Verified Human Knowledge Graphs

Verified Human Knowledge Graphs

We leverage the Verified Credentials JSON-LD Schema

The result of the Using the LQS to create Ontologies and Course Sequences, will be a unique Linked Talent Data File, which can be adopted through a verified credential, as well as be displayed on the course page, before it leaves the learning platform. 

We’ve designed 4 primary views a learner can observe their learning, those being: 

  • Neural view
  • Tree view
  • Aggregate view
  • Journey View

Verified Credential Standards & Networks

Velocity Network, Open Badges, and Credential Engine all are designed to enable the transmission and verification of credentials.  

(Check out the podcast about Velocity Network’s “Internet of Careers”)

Each of the above credentialing networks has a schema of associated data types, including JSON-LDs, which we use to transmit and populate associated linked data files with the verified credentials. 



Once the data is distributed to the individuals’ MyPythia App, the graph database in their human distributed Solid Pod will power a similar “master talent tree.”



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Self-Organizing Ontologies

We provide keywords families with clear meaning through Self-Organizing Ontologies

Concept Sequencing

We map knowledge and skills observed in courses through Concept Sequencing, creating Linked Talent Data

Verified Human Knowledge Maps

We distribute verified talent maps to individuals using Verified Credentials & blockchain networks.

Self-Soverign Verified Talent Data

We leverage human distributed Solid Pods to give the user ownership and control to combine and share their data, creating a Human Distributed Talent Ecosystem