Relating complex data

Abstract

A data analysis and processing method includes forming an initial assembly of datasets comprising multiple entities, where each entity is a collection of variables and relationships that define how entities interact with each other, simulating an evolution of the initial assembly by performing multiple iterations in which a first iteration uses the initial assembly as a starting assembly, and querying, during the simulating, the evolution of the initial assembly, for datasets that meet an optimality criterion.

1 - 14 . (canceled) 
     
     
         15 . A data visualization method, comprising:
 forming a multi-level visual depiction of datasets and algorithmic relationships by instantiating as a colony of assemblies, each assembly being represented as a lifeform in the colony, that have a range in variations of their dataset and algorithmic conditions;   simulating an evolution of the colony of assemblies such that, during the evolution, the assemblies are allowed to undergo formation, reproduction, detachment and mutation;   comparing, during the evolution, individual assemblies in the colony against each other and with at least one contextual condition to find optimizations provided by the individual assemblies; and   updating the visual depiction to depict a progress of the evolution of the colony of assemblies.   
     
     
         16 . The method of  claim 15 , wherein each lifeform of the lifeforms is represented by a format that comprises a dataset, inputs that are used as functions that change behavior of the each lifeform and outputs that change a characteristic of the each lifeform. 
     
     
         17 . The method of  claim 15 , wherein the simulation of the evolution of the colony comprises multiple iterations in which the colony is evolved based on interaction among the datasets of the lifeforms that result in changes in values of at least some datasets. 
     
     
         18 . The method of  claim 16 , wherein the mutation of a particular assembly comprises random changes to a dataset or algorithmic relationships of the particular assembly. 
     
     
         19 . The method of  claim 16 , wherein the reproduction of a particular assembly comprises inheriting features from parent assemblies of the particular assembly. 
     
     
         20 . The method of  claim 15 , further comprising, culling, during the simulation, certain assemblies that fail to meet a target objective function, and eliminating culled assemblies from the visual depiction. 
     
     
         21 . The method of  claim 20 , wherein a different target objective function is used for at least some iterations of the simulation. 
     
     
         22 . The method of  claim 21 , wherein the target objective function includes an energy function or a uniqueness function. 
     
     
         23 . The method of  claim 15 , wherein the multi-level visual depiction is organized in a 3D space, wherein evolution of each assembly is represented by a size, a position and a velocity thereof, and wherein a relationship between a first assembly and a second assembly that is a neighbor of the first assembly is visually depicted by a rotational change to the first assembly caused by a rotational change to the second assembly. 
     
     
         24 . A computing system comprising one or more processors configured to implement a method, comprising:
 forming a multi-level visual depiction of datasets and algorithmic relationships by instantiating as a colony of assemblies, each assembly being represented as a lifeform in the colony, that have a range in variations of their dataset and algorithmic conditions;   simulating an evolution of the colony of assemblies such that, during the evolution, the assemblies are allowed to undergo formation, reproduction, detachment and mutation;   comparing, during the evolution, individual assemblies in the colony against each other and with at least one contextual condition to find optimizations provided by the individual assemblies; and   updating the visual depiction to depict a progress of the evolution of the colony of assemblies.   
     
     
         25 . The computing system of  claim 24 , wherein each lifeform of the lifeforms is represented by a format that comprises a dataset, inputs that are used as functions that change behavior of the each lifeform and outputs that change a characteristic of the each lifeform. 
     
     
         26 . The computing system of  claim 24 , wherein the simulation of the evolution of the colony comprises multiple iterations in which the colony is evolved based on interaction among the datasets of the lifeforms that result in changes in values of at least some datasets. 
     
     
         27 . The computing system of  claim 25 , wherein the mutation of a particular assembly comprises random changes to a dataset or algorithmic relationships of the particular assembly. 
     
     
         28 . The computing system of  claim 25 , wherein the reproduction of a particular assembly comprises inheriting features from parent assemblies of the particular assembly. 
     
     
         29 . The computing system of  claim 24 , wherein the one or more processors are further configured to perform culling, during the simulation, certain assemblies that fail to meet a target objective function, and eliminating culled assemblies from the visual depiction. 
     
     
         30 . The computing system of  claim 29 , wherein a different target objective function is used for at least some iterations of the simulation. 
     
     
         31 . The computing system of  claim 30 , wherein the target objective function includes an energy function or a uniqueness function. 
     
     
         32 . The computing system of  claim 24 , wherein the multi-level visual depiction is organized in a 3D space, wherein evolution of each assembly is represented by a size, a position and a velocity thereof, and wherein a relationship between a first assembly and a second assembly that is a neighbor of the first assembly is visually depicted by a rotational change to the first assembly caused by a rotational change to the second assembly. 
     
     
         33 . A computer readable medium having code stored thereon, the code, when executed by a processor, causing the processor to implement a method, comprising:
 forming a multi-level visual depiction of datasets and algorithmic relationships by instantiating as a colony of assemblies, each assembly being represented as a lifeform in the colony, that have a range in variations of their dataset and algorithmic conditions;   simulating an evolution of the colony of assemblies such that, during the evolution, the assemblies are allowed to undergo formation, reproduction, detachment and mutation;   comparing, during the evolution, individual assemblies in the colony against each other and with at least one contextual condition to find optimizations provided by the individual assemblies; and   updating the visual depiction to depict a progress of the evolution of the colony of assemblies.   
     
     
         34 . The computer readable medium of  claim 33 , wherein each lifeform of the lifeforms is represented by a format that comprises a dataset, inputs that are used as functions that change behavior of the each lifeform and outputs that change a characteristic of the each lifeform.