1. A method for facilitating meta-analysis of data captured for intelligence purposes using a computer network and implemented as an unconstrained system, the method comprising the steps of: (a) establishing a distributed acquisition server architecture within the computer network responsive to a data-flow driven environment; (b) sampling a plurality of streams of unstructured data by said distributed acquisition server architecture; (c) converting said plurality of streams of unstructured data into a well described normalized form of binary data via a dedicated mining language tied to a current system ontology; (d) storing said converted binary data in a memory system tied to said current system ontology within said computer network, wherein said memory system defines a plurality of persistent storage containers required to contain said converted binary data; (e) directing said storing step with a memory management system which splits said converted binary data into an appropriate one of said plurality of persistent storage containers; (f) executing one or more control and/or data-flow based programs, called widgets, on said converted binary data stored in said plurality of persistent storage containers, wherein execution of said one or more widgets begins when a matching set of data objects or tokens from said converted binary data appear on an input data-flow pin of said one or more widgets; (g) producing a set of resultant data tokens on an output data-flow pin of said one or more widgets, wherein said set of resultant data tokens become part of said data-flow driven environment in said persistent storage containers or in a memory of a computer within the computer network; (h) querying a registered search capability of one or more said plurality of persistent storage containers producing a list of hits; (i) querying said list of hits with Boolean and other operators to specify logical combinations of said list of hits; (j) displaying and interacting with said plurality of streams of unstructured data, said list of hits, and said logical combinations of said list of hits through a user interface on a display device within the computer network; (k) forming collections of datums from said logical combinations of said list of hits through a memory collections system that forms and enables manipulation and exchange of said collections of datums both within a local computer as well as across the computer network; (l) delivering said collections of datums for meta-analysis to a user accessing the computer network through said user interface; and (m) based upon said meta-analysis by said user, revising said querying steps (h) and (i) repeating steps (j), (k) and (l).
1. A method for facilitating meta-analysis of data captured for intelligence purposes using a computer network and implemented as an unconstrained system, the method comprising the steps of: (a) establishing a distributed acquisition server architecture within the computer network responsive to a data-flow driven environment; (b) sampling a plurality of streams of unstructured data by said distributed acquisition server architecture; (c) converting said plurality of streams of unstructured data into a well described normalized form of binary data via a dedicated mining language tied to a current system ontology; (d) storing said converted binary data in a memory system tied to said current system ontology within said computer network, wherein said memory system defines a plurality of persistent storage containers required to contain said converted binary data; (e) directing said storing step with a memory management system which splits said converted binary data into an appropriate one of said plurality of persistent storage containers; (f) executing one or more control and/or data-flow based programs, called widgets, on said converted binary data stored in said plurality of persistent storage containers, wherein execution of said one or more widgets begins when a matching set of data objects or tokens from said converted binary data appear on an input data-flow pin of said one or more widgets; (g) producing a set of resultant data tokens on an output data-flow pin of said one or more widgets, wherein said set of resultant data tokens become part of said data-flow driven environment in said persistent storage containers or in a memory of a computer within the computer network; (h) querying a registered search capability of one or more said plurality of persistent storage containers producing a list of hits; (i) querying said list of hits with Boolean and other operators to specify logical combinations of said list of hits; (j) displaying and interacting with said plurality of streams of unstructured data, said list of hits, and said logical combinations of said list of hits through a user interface on a display device within the computer network; (k) forming collections of datums from said logical combinations of said list of hits through a memory collections system that forms and enables manipulation and exchange of said collections of datums both within a local computer as well as across the computer network; (l) delivering said collections of datums for meta-analysis to a user accessing the computer network through said user interface; and (m) based upon said meta-analysis by said user, revising said querying steps (h) and (i) repeating steps (j), (k) and (l). 5. The method according to claim 1 wherein said converting step (c) via said current system ontology further comprises the steps of: establishing an ontology description language, or ODL, wherein the ODL is derived by extensions to a standard computer programming base language as implemented using a types system; registering a plurality of data containing with a collections system via a plug-in registry; automatically generating and handling, with a database creation engine, one or more persistent storage tables necessary in the data containers that have been registered with the collections system, wherein the database creation engine uses specifications given in the ODL; and automatically generating, with a user interface creation engine using the ODL, a user interface that permits display, interaction with, and querying of the data residing in the persistent storage containers.