“Knowledge graphs could be envisaged as a network of all kind things which are relevant to a specific domain or an organization. They are not limited to abstract concepts and relations but can also contain instances of things like documents and datasets.”
- The Semantic Company
(fig.8: Linked Data is how we can automate serendipitous discovery and contextual search)
(Important note: data links can be anonymized or even hidden behind Zero-Knowledge Proofs)
We will use a variety of different graph technologies including a recent innovation in knowledge aware neural networks from researchers at Cornell University, adding considerable depth to our Identity Management framework and the Fair World Graph.
Fair World Graph is designed to account for the relational heterogeneity in knowledge graphs in ways conducive to and co-evolving with diversity, making for curation and co-creation of knowledge and value. We are building further on knowledge aware neural networks, using a combination of trainable and personalized linked data, relations, and systems intelligence scoring functions. These functions enable value flow accounting, dynamic tokenization, and token economics. This allows the Fair World Graph system of graphs to transform knowledge graphs into user-specific knowledge and value augmenting, weighted graphs, reflecting both the semantic information as well as user’s personalized interests.
We aim to deliver the most powerful contextual decision support system at a fraction of the cost of current systems by distributing the operating cost across a massive network of individuals, groups, organizations, enterprises, and services.