Abstract: A system and method for connecting one or more client applications with one or more knowledge representation servers and communicating there between includes an application programming interface (API) and a hypergraph transfer protocol (HGTP), for facilitating communication between the one or more client applications and one or more knowledge representation servers responsive to a client application request. The client application request includes an API call for a specific entity that is received by a first knowledge representation server. If the first knowledge representation server does not manage the specific entity, the first knowledge representation server forwards the specific entity call to a second knowledge representation server via the HGTP using a universal unique identifier (UUID) associated with the specific entity having encoded therein a network address for the second knowledge representation server.

Abstract: A knowledge model “overlay” for organizing and analyzing large, dynamic data volumes is implemented as a hypergraph that manifests as a result of a distributed theory-driven data source transformation process. This process maps exponentially growing data into an asymptotically limited information space. Within this space, real-world entities (e.g. people, computers, cities, Earth) and their complex interdependencies (e.g. social networks, connectivity, causal relationships) are represented as attributed hypergraph elements (i.e. both hypervertices and hyperedges). Attributes are represented as state vectors affixed to any hypergraph element. Transformation of source system data into this overlay structure is accomplished with minimal data movement and replication using a universal “pointer” like mechanism that is managed in a decentralized fashion by the respective transformation components.

Abstract: A system and method for connecting one or more client applications with one or more knowledge representation servers and communicating there between includes an application programming interface (API) and a hypergraph transfer protocol (HGTP), for facilitating communication between the one or more client applications and one or more knowledge representation servers responsive to a client application request. The client application request includes an API call for a specific entity that is received by a first knowledge representation server. If the first knowledge representation server does not manage the specific entity, the first knowledge representation server forwards the specific entity call to a second knowledge representation server via the HGTP using a universal unique identifier (UUID) associated with the specific entity having encoded therein a network address for the second knowledge representation server.

Abstract: A system and method for connecting one or more client applications with one or more knowledge representation servers and communicating there between includes an application programming interface (API) and a hypergraph transfer protocol (HGTP), for facilitating communication between the one or more client applications and one or more knowledge representation servers responsive to a client application request. The client application request includes an API call for a specific entity that is received by a first knowledge representation server. If the first knowledge representation server does not manage the specific entity, the first knowledge representation server forwards the specific entity call to a second knowledge representation server via the HGTP using a universal unique identifier (UUID) associated with the specific entity having encoded therein a network address for the second knowledge representation server.

Abstract: A knowledge model “overlay” for organizing and analyzing large, dynamic data volumes is implemented as a hypergraph that manifests as a result of a distributed theory-driven data source transformation process. This process maps exponentially growing data into an asymptotically limited information space. Within this space, real-world entities (e.g. people, computers, cities, Earth) and their complex interdependencies (e.g. social networks, connectivity, causal relationships) are represented as attributed hypergraph elements (i.e. both hypervertices and hyperedges). Attributes are represented as state vectors affixed to any hypergraph element. Transformation of source system data into this overlay structure is accomplished with minimal data movement and replication using a universal “pointer” like mechanism that is managed in a decentralized fashion by the respective transformation components.

Abstract: A knowledge model “overlay” for organizing and analyzing large, dynamic data volumes is implemented as a hypergraph that manifests as a result of a distributed theory-driven data source transformation process. This process maps exponentially growing data into an asymptotically limited information space. Within this space, real-world entities (e.g. people, computers, cities, Earth) and their complex interdependencies (e.g. social networks, connectivity, causal relationships) are represented as attributed hypergraph elements (i.e. both hypervertices and hyperedges). Attributes are represented as state vectors affixed to any hypergraph element. Transformation of source system data into this overlay structure is accomplished with minimal data movement and replication using a universal “pointer” like mechanism that is managed in a decentralized fashion by the respective transformation components.

Abstract: A knowledge model “overlay” for organizing and analyzing large, dynamic data volumes is implemented as a hypergraph that manifests as a result of a distributed theory-driven data source transformation process. This process maps exponentially growing data into an asymptotically limited information space. Within this space, real-world entities (e.g. people, computers, cities, Earth) and their complex interdependencies (e.g. social networks, connectivity, causal relationships) are represented as attributed hypergraph elements (i.e. both hypervertices and hyperedges). Attributes are represented as state vectors affixed to any hypergraph element. Transformation of source system data into this overlay structure is accomplished with minimal data movement and replication using a universal “pointer” like mechanism that is managed in a decentralized fashion by the respective transformation components.

Abstract: A knowledge model “overlay” for organizing and analyzing large, dynamic data volumes is implemented as a hypergraph that manifests as a result of a distributed theory-driven data source transformation process. This process maps exponentially growing data into an asymptotically limited information space. Within this space, real-world entities (e.g. people, computers, cities, Earth) and their complex interdependencies (e.g. social networks, connectivity, causal relationships) are represented as attributed hypergraph elements (i.e. both hypervertices and hyperedges). Attributes are represented as state vectors affixed to any hypergraph element. Transformation of source system data into this overlay structure is accomplished with minimal data movement and replication using a universal “pointer” like mechanism that is managed in a decentralized fashion by the respective transformation components.

Abstract: A system and method for connecting one or more client applications with one or more knowledge representation servers and communicating there between includes an application programming interface (API) and a hypergraph transfer protocol (HGTP), for facilitating communication between the one or more client applications and one or more knowledge representation servers responsive to a client application request. The client application request includes an API call for a specific entity that is received by a first knowledge representation server. If the first knowledge representation server does not manage the specific entity, the first knowledge representation server forwards the specific entity call to a second knowledge representation server via the HGTP using a universal unique identifier (UUID) associated with the specific entity having encoded therein a network address for the second knowledge representation server.

Abstract: A knowledge model “overlay” for organizing and analyzing large, dynamic data volumes is implemented as a hypergraph that manifests as a result of a distributed theory-driven data source transformation process. This process maps exponentially growing data into an asymptotically limited information space. Within this space, real-world entities (e.g. people, computers, cities, Earth) and their complex interdependencies (e.g. social networks, connectivity, causal relationships) are represented as attributed hypergraph elements (i.e. both hypervertices and hyperedges). Attributes are represented as state vectors affixed to any hypergraph element. Transformation of source system data into this overlay structure is accomplished with minimal data movement and replication using a universal “pointer” like mechanism that is managed in a decentralized fashion by the respective transformation components.