5. The method of claim 1 , further comprising: receiving, by one or more processors, a data stream of non-dimensional data objects; applying, by one or more processors, a dimension object to one of the non-dimensional data objects to define a conformed dimensional object, wherein the dimension object is a second facet that provides a measurement scale to the non-dimensional data objects; parsing, by one or more processors, the conformed dimensional object into a dimensional n-tuple, wherein the n-tuple comprises a pointer to said one of the non-dimensional data objects, a probability that said one of the non-dimensional data objects has been associated with a correct dimensional label, a probability that said one of the non-dimensional data objects is uncorrupted, and a weighting factor of importance of the conformed dimensional object; transmitting, by one or more processors, multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; further populating, by one or more processors, each of the multiple context-based conformed dimensional data gravity well frameworks with the multiple parsed conformed dimensional objects to further define the multiple context-based conformed dimensional data gravity wells according to a virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said dimension object in said particular context-based conformed dimensional data gravity well; and further dynamically adjusting, by one or more processors, a displayed appearance of the particular context-based conformed dimensional data gravity well according to the virtual mass of a parsed conformed dimensional object.
5. The method of claim 1 , further comprising: receiving, by one or more processors, a data stream of non-dimensional data objects; applying, by one or more processors, a dimension object to one of the non-dimensional data objects to define a conformed dimensional object, wherein the dimension object is a second facet that provides a measurement scale to the non-dimensional data objects; parsing, by one or more processors, the conformed dimensional object into a dimensional n-tuple, wherein the n-tuple comprises a pointer to said one of the non-dimensional data objects, a probability that said one of the non-dimensional data objects has been associated with a correct dimensional label, a probability that said one of the non-dimensional data objects is uncorrupted, and a weighting factor of importance of the conformed dimensional object; transmitting, by one or more processors, multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; further populating, by one or more processors, each of the multiple context-based conformed dimensional data gravity well frameworks with the multiple parsed conformed dimensional objects to further define the multiple context-based conformed dimensional data gravity wells according to a virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said dimension object in said particular context-based conformed dimensional data gravity well; and further dynamically adjusting, by one or more processors, a displayed appearance of the particular context-based conformed dimensional data gravity well according to the virtual mass of a parsed conformed dimensional object. 10. The method of claim 5 , further comprising: determining, by one or more processors, that said one of the non-dimensional data objects is uncorrupted by determining that said one of the non-dimensional data objects is not a fragment of an original data object.