedicine or a new subpackage named after a novel domain such as neuroscience. - Optionally, the loading step contains new options for further MeTTa encodings, either adding to or replacing the current three options, which is reflected in the code at https://github.com/robert-haas/kgw/blob/main/kgw/_shared/load.py and its documentation. - The subpackage for each new KG is documented in the API reference at https://robert-haas.github.io/kgw-docs/autoapi/index.html - A new version of the package is published on PyPI (in addition to GitHub): https://pypi.org/project/kgw

Link URL

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Expert Ratings

Reviews & Ratings

Group Expert Rating (Final)

Overall

5.0

  • Feasibility 4.7
  • Desirabilty 4.3
  • Usefulness 4.3

New reviews and ratings are disabled for Awarded Projects

  • Expert Review 1

    Overall

    5.0

    • Compliance with RFP requirements 5.0
    • Solution details and team expertise 5.0
    • Value for money 5.0
    Strong valuable proposal

    This proposal offers practical and ecosystem-relevant outcomes by expanding an established project. Valuable initiative for scaling AGI-aligned KG workflows.

  • Expert Review 2

    Overall

    4.0

    • Compliance with RFP requirements 4.0
    • Solution details and team expertise 3.0
    • Value for money 3.0

  • Expert Review 3

    Overall

    5.0

    • Compliance with RFP requirements 5.0
    • Solution details and team expertise 5.0
    • Value for money 5.0
    Updating Bio-Atomspace in this way seems high value for money and useful for mutual purposes

    the proposer is a known entity around the ecosystem and seems to have fairly solid understanding of related issues

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