Abstract: A method for securely storing and commingling shared Self-Governing data from multiple Publishers with Zero-Trust data security is provided. It comprises providing a key-value store as a repository for Self-Governing key-value tuples, wherein a data tuple contains a data element cell value a Publishers assigned Self-Governing data security element value from a Zero-Trust data sharing schema, a unique identifier of the Publisher source of that data element value, and a datetime of the creation of the tuple. The method further comprises receiving and reading one or more generated Self-Governing key-value tuples, replicating the read, write and delete functions of the key-value store, generating a new table within the key-value store using a model of named vertical columns and horizontal rows matching the formats within a Zero Trust data sharing schema, and blocking direct user access to any Self-Governing data during and after deposit into the system.

Abstract: A system supporting operations on securely commingling Self-Governing data sets from a plurality of Publishers is provided.

Abstract: A system supporting operations on securely commingling Self-Governing data sets from a plurality of Publishers is provided.

Abstract: System of decentralized Zero-Trust services for creating, using and analyzing securely commingled Self-Governing data sets that prevents extraction by any party and unauthorized in contradiction to the Self-Governing need-to-know policies defined by each Publisher. Such an invention enables performance of combinatorial analytics, machine learning or artificial intelligence (AI) or other permitted data usage processes applied to commingled data without exposing the Self-Governing data in any manner contravening the embedded and enforced fine-grained security and governance settings which control how and by whom and in what context each data element can be used.

Abstract: System of decentralized Zero-Trust services for creating, using and analyzing securely commingled Self-Governing data sets that prevents extraction by any party and unauthorized in contradiction to the Self-Governing need-to-know policies defined by each Publisher. Such an invention enables performance of combinatorial analytics, machine learning or artificial intelligence (AI) or other permitted data usage processes applied to commingled data without exposing the Self-Governing data in any manner contravening the embedded and enforced fine-grained security and governance settings which control how and by whom and in what context each data element can be used.

Abstract: System and method of decentralized services to make federated raw data sets owned by a plurality of Publishers Self-Governing for secure sharing and commingling allowing the commingled data to be productively used or analyzed by Subscribers only in an indirect manner that prevents extraction by any party and unauthorized in contradiction to the Self-Governing need-to-know policies defined by each Publisher.

Abstract: System and method of decentralized services to make federated raw data sets owned by a plurality of Publishers Self-Governing for secure sharing and commingling allowing the commingled data to be productively used or analyzed by Subscribers only in an indirect manner that prevents extraction by any party and unauthorized in contradiction to the Self-Governing need-to-know policies defined by each Publisher.