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Publication numberUS20020156792 A1
Publication typeApplication
Application numberUS 10/010,727
Publication dateOct 24, 2002
Filing dateDec 6, 2001
Priority dateDec 6, 2000
Also published asUS6988109, US7702639, US20020156756, US20020198858, US20040003132, US20050289166
Publication number010727, 10010727, US 2002/0156792 A1, US 2002/156792 A1, US 20020156792 A1, US 20020156792A1, US 2002156792 A1, US 2002156792A1, US-A1-20020156792, US-A1-2002156792, US2002/0156792A1, US2002/156792A1, US20020156792 A1, US20020156792A1, US2002156792 A1, US2002156792A1
InventorsErich Gombocz, Robert Stanley
Original AssigneeBiosentients, Inc.
Export CitationBiBTeX, EndNote, RefMan
External Links: USPTO, USPTO Assignment, Espacenet
Intelligent object handling device and method for intelligent object data in heterogeneous data environments with high data density and dynamic application needs
US 20020156792 A1
Abstract
System, method, computer program and computer program product for generation of Intelligent Object data; unified presentation of dynamically customizable functional menus and interfaces such as for user definition, administration and security protocols; secured user interaction, access and presentation based on imported and/or defined user definition, administration and security protocols; data object standardization and normalization; definition of user interaction and computing environment protocols for data object translation, standardization, access and routing; definition of data type access, translation, presentation and routing protocols for functional data and applications integration; definition of application and/or application components and interface access, translation, presentation and routing protocols for functional data and applications integration; provision of interactive, unified, functionality for data acquisition, management, viewing and analysis. Application of such methods and techniques whether implemented in computer program software or otherwise to heterogeneous data environments with high data density and dynamic application needs
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Claims(64)
We claim:
1. An applications handling framework is provided to enable functionally integrated user interactivity, comprising structures and methods for one or more of
a. bi-directional information interchange with components and access interfaces comprising such as a data object with a comprised status management component agent; an object pool database structure with a comprised result aggregation engine; an object normalization engine; an object state engine; an object translation engine; and application translation interface, a master query interface; and a report generation interface;
b. utilizing unique data structures as core accessing; routing; and processing elements for
i. unified analysis of homogeneous and/or heterogeneous data content, contained within homogeneous and/or heterogeneous data formats, types and structures;
ii. by homogeneous and/or heterogeneous analytical applications, modules, and plug-ins;
iii. in homogeneous and/or heterogeneous network computing environments; to enable
c. provision of user interactivity utilizing said Intelligent Object data, Intelligent Object Handler, and Intelligent Object Pool applications within a unified, globally accessible graphical user environment, via an interactive unified presentation layer (UPL) graphical user interface.
2. An applications handling framework as in claim 1, wherein said methods for one or more of utilization, accessing, routing and processing of data structures further comprise
a. definition of said data object and data content according to methods comprising data matrix structure definition; application requirements definition; data resource definition; and
b. preparation of said data object and data content according to methods for one or more of data content and activity synchronization; standardization; translation; validation; ranking; and automated and/or interactive data organization;
c. nested vector table translation of data content presentation via extraction of required information, generation and provision of look up tables for applications integration; and
d. non-destructive cache-based “overlay” analytical processing of data content;
e. analysis and presentation of said data object and data content according to methods required for analysis by potentially heterogeneous applications; to enable
f. unified analysis of homogeneous and/or heterogeneous data by heterogeneous analytical applications in heterogeneous network environments.
3. An applications handling framework as in claim 1, wherein said methods for one or more of utilization, accessing, routing and processing of data structures further comprise
a. applications environment detection, extraction and definition for accessing, unified viewing, processing and routing; and
b. data content detection, extraction and definition for accessing, unified viewing, processing and routing.
4. An applications handling framework as in claim 1, wherein said methods for utilization, accessing, routing and processing of functionally integrated data structures further comprise one or more of
a. direction of vectorized data content accessing, linking and routing between data objects for direct parallel information interchange;
b. direction of meta-data accessing, linking and routing between data objects for direct parallel information interchange;
c. direction of vectorized data content accessing, linking and routing between data objects and applications for direct parallel information interchange;
d. direction of meta-data accessing, linking and routing between data objects and applications; for direct parallel information interchange; and
e. comparison, ranking and organization of said data according to Boolean analysis, structural matching and/or other statistical analyses of said information interchanged.
5. An applications handling framework as in claim 1, wherein said methods for user interaction further comprise one or more of
a. direct vectorized accessing to all relevant data content and meta-data properties of said potentially heterogeneous and distributed data content;
b. direct accessing to analytical functionality of integrated applications and/or analytical components; and
c. functional integration of data content according to data inter-relationships and analytical functionality required for interactive accessing; routing; viewing; querying; and analyzing of data content.
6. Within information technology platform architecture advantageously enabled in software as the “Sentient IT Platform”, comprising Intelligent Object data structures and the Intelligent Object Pool database structure, an Intelligent Object Handler data and applications handling framework is provided to enable functionally integrated user interactivity, said Intelligent Object Handler comprising structures and methods for one or more of
a. bi-directional information interchange with components and access interfaces comprising such as a data object with a comprised status management component agent; an object pool database structure with a comprised result aggregation engine; an object normalization engine; an object state engine; an object translation engine; and application translation interface, a master query interface; and a report generation interface;
b. utilizing unique Intelligent Object data structures and comprised processing components and access interfaces as accessing; routing; and processing elements; for
i. unified analysis of homogeneous and/or heterogeneous data content, contained within homogeneous and/or heterogeneous data formats, types and structures;
ii. by homogeneous and/or heterogeneous analytical applications, modules, and plug-ins;
iii. in homogeneous and/or heterogeneous network computing environments; to enable
c. provision of user interactivity utilizing said Intelligent Object data, Intelligent Object Handler, and Intelligent Object Pool applications within a unified, globally accessible graphical user environment, via an interactive unified presentation layer (UPL) graphical user interface.
7. An Intelligent Object Handler data and applications handling framework as in claim 6, wherein said methods for utilization, accessing, routing and processing of Intelligent Object data structures and applications further comprise
a. Intelligent Object (“IMO”, hereinafter “Intelligent Object”) data as core elements, which provide methods advantageous for data handling, for
i. automated and/or interactive data and data resource access, routing, processing, translation, analytical integration, viewing, analysis and management;
b. definition of said Intelligent Object data structures and data content according to methods comprising data matrix structure definition; application requirements definition; data resource definition; and
c. preparation of said Intelligent Object data structures and data content according to methods for data content and activity synchronization; standardization; translation; validation; ranking; and automated and/or interactive data organization;
d. nested vector table translation of data content presentation via extraction of required information, generation and provision of look up tables for applications integration; and
e. non-destructive cache-based “overlay” analytical processing of data content;
f. analysis and presentation of said Intelligent Object data structures and data content according to methods required for analysis by potentially heterogeneous applications; to enable:
g. unified analysis of homogeneous and/or heterogeneous data by heterogeneous analytical applications in heterogeneous network environments.
8. An Intelligent Object Handler data and applications handling as in claim 6, wherein said methods for unified utilization, accessing, routing and processing of Intelligent Object data structures further comprise one or more of
a. applications environment detection, extraction and definition for accessing, unified viewing, processing and routing; and
b. data content detection, extraction and definition for accessing, unified viewing, processing and routing.
9. An Intelligent Object Handler data and applications handling framework as in claim 6, wherein said methods for utilization, accessing, routing and processing of functionally integrated Intelligent Object data structures further comprise one or more of
a. direction of vectorized data content accessing, linking and routing between Intelligent Object data structures for direct parallel information interchange;
b. direction of meta-data accessing, linking and routing between Intelligent Object data structures for direct parallel information interchange;
c. direction of vectorized data content accessing, linking and routing between Intelligent Object data structures and applications for direct parallel information interchange;
d. direction of meta-data accessing, linking and routing between Intelligent Object data structures and applications; for direct parallel information interchange; and
e. comparison, ranking and organization of said Intelligent Object data structures and their data content according to Boolean analysis, structural matching and/or other statistical analyses of said information interchanged.
10. An Intelligent Object Handler data and applications handling framework as in claim 6, wherein said methods for user interaction further comprise one or more of
a. direct vectorized accessing to all relevant data content and meta-data properties of said potentially heterogeneous and distributed data content; and
b. direct accessing to analytical functionality of integrated applications and/or analytical components; and
c. functional integration of data content according to data inter-relationships and analytical functionality required for interactive accessing; routing; viewing; querying; and analyzing of data content utilizing said applications and applications components.
11. An Intelligent Object Handler data and applications handling framework as in claim 6, providing a graphical user interface comprising further methods for
a. User-directed functional integration of plug-ins; components; modules; applications; interfaces; from sources not limited to diverse scientific; business; manufacturing; academic; manufacturing; and laboratory systems environments; including
i. multi-platform installation; including for such as Unix, Linux, Win32, Mac OS 9 and 10, and other computer operating systems; and
ii. automated and/or interactive applications translation, integration, access, viewing and management; automated and/or interactive data and data resource access, routing, processing, translation, integration, viewing, analysis and management.
12. An Intelligent Object Handler data and applications handling framework as in claim 6, providing a graphical user interface comprising further methods for one or more of
a. interactive data object handling and analysis of data content, dynamically presented to enable user interactivity, via sets of customizable toolbars such as; user menus; and various analytical interfaces; such as File; New; Open; Open All (in directory); Close; Close All; Print preview; Print; Edit Undo; Redo; Cut; Copy; Paste; Select; Select All; and other customizable toolbars and menus.
13. A user definition and administration (UDA) component for user, access, authentication and privilege definition and processing, comprising methods for one or more of
a. bi-directional information interchange with components and access interfaces including the said User menu, Intelligent Object generator component; object state engine component; master query component; and
b. definition and integration of requirements for user, access, authentication and privilege definitions such as Laboratory Information Management Systems (LIMS) for local and/or remote data sources; applications; and other user activities within heterogeneous and/or homogeneous computing and/or network information environments.
14. A user definition and administration (UDA) component as in claim 13, functionally linked to a “User” menu comprised by said unified presentation layer within said Intelligent Object handler, said component comprising further methods for one or more of
a. provision of a user interface and functionality to set up and govern user preferences and privileges, for such as password settings; look preference;
color preference; local cache size; local cache clear; import settings; auto setup; connectivity profile; database access preference; applications list; personal data storage; and for
b. provision of a user interface and functionality for global user administration; comprising such as a dynamically updated list of user names; a dynamically updated list of user levels; Add User; Edit User; Export User; Import User; Lock/Unlock User; Retire User; and Clear User Password.
15. An Intelligent Object generator (IMO-G) component, to generate new Intelligent Objects, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including the data type translator component;
b. fielding of data object and content import requests;
c. generation of Intelligent Object data structures;
d. utilization of data content and information provided by a data type translator; for one or more of:
e. provision of run-time translation of heterogeneous data types and their data content into Intelligent Object data; and
f. assignation of a unique object identifier to the Intelligent Object, such as a 128 bit alphanumeric identifier.
16. An Intelligent Object generator (IMO-G) component as in claim 15, which comprises further methods for one or more of
a. bi-directional information interchange with components and access interfaces including the user definition and administration component; direct instrument acquisition and control component; and object state engine component; and
b. activation of object state history via the object state engine.
17. An object state engine (OSE) component for Intelligent Object state management, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including an object handler, status management component agents comprised by said Intelligent Objects; and master query interface;
b. monitoring and governing any activities of Intelligent Objects in real-time via a comprised active listening mode (ALM) 2028;
c. provision of continuously-running sets of processes updated by synchronization with any system clock, such as atomic clock synchronization over a network;
d. provision of a state processing method for recording Intelligent activity or transactions, to provide activity history;
e. provision of a state processing method assigning a defined state to the Intelligent Object to synchronize the current action;
f. provision of a query processing method for handling of external query submissions to Intelligent Objects;
g. provision of a query processing method for Intelligent Object-to-Intelligent Object query result synchronization;
h. provision of a query processing method for governing user access to Intelligent Objects and Intelligent Object-to-Intelligent Object intercommunication between Intelligent Objects, between said Intelligent Objects and applications, and between analytical and processing components; based on definitions such as security protocols and privilege definitions;
i. provision of a query processing method for governing user access to output generation of said Intelligent Objects and analyses;
j. provision of a query processing method for query status updating;
k. provision of a query processing method for query result synchronization;
l. provision of a query processing method for output generation;
m. provision of an access processing method for Intelligent Object root addressing and routing;
n. provision of an access processing method for data content addressing and routing;
o. provision of an access processing method for Intelligent Object-to-Intelligent Object linking and synchronization.
18. An object state engine (OSE) component as in claim 15, which comprises further methods for
a. bi-directional information interchange with components and access interfaces including the master query component; and legacy synchronization interface.
19. An object state engine (OSE) component as in claim 15, which comprises further methods for one or more of
a. Intelligent Object generator; Intelligent Object standardization component; Object and Image Normalization components; object translation engine component; data type translator component; direct instrument acquisition and control interface; triggering of the Intelligent Object generator to create a new Intelligent Object if an available Intelligent Object pertaining to queried data content does not exist;
b. assigning a unique identifier to newly generated Intelligent Objects;
c. provision of a state processing method for comparison of said activity history to GLP/GMP laboratory information management system (LIMS)-style experiment data states and validating any action by assigning a defined state to the object;
d. provision of a state processing method for validation state-based alerting and information ranking;
e. provision of a state processing method which queries existing data and application resources to detect and update data content status;
f. provision of a state processing method for accepting status updates received or “pushed” from external data and applications sources;
g. provision of a state processing method for maintaining status memory over state-less networks by transmitting action consequences back to the backend system;
h. provision of a query processing method for handling of network requests to Intelligent Objects;
i. provision of an access processing method comprising procedural ranking of requests for information exchange based on annotation or validation state of the addressed Intelligent Object;
j. provision of an access processing method for activating vectorized access to subsets of object data (“the workspace”) within provided data content matrices for dynamic information interchange; and
k. provision of an access processing method for access ordering and ranking; and synchronized accessing to raw data matrix vectors;
l. enabling other customized functionality for monitoring, governing, updating, synchronization, recordation and alerting activities of Intelligent Objects in real-time and/or within latency environments.
20. An object standardization technique (IMO-S) component for standardization of data content queried or processed, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including the object state engine; object translation engine; and
b. provision of calibration to data content via utilization of linear; non-linear;
polynomial; exponential; logarithmic; cubic spline; adaptive; weighted point-to-point fit; and a variety of multi-parametric functions.
21. An object standardization technique (IMO-S) component as in claim 20, which comprises further methods for one or more of
a. bi-directional information interchange with components and access interfaces including the object normalization engine component; and global image normalization component; and
b. activation and interaction with said components to provide automated standardization; and normalization of data; by methods for calibration by standardized empirical criteria.
22. An object normalization engine (ONE) component, for normalization of data to be compared, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including an object state engine;
b. normalization of scientific data contained in Intelligent Objects for comparison independent of procedural errors and multiple sources of errors inherent in multiple datasets of different origins; via comprised methods for
i. generation of a normalized global standard to provide algorithms to which all similar data can be referenced to in regard to their field parameters contained within the raw data matrix;
ii. application of said algorithms to user-defined workspaces addressed by dynamically generated vector subsets to minimize data exchange and increase processing speed, allowing for use of said algorithm even in network environments with limited data exchange capabilities;
iii. utilization of a workspace cache area for said processing to maintain data content integrity at all times; and
iv. provision of standard algorithms for processing a variety of scientific data configurations such as timeline-related; spectra or wavelength-related; kinetics-related; migration- or separation-related data content matrices in single and multidimensional variations; locational deviations within arrays, bioassay-related and gene and/or protein sequence-related raw data matrices.
23. An object normalization engine (ONE) component as in claim 22, which comprises further methods for
a. an object standardization technique component; an object translation engine; and application translation interface, a master query interface; and a report generation interface.
24. An object normalization engine (ONE) component as in claim 22, which comprises further methods for one or more of
a. provision of multi-parameter normalization in respect to color, intensity, dynamic range and x/y/z distortions in 2D and 3D scientific images;
b. provision of x/y/z-alignment and component distance adjustments in molecular structures; and acoustic wave pattern and/or video signals.
25. An object normalization engine (ONE) component as in claim 22, which comprises further methods for one or more of
a. detection of non-obvious data redundancies in diverse data resources, databases, data marts or data warehouses;
b. validation and accessibility ranking of such multiple records;
c. multiple addressing of such multiple records; and/or
d. elimination or retirement of such multiple records.
26. An object normalization engine (ONE) component as in claim 22, which comprises further methods for one or more of
a. application of said algorithms to subsets of decompressed workspaces within loss-free compressed raw data providing normalization to compressed data without the need for decompression of the entity of such data sets.
27. An object normalization engine (ONE) component as in claim 22, which comprises further methods for one or more of
i. tracking of deviations from an established global standard; and to
ii. correction of detected deviations in real-time for use in calibrated on- the-fly analysis applications.
28. An object normalization engine (ONE) component as in claim 22, which comprises further methods for
a. saving or transferring workspace cache area data converted by said algorithms between applications.
29. A direct instrument acquisition and control (DIAC) interface, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including the master query component; Intelligent Object generator component; object state engine component; and external instruments and devices;
b. acquisition of data content via instrumentation;
c. recordation of experimental and instrument running parameters; and
d. activation of a component for generation of Intelligent Objects corresponding to said data content.
30. A direct instrument acquisition and control (DIAC) interface as in claim 29, which comprises further methods for one or more of
a. automated detection and/or user definition of instrument and device dependencies, parameters, and/or operational method definitions;
b. definition and functional integration of said dependencies, parameters, and/or operational method definitions for interactive remote and/or local user interactivity and instrument control;
c. linking of said user-defined and or automatically detected instrument and/or device dependencies with said Instrument Control user interface; to enable
d. real-time, pre-programed and/or latent viewing and interactivity from local and/or remote locations; and
e. provision of an Instrument Control interface comprised by the unified presentation layer, which presents information for Connection status, such as presence or absence of connection and connection type information; instrument activity information such as run-time - hours, minutes, seconds; experiment status information such as validation status; instrument status information such as various operating parameters; and user interactivity such as start, pause, resume, stop.
31. A data type translator (DTT), which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including the Intelligent Object generator; object translation engine component; and application framework component;
b. fielding of applications and database environment definitions provided by an application/database definition generator interface; and
c. definition of data type dependencies to define the Intelligent Object;
32. A data type translator (DTT) as in claim 31, which comprises further methods for
a. provision of data type dependencies as required for linked components and access interfaces.
33. An object translation engine (OTE) component, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including the master query component; object state engine component; data type translator component; application/database definition generator; and master query interface;
b. activation of data object, data field and raw data matrix structure definition tables for translation of Intelligent Object presentation according to applications requirements;
c. activation of table lookup to provide real-time translation of the Intelligent Object within heterogeneous database and application environments;
d. activation of data structure information for non-object data for translation of Intelligent Object presentation according to applications requirements;
e. activation of data type, access and structure definition tables for translation of Intelligent Object presentation according to applications requirements;
f. activation of database type, access and structure definition tables for translation of Intelligent Object presentation according to applications requirements;
g. activation of application type, access and structure definition tables for translation of Intelligent Object presentation according to applications requirements; and
h. automated translation of said previously heterogeneous and/or incompatible data object into a variety of required data types; structures formats; and matrices.
34. An object translation engine (OTE) component as in claim 33, which comprises further methods for one or more of
a. activation of data content access and routing protocols required for functional integration for heterogeneous and/or dynamically defined query, viewing or analysis protocols; processing components; access interfaces; data resources; and/or applications environments; and
b. linking of said structure information and definition tables to dynamically direct Intelligent Object property pane activation and presentation; data object activation and presentation; data content activation and presentation; application activation and presentation; component activation and presentation; and interface activation and presentation; in real-time, according to defined data structure; database; and application requirements.
35. An application/database definition generator (ADG) component, for detection, extraction and generation of structural and functional information necessary for standardized unified access, presentation and utilization of heterogeneous data; comprising methods for one or more of
a. bi-directional information interchange with components and access interfaces including the object translation engine; Intelligent Object application framework; application translation interface; external data content; databases and data resources; and external applications and components;
b. provision of an interface for detection and extraction of diverse data object, data field and raw data matrix definitions
c. provision of an interface for detection and extraction of diverse data type, access, structure and functional dependencies;
d. provision of an interface for detection and extraction of diverse database type, access and structure dependencies;
e. provision of an interface for detection and extraction of diverse application type, access and structure dependencies;
f. provision of an automated query interface to define application and database dependencies according to automated and/or user-defined requirements utilizing said provided methods for
i. data table extraction to determine data object, data field and raw data matrix definitions;
ii. data type extraction to determine data access and structure dependencies for Intelligent Objects;
iii. database type extraction to determine database access and structure dependencies; and
iv. application type extraction to determine application type, access and structure;
g. dynamic updating of applications and database resource availability information based on presence, absence or other characteristics such as performance response time, for previously detected application and database functionality;
h. dynamic updating of applications and database resource availability information based on presence, absence or other characteristics such as performance response time, for application and database functionality requested at run-time;
i. generation of table definitions for look-up to provide real-time translation of Intelligent Object data content between and within heterogeneous computing environments; and
j. definition of the computing environment as required for linked components and access interfaces including the data type translator, the application framework and the application translation interface.
36. An application/database definition generator (ADG) component as in claim 35, comprising further methods for one or more of
a. provision of an interface for activation of external components for meta-data extraction;
b. generation of table definitions for look-up to provide real-time translation of Intelligent Object meta-data.
37. A master query component (MQC), which comprises methods for
a. bi-directional information interchange with components and access interfaces including an object state engine component; an Intelligent Object handle component; an Intelligent Object application framework component; and a master query interface;
b. fielding and direction of automated queries and commands for data acquisition; access, retrieval, translation, viewing, processing and/or analysis; and
c. provision of state-related vector definition of object data subsets for dynamic information interchange.
38. A master query component (MQC) as in claim 37, comprising further methods for one or more of
a. bi-directional information interchange with components and access interfaces including unified presentation layer toolbars and query interfaces; a direct instrument acquisition and control interface; an object translation engine; and
b. presentation of security, access and interactivity protocols to menus, toolbars and/or other tools for user interactivity according to said unified presentation layer; and
c. fielding and direction of user-directed queries and commands for data acquisition; access, retrieval, translation, viewing, processing and/or analysis.
39. A master query interface (MQI) for direct linking of vectorized data content and meta-data between Intelligent Objects, applications, analytical components and interfaces, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including the object state engine; external object query interfaces comprised by Intelligent Objects; components and/or access interfaces comprised by external Intelligent Object Pool and/or Intelligent Object Pools (“IOP”;
hereinafter “Pool(s)”); external result aggregation engine; and depending on the system configuration, to varied components, interfaces and data content resources;
b. linking to Intelligent Object root routing information;
c. linking to direct interactive Intelligent Object content routing vector addresses; and
d. linking to aggregated query result output provided by external result aggregation engines.
40. A master query interface (MQI) as in claim 39, which comprises further methods for one or more of
a. bi-directional information interchange with components and access interfaces including the master query component; object translation engine; Intelligent Object handle component;
b. linking to Intelligent Object meta-data content information;
c. linking to other external components and access interfaces for query processing, such as a distributed learning engine, or knowledge extraction engine.
41. An Intelligent Object handle component (IMO-H) for activation and direction of Intelligent Object information interchange, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including the master query component; master query interface; Intelligent Object application framework component; and report generation interface;
b. management of Intelligent Object data by activating and directing information linking provided by said components and access interfaces to comprised meta-data tags; data content attribute definitions; vector address pointers; comprised by said Intelligent Objects,
c. fielding of queries and/or command parameters provided by automated; and/or user-based methods.
42. A report generation interface (RGI), for generation of reports based on data information and aggregated processing results, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including the Intelligent Object handle component; object translation engine; distributed learning engines; knowledge extraction engines; and an external result aggregation engine component;
b. assembly of information comprised by such as data objects; specified meta-data indices of said data; specified data content subsets defined to levels of granularity as small as a single byte; and aggregated processing results;
c. tabulation of information comprised by such as data objects; specified meta- data indices of said data, specified data content subsets defined to levels of granularity as small as a single byte; and aggregated processing results;
i. according to information and requests received from external processing engines and access interface components; and
d. relaying generated results to external processing engines, access interfaces and pane descriptor components in an automated, synchronized, real-time manner.
43. A report generation interface (RGI) as in claim 42, which comprises fuirther methods for one or more of
a. validation reporting regarding information comprised by such as data objects; specified meta-data indices of said data; specified data content subsets defined to levels of granularity as small as a single byte; and aggregated processing results; and
b. ranked reporting of information comprised by such as data objects; specified meta-data indices of said data; specified data content subsets defined to levels of granularity as small as a single byte; and aggregated processing results;
i. according to information and requests received from external processing engines and access interface components.
44. An Intelligent Object application framework (IMO-A) for functional integration of Intelligent Object data with applications components, plug-ins and modules, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including the Intelligent Objects and their content; master query component; data type translator component; Application/Database Definition Generator; Intelligent Object handle component; application translation interface; applications comprised within said Intelligent Object handler as components, modules and/or plug-ins;
b. fielding of automated and/or user-directed queries; applications assembly commands; processing requests; viewing requests; other dynamic applications needs;
c. detection of required components, interfaces and protocols to enable functionally integrated analysis utilizing homogeneous and/or heterogeneous data content and applications; and
d. activation and enabling of a comprised automated applications assembly component to enable dynamic assembly of applications utilizing Intelligent Objects for unified, functionally integrated analysis utilizing homogeneous and/or heterogeneous data content and applications.
45. An automated applications assembly component (AAA), to enable automated assembly of new applications during run-time (“just-in-time”) from sets of components according to specific needs and best suited for complex processing requirements in heterogeneous data and applications environments, comprising methods for one or more of
a. selection and combination of required I/O components, such as components required to transfer data into and results out of individual analytical and/or descriptive and/or annotative components;
b. selection of algorithms best suited for processing of specifically defined data types or data type descriptors;
c. dynamic combination of said components and algorithms towards automated and/or user-defined analytical performance goals, utilizing distributed subcomponent integration under best-fit conditions;
d. activation of required components, interfaces and protocols to enable functionally integrated analysis utilizing homogeneous and/or heterogeneous data content and applications;
e. synchronization of required components, interfaces and protocols to enable functionally integrated analysis utilizing homogeneous and/or heterogeneous data content and applications;
f. assembly of required components, interfaces and protocols to enable functionally integrated analysis utilizing homogeneous and/or heterogeneous data content and applications memory ranking of performance-optimized component selection;
g. memory ranking of information-optimized component selection; and
h. best choice adjustment according to user-defined functional requirements.
46. An automated applications assembly (AAA) component according to claim 45, further contained in a stand-alone application or module for non-object data.
47. An automated applications assembly (AAA) component according to claim 45, further contained in a stand-alone application or module for object data.
48. An automated applications assembly (AAA) component according to claim 45, further contained as a plug-in or module for an information technology platform containing Intelligent Object data.
49. An automated applications assembly according to claim 45, in which selection of components is based on their immediate availability for real-time use.
50. An automated applications assembly according to claim 45, comprising further methods for one or more of:
a. selection of components based on their functional consistency and accuracy within all components assembled, such as, but not limited to functions for governing raw data precision; handling of mathematical errors; provision of data pointer referencing; matrix operation synchronization in regard to internal or external transformations and dimension descriptions; output rounding; determination of logical processing pathways; accounting for Boolean inheritances; iterative step tracing; and controlling and logging of rollback behavior.
51. An automated applications assembly according to claim 45, comprising further methods for one or more of:
a. selection of components is based on the ranking among available components in regard to overall performance, such as, but not limited to one or more of: network traffic; local processing; remote processing; process sharing; distributed processing; direct “on-object”-processing; result clustering; and graphics element preprocessing and charting.
52. An automated applications assembly according to claim 45, comprising further methods for one or more of:
a. selection of components based on the ranking among available components in regard to validation required for decisive answers (output knowledge assessment).
53. An automated applications assembly according to claim 45, comprising further methods for
a. provision of a vectorized “Application Archive Table” for quick referencing of previously assembled applications with similar processing needs.
54. An automated applications assembly according to claim 45, comprising further methods for
a. provision of “on-the-fly” temporary applications memory management for Just-in-Time (JIT) component linking, loading and unloading from the active caching area.
55. An automated applications assembly according to claim 45, comprising further methods for
a. provision of an intuitive interactive graphical user interface for drag-&-drop selection of components for process modeling and analytical simulations based on user output requests.
56. An automated applications assembly according to claim 45, comprising further methods for
a. provision of active communication with learning engines, such as for example, a distributed learning engine or knowledge extraction engine to optimize iterative processes or loop algorithms based on condition feedback.
57. An application translation interface (ATI), for presentation of Intelligent Object data according to heterogeneous applications requirements, which comprises methods for
a. bi-directional information interchange with components and access interfaces such as the Intelligent Object Handler; master query interface, provision of an interface layer to present defined data object, data field and raw data matrix structure definitions to required external data resources; applications; access interfaces; and processing components utilizing provided definition look-up tables;
b. provision of an interface layer to present defined data type, access, structure and function definitions to required external data resources; applications; access interfaces; and processing components via provided look-up tables;
c. provision of an interface layer to present defined database type, access, structure and function definitions to required external data resources; applications; access interfaces; and processing components via provided look-up tables;
d. provision of an interface layer to present defined application type, access and structure definitions to required external data resources; applications; access interfaces; and processing components via provided look-up tables; and
e. transferring of requests such as read/write processes within or in-between external applications; Intelligent Object and data content property presentation in real-time, according to defined requirements.
58. An application translation interface (ATI), for presentation of Intelligent Object data according to heterogeneous applications requirements, which comprises methods for
a. bi-directional information interchange with components and access interfaces such as the result aggregation engine; application/database definition generator; application handling framework; external result aggregation engine; as well as with external data resources; applications; access interfaces; and processing components.
59. A legacy synchronization interface (LSI), for updating and synchronization of batch processed or temporarily offline Intelligent Object data and data content, which comprises methods for one or more of
a. bi-directional information interchange with components and access interfaces including the object state engine; and external data content, databases, and data resources;
b. synchronization of object data of various types with data content contained in off-line and/or batch processing legacy databases or external applications, in regard to data integrity, content and state for updating of such as raw data vector matrices linking; and property pane content definition;
c. synchronization of Intelligent Object data with data content contained in off- line and/or batch processing legacy databases or external applications in regard to data integrity, content and state for updating of such as raw data vector matrices linking; and property pane content definition;
d. synchronization of Intelligent Object data content with external, off-line or temporarily unavailable data sets in regard to data integrity, content and state for updating of such as raw data vector matrices linking; and property pane content definition.
60. A legacy synchronization interface (LSI) as in claim 59, comprising further methods for
a. reporting to the object slate engine to update state history records for changes during times where activity-listening-mode is temporarily unavailable under conditions, such as, but not restricted to off-line; connection time-out; transaction acknowledgement errors; or record locking conflicts on the legacy end.
61. A legacy synchronization interface (LSI) as in claim 60, comprising further methods for one or more of
a. metadata index updating in batch mode; and for
b. object pane descriptor updating whenever object panes are added or descriptors need to be modified; by
c. relaying required information to said object state engine component.
62. A legacy synchronization interface (LSI) as in claim 60, comprising further methods for one or more of
a. provision of link functions between “local state machines” or agents, such as for “pushed” updating and said object state engine component; to enable
b. synchronous handshaking during connect and disconnect of heterogeneous legacy data and/or applications;
c. transaction management and accounting for such as “once-and-only-once” transactions;
d. linking between “local state machines” or agents and components within the unified presentation layer of said Intelligent Object handler; to enable
e. platform-integration of external applications, which modify data properties during their execution, for synchronization and update.
63. A legacy synchronization interface (LSI) as in claim 60, comprising further methods for one or more of:
a. provision of feedback on synchronization conditions for frequency; updates; and timing preferences towards a variety of internally and/or externally comprised components and interfaces, such as knowledge extraction engines; and distributed learning engines; and for
b. “best-fit” optimization of synchronization and timing based on said event history feedback.
64. A legacy synchronization interface as in claim 60, comprising further methods for
a. logging and reporting of synchronization events to methods comprised within such as Intelligent Objects; processing components; access interfaces; applications; data resources and/or databases; and
b. provision of the interface to integrate required methods for synchronization requests or “pulls” and/or metadata index updates utilizing provided protocols and/or definitions such as user preferences; user profiles; administrative protocols; and/or maintenance action definitions.
Description
RELATED APPLICATIONS

[0001] Priority is hereby claimed under 35 U.S.C. 120 and/or 35 U.S.C. 119(e) to the following United States Provisional and Utility Patent Applications, each of which is hereby incorporated by reference:

[0002] U.S. Utility Patent Application Serial No. _/___,___ (Attorney Docket No. A-70134/RMA) filed Dec. 6, 2001 and entitled Data Pool Architecture, System, And Method For Intelligent Object Data In Heterogeneous Data Environments;

[0003] U.S. Utility Patent Application Serial No. _/___,___ (Attorney Docket No. A-70135/RMA) filed Dec. 6, 2001 and entitled Intelligent Molecular Object Data Structure and Method for Application in Heterogeneous Data Environments with High Data Density and Dynamic Application Needs;

[0004] U.S. Utility Patent Application Serial No. _/___,___ (Attorney Docket No. A-70136/RMA) filed Dec. 6, 2001 and entitled Intelligent Object Handling Device and Method for Intelligent Object Data in Heterogeneous Data Environments with High Data Density and Dynamic Application Needs;

[0005] U.S. Utility Patent Application Serial No. _/___,___ (Attorney Docket No. A-70310/RMA) filed Dec. 6, 2001 and entitled System, Method, Software Architecture, And Business Model For An Intelligent Object Based Information Technology Platform;

[0006] U.S. Provisional Application Serial No. 60/254,063 filed Dec. 6, 2000 entitled Data Pool Architecture for Intelligent Molecular Object Data in Heterogeneous Data Environments with High Data Density and Dynamic Application Needs;

[0007] U.S. Provisional Application Serial No. 60/254,062 filed Dec. 6, 2000 entitled Intelligent Molecular Object Data for Heterogeneous Data Environments with High Data Density and Dynamic Application Needs;

[0008] U.S. Provisional Application Serial No. 60/254,064 filed Dec. 6, 2000 entitled Handling Device for Intelligent Molecular Object Data in Heterogeneous Data Environments with High Data Density and Dynamic Application Needs;

[0009] U.S. Provisional Application Serial No. 60/259,050 filed Dec. 29, 2000 entitled Object State Engine for Intelligent Molecular Object Data Technology;

[0010] U.S. Provisional Application Serial No. 60/264,238 filed Jan. 25, 2001 entitled Object Translation Engine Interface For Intelligent Molecular Object Data;

[0011] U.S. Provisional Application Serial No. 60/266,957 filed Feb. 6, 2001 entitled System, Method, Software Architecture and Business Model for an Intelligent Molecular Object Based Information Technology Platform;

[0012] U.S. Provisional Application Serial No. 60/276,711 filed Mar. 16, 2001 entitled Application Translation Interface For Intelligent Molecular Object Data In Heterogeneous Data Environments With Dynamic Application Needs;

[0013] U.S. Provisional Application Serial No. 60/282,656 filed Apr. 9, 2001 entitled Result Generation Interface For Intelligent Molecular Object Data In Heterogeneous Data Environments With Dynamic Application Needs;

[0014] U.S. Provisional Application Serial No. 60/282,658 filed Apr. 9, 2001 entitled Knowledge Extraction Engine For Intelligent Object Data In Heterogeneous Data Environments With Dynamic Application Needs;

[0015] U.S. Provisional Application Serial No. 60/282,654 filed Apr. 9, 2001 entitled Result Aggregation Engine For Intelligent Object Data In Heterogeneous Data Environments With Dynamic Application Needs;

[0016] U.S. Provisional Application Serial No. 60/282,657 filed Apr. 9, 2001 entitled Automated Applications Assembly Within Intelligent Object Data Architecture For Heterogeneous Data Environments With Dynamic Application Needs;

[0017] U.S. Provisional Application Serial No. 60/282,655 filed Apr. 9, 2001 entitled System, Method And Business Model For Productivity In Heterogeneous Data Environments;

[0018] U.S. Provisional Application Serial No. 60/282,979 filed Apr. 10, 2001 entitled Legacy Synchronization Interface For Intelligent Molecular Object Data In Heterogeneous Data Environments With Dynamic Application Needs;

[0019] U.S. Provisional Application Serial No. 60/282,989 filed Apr. 10, 2001 entitled Object Query Interface For Intelligent Molecular Object Data In Heterogeneous Data Environments With Dynamic Application Needs;

[0020] U.S. Provisional Application Serial No. 60/282,991 filed Apr. 10, 2001 entitled Distributed Learning Engine For Intelligent Molecular Object Data In Heterogeneous Data Environments With Dynamic Application Needs; and

[0021] U.S. Provisional Application Serial No. 60/282,990 filed Dec. 10, 2001 entitled Object Normalization For Intelligent Molecular Object Data In Heterogeneous Data Environments With Dynamic Application Needs;

[0022] each of which U.S. utility and U.S. provisional patent application is hereby incorporated by reference in its entirety.

FIELD OF INVENTION

[0023] This invention pertains generally to system, method, computer program product, data structure and architecture, data management, and software architecture; and more particularly to system, method, computer program product, and data structure and architecture, data management, and software architecture in the life sciences, biotechnology, therapeutic diagnostic and intervention, pharmaceuticals, and bioinformatics.

BACKGROUND

[0024] As demand for effective Information Technology (IT) software to provide global data access and integrated scientific and business solutions has grown, significant challenges have become evident. A central problem poses access, integration, and utilization of large amounts of new and valuable information generated in each of the major industries. Lack of unified, global, real-time data access and analysis is detrimental to crucial business processes, which include new product discovery, product development, decision-making, product testing and validation, and product time-to-market. Additionally, the importance of functionally integrating multiple dimensions of heterogeneous data in the field, such as protein expression data, chemical structure data, bioassay data and clinical text data, is recognized (Lin, D., et al., 2001).

[0025] With the completion of the sequence of the human genome and the continued effort in understanding protein expression in the life sciences, a wealth of new genes are being discovered that will have potential as targets for therapeutic intervention. As a result of this new information, however, Biotech and Pharmaceutical companies are drowning in a flood of data. In the Life Sciences alone, approximately 1 Terabyte of data is generated per company and day, of which currently the vast majority is unutilized for several reasons.

[0026] Data are contained in diversified system environments using different formats, heterogeneous databases and have been analyzed using different applications. These applications may each apply different processing to those data. Competitive software, based on proprietary platforms for network and applications analysis, have utilized data platform technologies such as SQL with open database connectivity (ODBC), component object model (COM), Object Linking and Embedding (OLE) and/or proprietary applications for analysis as evidenced in patents from such companies as Sybase, Kodak, IBM, and Cellomics in U.S. Pat. No. 6,161,148, U.S. Pat. No. 6,132,969, U.S. Pat. No. 5,989,835, U.S. Pat. No. 5,784,294, for data management and analysis, each of which patents are hereby incorporated by reference. Because of this diversity, despite the fact that the seamless integration of public, legacy and new data is crucial to efficient drug discovery and life science research, current data mining tools cannot handle all data and analyze their functional relationships simultaneously. There is a significant lack of data handling methods, which can utilize these data in a secure, manageable way. The shortcomings of these technologies are evident within heterogeneous software and hardware environments with global data resources. Despite the fact that the seamless integration of public, legacy and new data is crucial to efficient research (particularly in the life sciences), product discovery (such as for example drug, or treatment regime discovery) and distribution, current data mining tools cannot handle or validate all diverse data simultaneously.

[0027] With the expansion of high numbers of dense data in a global environment, user queries often require costly massive parallel or other supercomputer-oriented processing in the form of mainframe computers and/or cluster servers with various types of network integration software pieced together for translation and access functionality as evidenced by such companies as NetGenics, IBM and ChannelPoint in U.S. Pat. No. 6,125,383 U.S. Pat. No. 6,078,924, U.S. Pat. No. 6,141,660, U.S. Pat. No. 6,148,298, each of which patents are herein incorporated by reference—(e.g. Java, CORBA, “wrapping”, XML) and networked supercomputing hardware as evidenced by such companies as IBM, Compaq and others in patents such as for example U.S. Pat. No. 6,041,398, U.S. Pat. No. 5,842,031, each of which is hereby incorporated by reference. Even with these expensive software and hardware infrastructures, significant time-delays in result generation remain the norm.

[0028] In part due to the flood of data and for other reasons as well, there is a significant redundancy within the data, making queries more time consuming and less efficient in their results. Tools are not yet in place which can effectively detect data redundancy over heterogeneous data types and network environments, especially of data content subsets within data files, and provide ranked and validated multiple addressing and/or removal of said redundant data. The flood of new and legacy data results in a significant redundancy within the data making queries more time consuming and less efficient in their results.

[0029] With the advent of distinct differentiations in the field of genomics, proteomics, bioinformatics and the need for informed decision making in the life sciences, the state of object data is crucial for their overall validation and weight in complex, multi-disciplinary queries. This is even more important due to inter-dependencies of a variety of data at different states. Furthermore, because biological data describe a “snapshot” representing a unique moment of complex processes at a defined state of the organism, data obtained at any time refer to this unique phase of metabolism. Thus, in order to account for meaningful comparison, only data in similar states can be utilized. Therefore, there is a growing need for an object data state processing engine, which allows to continuously monitor, govern, validate and update the data state based on any activities of intelligent molecular objects in real-time. Currently, these capabilities are not broadly available for network data structures, and they are not available for data structures integrating heterogeneous data over distributed network environments.

[0030] With the advent of distinct differentiations in the field of genomics, proteomics, bioinformatics and the need for informed decision making in the life sciences, access to all data is crucial for overall validation and weight in complex, multi-disciplinary queries. This is even more important due to inter-dependencies of a variety of data at different states. The current individual data translation approach does not support these needs. Most of these problems require real-time processing; automated, instant data translation of data from different sources; and integration of heterogeneous applications and analytical components for their solutions. Data contained in diversified system environments may use different formats, heterogeneous databases and different applications, each of which may apply different processing to those data. Therefore, there is a growing and unmet need for an automated object data translation engine, which allows for bi-directional translation of multidimensional data from various sources into intelligent molecular objects in real-time. Currently, data translation processes between different data types are time-consuming and require administrative exchange of information on data structures, pplication programming interfaces (API's) and other dependencies, as required by the latest technologies such as Incellico's CELL, IBM's DiscoveryLink, Netgenic's Synergy and Tripos' MetaLayer solutions (Haas et al 2001). These processes, although available and used, have a number of shortcomings. Despite the fact that the rapid seamless integration of public, legacy and newly emerging data is crucial to efficient drug discovery and life science research, unique “wrappers” or translation layers must currently be designed and programmed in order to translate each of those data sets correctly, and even with this manual integration, multiple data types and dimensions of data interdependencies are not made available, or “functionally integrated” for detailed qualitative and quantitative comparison and analysis across data types and dimensions. These solutions currently require significant effort and resources in both, software development and data processing, and the need for improvements such as those offered by this invention are recognized.

[0031] An additional consideration, which is prohibitive to change towards a more homogeneous infrastructure is the missing of fluently definable object representation definition protocols to prepare and present data objects for unified, functionally integrated interaction within heterogeneous environments. There is a lack of defined sets of user interaction and environment definition protocols needed to provide means for intelligent data mining and optimization of multidimensional analysis to achieve validated solutions. Data currently are interacted with and presented in diverse user interfaces with dedicated, unique features and protocols, preventing universal, unified user access. Thus, a homogeneous, unified presentation such as a flexibly network-enabled graphical user interface, which integrates components from diverse applications and laboratory systems environments over a variety of connections and protocols, is highly desirable, but currently non-existent for real-time data access and analysis utilizing diverse applications and data.

[0032] Finally, an additional consideration, which is prohibitive to change towards a homogenous data and applications infrastructure, is cost. The cost to bring legacy systems up to date, to retool a company's intranet-based software systems, to create a unified environment utilizing existing software products and tools such as CORBA, JAVA, XML, SQL and classic data warehousing techniques, can be time-consuming and expensive. Conventional practices require retooling and/or translating at both application and hardware layers, as evidenced by such companies as Unisys and IBM in U.S. Pat. No. 6,038,393, U.S. Pat. No. 5,634,015, and may be prohibitively expensive for smaller and medium-sized companies or groups wishing to access this type of functionality.

[0033] Because of the constraints outlined above, it is nearly impossible to extract useful, functionally integrated information from the entity of data within reasonable computing time and efforts. For these reasons, the development of a unique architecture and system, comprising a unique application framework, data structure, and database structure, is unavailable and needed to overcome these obstacles (Hobbs, D. W. 2001).

[0034] LITERATURE

[0035] Andreoli, J-M., In: Agha G., Wegner P., Yonezawa A.(eds.): Research Directions in Concurrent Object-Oriented Programming, MIT Press (1993): 260-263; Bertino E., Urban S., Rundensteiner E. A.(eds.): Theory and Practice of Object Systems (1999) 5 (3): 125-197; Chaudhri A. B., McCann J. A., Osmon P.: Theory and Practice of Object Systems (1999) 5 (4): 263-279; Cai D., McTear M. F., McClean S.I.: International Journal of Intelligent Systems (2000): 15 (8): 745-761; Hert C. A., Jacob E. K., Dawson P.: Journal of the American Society for Information Science (2000) 51 (11): 971-988; Hobbs, D. W., Chemical and Engineering News. (2001) 79 (13): 266; Lin, D., et al.: American Genomic/Proteomic Technology (2001) 1 (1): 38-46; Williams R. J., In: Miller W., Thomas I., Sutton R. S., Werbos, P. J. (eds.): Neural Networks for Control, MIT Press (1990): 97-114; Wilson G. V., Lu P. (eds.): Parallel Programming and C++, MIT Press (1996): 257-280.; C. N. Lauro, G. Giordano, R. Verde: Applied Stochastic Models and Data Analysis: A multidimensional approach to conjoint analysis (1998) 14 (4): 265-274; Meyer, Bertrand: IEEE Computer. (1999) 32 (1): 139-140.; Chalmers, Mathew: Journal of the American Society for Information Science. (1999) 50 (12): 1108-1118.; Teasley, Stephanie and Steven Wolinsky: Science. (2001, June 22) 292:2254; Haas, L. M., et al: IBM Systems Journal. (2001) 40 (2): 489-511.; Siepel, A., et al: IBM Systems Journal. (2001) 40 (2): 570-591; and Steiner, S. and Witzmann, F. A.. Electrophoresis. (2000) 21: 2099-2104; each of which publications are incorporated by reference.

[0036] The following United States Patents: U.S. Pat. No. 5,596,744, U.S. Pat. No. 5,867,799, U.S. Pat. No. 5,745,895, U.S. Pat. No. 6,076,088, U.S. Pat. No. 5,706,453, U.S. Pat. No. 5,767,854, U.S. Pat. No. 6,035,300, U.S. Pat. No. 6,145,009, U.S. Pat. No. 5,664,066, U.S. Pat. No. 5,862,325, U.S. Pat. No. 6,016,495, U.S. Pat. No. 6,119,126, U.S. Pat. No. 6,088,717, U.S. Pat. No. 6,052,722, U.S. Pat. No. 6,064,382, U.S. Pat. No. 6,134,581, and U.S. Pat. No. 6,146,027; each of which publications are incorporated by reference.

SUMMARY

[0037] System, method, computer program and computer program product are provided for: generation of Intelligent Object data; unified presentation of dynamically customizable functional menus and interfaces such as for user definition, administration and security protocols; secured user interaction, access and presentation based on imported and/or defined user definition, administration and security protocols; data object standardization and normalization; definition of user interaction and computing environment protocols required for data object translation, standardization, access and routing; definition of data type access, translation, presentation and routing protocols for functional data and applications integration; definition of application and/or application components and interface access, translation, presentation and routing protocols for functional data and applications integration; provision of interactive, unified, functionality for data acquisition, management, viewing and analysis; as well as other methods and procedures as described in detail herein. Such methods an techniques whether implemented in computer program software or otherwise is useful in heterogeneous data environments with high data density and dynamic application needs.

[0038] In the object creation methods, the Intelligent Object generator extracts relevant data information, routes real-time data from ongoing data acquisitions and transforms device outputs and heterogeneous data types to Intelligent Object data. Data content may be stored remotely from the corresponding Intelligent Object, and both, data content as well as Intelligent Objects (stored in “Intelligent Object Pools” or Pool subset “iPools”) may be stored locally or may be distributed across heterogeneous data storage resources and networks. Next, components such as the object standardization technique and the object normalization engine standardize and normalize the data by calibration according to standardized empirical criteria.

[0039] In the interactive user access and presentation methods, the unified presentation layer provides the web-enabled graphical user interface that integrates the technology defined to unify diverse applications, laboratory systems environments, and Intelligent Object data at the graphic user interface layer. As an example, in the security and access methods, the user menu activates the user definition and administration shell and prompts for user input regarding access privileges environments at login. The master query component then presents security and access protocols to the unified presentation layer and to the object state engine for authentication and permits or denies access to begin fielding user queries and commands for data acquisition, retrieval, or analysis.

[0040] In the methods for interactive, functionally integrated data acquisition, management, viewing and analysis, user interactivity at the front end is enabled by the unified presentation layer, which is linked to defined processing components and access interfaces.

[0041] In the environment definition methods, the application/database definition generator interface dynamically detects application and database requirements and defines the computing environment for the data type translator, the application translation interface, and the application framework.

[0042] In the object definition methods, the data type translator defines the data type dependencies for the Intelligent Object generator, the object translation engine and the application framework component according to the applications and database environment defined by the application/database definition generator.

[0043] Simultaneously, in the functional integration methods, the Intelligent Object application framework provides functional integration of components, access interfaces and Intelligent Objects comprised by the Intelligent Object Handler, to provide fast, efficient, functionally integrated querying, viewing and analysis. Components and interfaces such as the application/database definition generator interface and the application translation interface provide access and routing protocols to heterogeneous applications and databases.

[0044] Additionally, in the methods for functional integration, the Intelligent Object handle enables activities including real-time acquisition, management, viewing and analysis of Intelligent Object data through the utilization of integrated meta-data tags and pointers activated by the master query component and returned via components and access interfaces to the master query interface for presentation to the user.

[0045] Finally, automated and/or user-directed interaction with external applications, processing components, instruments and devices is enabled by access interfaces including the master query interface, direct instrument acquisition and control, legacy synchronization interface, and report generation interface.

BRIEF DESCRIPTION OF THE DRAWINGS

[0046]FIG. 1 depicts an embodiment of the unified presentation layer for the Sentient (IMO) IT Platform, showing the Intelligent Object Handler and a variety of Intelligent Objects.

[0047]FIG. 2 depicts an embodiment of a query dialog within the Intelligent Object Handler utilizing Intelligent Object handle features.

[0048]FIG. 3 depicts an embodiment of the intelligent object handler in their relationships comprising a unified presentation layer, components and access interfaces. The figure shows the relationship of the Intelligent Object Handler (“IOH”) to its comprised components and access interfaces, such as to the “IOH User”, to Intelligent Objects (“IMO(s)”), to an external Intelligent Object Pool (“IOP”) and its comprised components and access interfaces, and to the external “Legacy”domain of existing heterogeneous data content, applications, and devices.

[0049]FIG. 4 depicts an embodiment of an exemplary hardware configuration for the Intelligent Object Handler and its enabling architecture.

[0050]FIG. 5 depicts an embodiment of the Intelligent Object Handler comprised within a software information technology platform architecture (such as the exemplary Sentient IT Platform) for one exemplary and advantageous embodiment.

[0051]FIG. 6 depicts an embodiment of the object state engine showing its major functions, internal architecture and certain of its relationships to external components.

[0052]FIG. 7 depicts an embodiment of the object translation engine showing its relationships to external databases and to required and optional components and access interfaces.

[0053]FIG. 8 depicts an alternative embodiment of the object translation engine.

[0054]FIG. 9 depicts an embodiment of the Intelligent Object Handler, providing an overview for a more general understanding of the Intelligent Object Handler's functions.

[0055]FIG. 10 is an illustration depicting an embodiment of a first menu.

[0056]FIG. 11 is an illustration depicting an embodiment of a another menu screen showing various pull-down menu details and options.

DESCRIPTION OF EXEMPLARY EMBODIMENTS

[0057] Methods are provided to define and describe an exemplary embodiment of an information technology platform architecture utilizing an Intelligent Object Handler (IOH) 202 and Intelligent Object (IMO) 200 data structures as core processing components. The Intelligent Object Handler (IOH) 202 comprises a unified presentation layer (UPL) 206 to enable user interactivity, component processing engines and access interfaces required to enable interactive, secure, efficient, property-driven functional access to data content queried, presented and analyzed, utilizing a variety of raw data sources, applications and analytical components. Additionally, optional embodiments define and describe an information technology platform architecture utilizing the Intelligent Object Handler (IOH) 202 for any object data structures as core processing components.

[0058] For reasons of explanation, these methods, components and processes will be described in a fashion that does not represent the entity of simultaneous and/or interactive actions as they occur. However, it should be noted that the system herein described is composed of bi- directonally interactive components and interfaces which perform certain tasks simultaneously, or in a rapidly alternating fashion.

[0059] Examples of enabling code are provided to define and describe a single exemplary embodiment, which utilizes Microsoft C++ as the exemplary programming language. Additionally, software development tools not limited to Visual C++, Microsoft Foundation Classes (MFC), DIB image transformations and matrix-based graphical content generation were utilized to enable this specific embodiment. The overall architecture, its application across varied domains, its processing engines and its access interfaces are in no way limited to the utilization of Microsoft C++ or the Windows 32-bit operating system environment. It is readily apparent to anyone skilled in the art that other enabling software codes or enabling techniques may also be used, including for example Java, XML and other markup languages, and/or other similar techniques.

[0060] The Intelligent Object Handler (IOH) 202 may be compiled to run on multiple platforms, including, but not limited to, UNIX, Linux, Macintosh OS 9 and 10, or any Window 32-bit operating systems. The following hardware specifications are provided to define and describe the requirements for a specific exemplary embodiment, implemented for a 32-bit Microsoft Windows environment.

[0061] The depiction in FIG. 1, represents an embodiment of a graphical user interface (and the display image available via that interface) for interaction with Intelligent Object data. The dynamically defined menu bar shows extensible options in a standard order, consisting of, but not limited to, drop-down menu items such as file, edit, view, options, objects, selection, query, analysis, link, user, window and help-functions. Within the common user interface window, several independent sub-windows show a depiction of the Intelligent Objects, as well as related query and/or analysis tools and the real-time answer window, which presents the relevant results in their significance numerically and/or graphically.

[0062] The depiction in FIG. 2, represents an embodiment of a typical query profiler (and the screen display image resulting therefrom) utilizing Intelligent Object technology. Such queries can be performed using pre-definable templates, subsets of common, industry-specific questions, and/or by free form, user-defined entries and graphical “drag-and-drop” query definition.

[0063] The inventive system, architecture, method, and computer program and computer program product of the Intelligent Object Handler (IOH) as well as other core elements and modules described herein and in the related applications identified herein, may be used in a variety of computing and network or connectivity environments as are known in the art and advantageoulsy are hardware and operating system agnostic. For example, the invention may be practices with the great majority of contemporary personal computers, workstations, mainframes, as well as notebook and other portable computing devices and all manner of information appliances. Exemplary computing devices and components are for example illustrated in the embodiments illustrated in FIG. 3, FIG. 4, and FIG. 5.

[0064] It will be apparent to anyone skilled in the art in light of the description provided herein that these requirements are provided by way of instruction regarding a specific embodiment of the technology, and that the implementation of the Intelligent Object Handler (IOH) 202 is not limited to the particular embodiments shown in the drawings as many optional components that provide optional and enhanced features are shown that are not required.

[0065] An overview of major presentation, processing and interface methods are provided below to describe and define, in an exemplary embodiment, the Intelligent Object Handler (IOH) 202 comprised by information technology architecture for user interaction, viewing, analysis, and other automated and/or interactive data handling activities utilizing Intelligent Object (IMO) 200 data as core components. In an optional embodiment, and Intelligent Object Handler (IOH) 202 utilizing a variety of object data is defined and described.

[0066] The embodiment of the system, architecture, and method in FIG. 3, represents an exemplary embodiment of the inventive elements and their relationships, showing the relationship of the Intelligent Object to an external Intelligent Object Handler (IOH), its components and access interfaces, the legacy domain of existing data content, applications, and devices, and an external Intelligent Object Pool (IOP). Unbroken lines ending with arrows on each end 490 represent bi-directional communication between exemplary property panes, components and access interfaces. Dashed lines ending with arrows on each end 492 represent bi-directional communication between optional property panes, components and access interfaces. Forked lines 491 at or near the “interface to external legacy domain” were utilized for clarity due to the complexity of the figure, and represent unbroken bi-directional connectivity between opposed arrows. Crossed lines do not represent connections in this figure.

[0067] The depiction in FIG. 4, represents an exemplary embodiment of a hardware configuration for the Intelligent Object Handler and its enabling architecture. All major elements within the diagram below may be bi-directionally connected over a variety of network protocols. The minimum hardware requirement is defined by a single machine. In an exemplary embodiment, as below, two laptop computers are connected in a peer-to-peer configuration and in a client/server configuration to a workstation and via these workstation directly to a laboratory instrument, such as a gene sequencer or gel electrophoresis machine. Other connectivity schemes may alternatively or additionally be provided.

[0068] In FIG. 4, dotted bi-directional lines 248 represent options for “any-to-any” connectivity enabled via use of Intelligent Objects as central accessing and routing components. Any-to-any options include but are not limited to LAN, WAN, peer-to-peer (e.g. data, applications, memory and processor sharing between two or more laptops, workstations, etc.), server-server, Portal, ASP and other unified, distributed, parallel and grid network options. Connectivity protocols include and are not limited to PPP, http, TCP/IP, and ftp over multiple platforms.

[0069] The depiction in FIG. 5, represents an embodiment of the Intelligent Object Handler comprised within an exemplary software platform architecture (Sentient IT Platform). This embodiment depicts minimal core elements for the Intelligent Object Handler, along with the Intelligent Object, Intelligent Object Pool, and other components (Processing Engines) and access interfaces required by or desired in the Sentient IT Platform.

[0070] In an exemplary embodiment advantageously enabled in software, sets of structures and methods are provided for; unified, functionally integrated and user-directed interactivity with previously heterogeneous data and applications; applications environment and data definition and translation; and functional integration of heterogeneous and/or homogeneous data objects and their contents with comprised and/or external as well as local and/or remote applications; including one or more of:

[0071] An information technology platform, such as the Sentient (IMO) IT Platform illustrated in FIG. 3 and FIG. 5, comprising methods for user interactivity, applications environment and data definition and functional data and applications integration

[0072] utilizing Intelligent Objects (IMO) 200 as core components;

[0073] providing interactive, dynamically defined menus, toolbars and user interface panes presented within a unified presentation layer (UPL) 206 to enable an interactive, functionally integrated graphical user interface; and

[0074] providing integration of heterogeneous data content for analysis by internal components and access interfaces as well as components and interfaces of other external applications or devices, over a variety of local and/or distributed connectivity protocols.

[0075] Intelligent Object Handler (IOH) 202, comprising methods for one or more of:

[0076] enabling user interactivity within the Sentient IT Platform (See FIG. 5);

[0077] providing interactive, dynamically defined menus, toolbars and user interface panes presented within the unified presentation layer (UPL) 206; and

[0078] providing functional integration of corresponding components and access interfaces, which comprise data-enabling methods for handling of Intelligent Objects (IMO) 200 and their data content.

[0079] User definition and administration (UDA) 2000 interface shell component, comprising methods for one or more of:

[0080] enabling its related menus and a user interface for user definition and privilege administration presented within the unified presentation layer (UPL) 206 comprised by the Intelligent Object Handler (IOH) 202,

[0081] providing issuance and regulation of access privileges within the entity of heterogeneous data network environments for Intelligent Objects (IMO) 200.

[0082] Intelligent Object generator (IMO-G) 2002, comprising methods for one or more of:

[0083] automated generation of Intelligent Objects (IMO) 200 corresponding to newly acquired, imported, or queried data content from laboratory devices (Instrumentation) 1076 and/or heterogeneous data types; and

[0084] generation of initial Intelligent Object (IMO) 200 state history records.

[0085] Object state engine (OSE) 212 component, comprising methods for one or more of:

[0086] continuously monitoring, governing, synchronizing, recording and activating alerts for all activities of Intelligent Objects (IMO) 200 in real-time and/or within latency environments; and

[0087] synchronization with and updating of a comparable continuously running status management component (SMC) 208 or comparable component comprised within a data structure.

[0088] Object standardization technique (IMO-S) 2004, comprising methods for one or more of:

[0089] basic calibration of a variety of data content by calibration with standardized empirical criteria according to comprised algorithms; and

[0090] linking to additional components which normalize the data content, such as the object normalization engine (ONE) 210.

[0091] Object normalization engine (ONE) 210, comprising methods for one or more of:

[0092] normalization of scientific data contained in objects for comparison independent of procedural errors resulting from variation in experimental and inherent in multiple datasets of different origins.

[0093] Direct instrument acquisition and control (DIAC) 2006 interface, comprising methods for one or more of:

[0094] enabling its related menus, toolbars and user interface presented within the unified presentation layer (UPL) 206 comprised by the Intelligent Object (IMO) 200 and linked via the master query component (MQC) 2012; and

[0095] providing for remote and/or local instrument control and/or data acquisition.

[0096] Data type translator (DTT) 2008 component, comprising methods for

[0097] Defining and integrating heterogeneous data content, data types and structures as data content for Intelligent Objects (IMO) 200, without writing to the data content.

[0098] Object translation engine (OTE) 214, comprising methods for one or more of:

[0099] provision of nested vector table lookup and translation to enable required data type translation according to interactivity requirements of heterogeneous computing environments;

[0100] presentation of translated and defined data type dependencies to components which generate required representations of the data content; and

[0101] provision of varying data content access, routing and presentation protocols to components and interfaces required for functional integration of data and applications.

[0102] Application/database definition generator (ADG) 2010, comprising methods for

[0103] detection, extraction and definition of requirements for functional interaction with external applications, components, access interfaces and heterogeneous data resources.

[0104] Master query component (MQC) 2012, comprising methods for one or more of:

[0105] enabling its related menus, toolbars and user interface presented within the unified presentation layer (UPL) 206 comprised by the Intelligent Object Handler (IOH) 202,

[0106] fielding and directing automated and/or user queries and commands for data acquisition, retrieval, or analysis.

[0107] Master query interface (MQI) 218, comprising methods for one or more of:

[0108] linking, accessing and routing of bi-directional vectorized data content pointers and meta-data tags between Intelligent Objects (IMO) 200; and

[0109] directing of accessing and routing to and between linked processing components and access interfaces.

[0110] Intelligent Object handle (IMO-H) 2014 component, comprising methods for one or more of:

[0111] enabling its related menus, toolbars and user interface presented within the unified presentation layer (UPL) 206 comprised by the Intelligent Object Handler (IOH) 202 and linked via the master query component (MQC) 2012;

[0112] presentation and functional integration of the Intelligent Object (IMO) 200 data with the user interface layer and its described functionality; via activation of external

[0113] methods for dynamic updating, activation, accessing and routing of bi-directional vectorized data content pointers and meta-data tags.

[0114] Report generation interface (RGI) 220, comprising methods for one or more of:

[0115] assembly, tabulation, validation and ranking, according to information received from external processing engines and access interface components, of Intelligent Object (IMO) 200 and data content information; and

[0116] relaying of generated results to external processing engines, access interfaces and pane descriptor components.

[0117] Intelligent Object application framework (IMO-A) 2016, comprising methods for one or more of:

[0118] user-directed functional assembly and functional integration of processing components and access interfaces comprised within the Intelligent Object Handler (IOH) 202 as applications, modules or plug-ins; and optionally further comprising a component for

[0119] automated applications assembly according to dynamic, automated and/or user- directed processing requirements.

[0120] Application translation interface (ATI) 216, which comprises methods for

[0121] interface linking and translation for functional integration of applications, to provide user interactivity for Intelligent Object (IMO) 200 data within heterogeneous data and applications environments.

[0122] In an optional embodiment, a set of interaction protocols are also provided, which may include one or any combination of the following:

[0123] An IT Platform supporting the requirements of the inventive system and method, such as for example, the Sentient IT Platform illustrated in FIG. 5, comprising methods for one or more of:

[0124] using data objects other than Intelligent Objects (IMO) 200 as core components;

[0125] comprising menus, toolbars and user interface panes presented within a unified presentation layer (UPL) 206 to enable an interactive, functionally integrated graphical user interface; and

[0126] integrating internal components and access interfaces as well as components and interfaces of other external applications or devices over a variety of local and/or distributed connectivity protocols.

[0127] A data object and applications handler (IOH) 202, comprising methods for

[0128] providing a core data and applications handling framework within an IT Platform (See FIG. 3 and FIG. 4),

[0129] provision of interactive menus, toolbars and user interface panes presented within a unified presentation layer (UPL) 206; and

[0130] provision of corresponding components and access interfaces, which comprise data-enabling methods for handling of various data objects and their data content.

[0131] The following embodiments defined and described in enabling detail by minimal set of processing components and access interfaces below as well as certain optional and advantageous embodiments. Alternative embodiments may or may not have corresponding or additional processing components, access interfaces and property panes with unique, functionality-driven properties. In this exemplary embodiment, the set of property panes, processing components and their corresponding access interfaces are defined as follows.

[0132] In an advantageous and exemplary embodiment, an information technology platform architecture such as for example the “Sentient IT Platform” (See FIG. 5), as described here or in one or more of the related applications identified herein, advantageously enabled in software, comprises a unified presentation layer (UPL) 206 graphical user interface, processing components and access interfaces to enable functionally integrated user interactivity. The presentation layer, interfaces and components comprise sets of instructions for methods, processes and/or protocols including user interaction; data content definition, accessing, unified viewing, processing and routing; environment definition, accessing, unified viewing, processing and routing; to provide unified functionality within previously homogeneous and/or heterogeneous data and applications environments. The information technology platform allows for fast, efficient, functionally integrated, multidimensional accessing, routing; viewing; querying; analyzing; and other data- enabling operations via the utilization of comprised methods and/or processes including vectorized data content accessing and routing; direct information interchange between data objects; data-enabled parallel processing via organization, ranking and result generation of the information interchanged, according to Boolean and other statistical analyses; nested vector table translation; and non-destructive cache “overlay” processing.

[0133] The architecture utilizes Intelligent Objects (IMO) 200 as core accessing; routing; and processing elements; and provides a set of components and access interfaces including but not limited to definition of Intelligent Object (IMO) 200 and data content according to methods including but not limited to data object and content definition; data matrix structure definition; application requirements definition; data resource (database, data storage) definition; and preparation of Intelligent Object (IMO) 200 and data content according to methods including but not limited to data content and activity synchronization; standardization; translation; validation; ranking; automated and/or interactive data organization; cache-based non-destructive processing; analysis and presentation of Intelligent Object (IMO) 200 and data content according to methods including but not limited to direct data-to-data information interchange; vectorized accessing and routing of data content; meta-data learning and optimization; to enable fast, efficient, functionally integrated interaction of Intelligent Object (IMO) 200s within homogeneous and/or heterogeneous data and applications environments.

[0134] In an advantageous and exemplary embodiment, an Intelligent Object Handler (IOH) 202, advantageously enabled in software, comprises a unified presentation layer (UPL) 206 graphical interface, processing components and access interfaces to enable functionally integrated user interactivity. These unified presentation layer (UPL) 206, components and interfaces comprise methods not limited to Intelligent Object (IMO) 200 data as core elements, which provide methods advantageous for Intelligent Object handling, including but not limited to automated and/or interactive data and data resource access, routing, processing, translation, analytical integration, viewing, analysis and management. The Intelligent Object Handler (IOH) 202 comprises a multi-platform graphical user interface which functionally integrates plug-ins; components; modules; applications; interfaces; from sources not limited to diverse scientific; business; manufacturing; academic; manufacturing; and laboratory systems environments. The unified presentation layer (UPL) 206 provides methods advantageous for data Object Handling and analysis of data content, dynamically presented within the Handler to enable user interactivity, including but not limited to sets of customizable toolbars; user menus; and various analytical interfaces at the unified presentation layer (UPL) 206 , such as File New; Open; Open All (in directory); Close; Close All; Print preview; Print; ( . . . ); Edit; Undo; Redo; Cut; Copy; Paste; Select; Select All; as well as additional and easily extensible options for user interactivity and automated functionality.

[0135] Owing at least in part to the significant operational advantages provided by the inventive system, architecture, method, and computer program and computer program product, the structure, function, and operation of aspects of the invention are described in the context of a series of experiments so that the manner in which a scientist or other investigator would utilize and interact with the system and method are clearly set forth. Elements of various structural, methodological, and computer program facets of the invention are described in this context.

[0136] In this description, data from protein expression studies based on 2-dimensional gel electrophoresis (2DE) are complex to interpret due to the limited reproducibility of the experimental procedure, which typically does not allow for direct comparisons regarding spot position and quantity. Within the inventive intelligent object or intelligent molecular object IMO technology, such object queries can be performed in real-time at an individual spot level. The attached images of the user interface handling input/output operation between the Intelligent Objects demonstrate the effective, interactive real-time answer generation process.

[0137] Three examples are also described. “Example 1” depicts a specific embodiment of enabling code, providing instructions utilized for the exemplary embodiment of dynamic menu configuration for the Intelligent Object Handler's (IOH) main routing menu. “Example 2” depicts a specific embodiment of enabling code, providing instructions utilized in the user definition and administration (UDA) Shell. “Example 3” depicts a specific embodiment of enabling code, providing instructions utilized in the direct instrument data acquisition and control (DIAC) interface to remotely operate and/or monitor connected instrumentation in real-time. Functions such as status of the instrumentation, parameter queries, start-stop or pause-resume and the like are provided. A remote-control styled dialog and message handler are implemented.

[0138] Three examples showing specific instantiation of computer software program code are now described.

EXAMPLE 1

[0139] Example 1 shows a specific instantiation of enabling code, providing instructions utilized for the exemplary embodiment of dynamic menu configuration for the Intelligent Object Handler's (IOH) 202 main routing menu.

[0140] IMPLEMENT DYNCREATE(CMainDoc, COleDocument)

[0141] BEGIN MESSAGE_MAP(CMainDoc, COleDocument)

[0142] //((AFX MSG_MAP(CMainDoc)

[0143] ON_UPDATE_COMMAND_UI(ID_ANALYZE_STAT_SIMCLUSTER,

[0144] On UpdateAnalyzeStatSimCluster)

[0145] ON_COMMAND(ID_ANALYZE_STAT SIMCL USTER, OnAnalyzeStatSimCluster)

[0146] ON_UPDATE_COMMAND_UI(IDFILE_SAVE, OnUpdateFileSave)

[0147] ON_COMMAND(ID_VALIDA TE_RA WDA TA_INTEG, On Validate VerifyIntegrity)

[0148] ON_ UPDATE_COMMAND_UI(ID_VALIDATE_RA,WDATA_INTEG,

[0149] On Update Validate VerifyIntegrity)

[0150] //}}AFX MSG_MAP

[0151] //Enable default OLE container implementation

[0152] ON UPDATE COMMAND UI(ID EDIT PASTE,

[0153] COleDocument::On UpdatePasteMenu)

[0154] ON_UPDATE_COMMAND_UI(ID_EDIT PASTE LINK,

[0155] COle.Document:: On UpdatePasteLinkMenu′

[0156] ON_UPDATE COMMAND UI(ID_OLE EDIT CONVERT

[0157] COleDocument:: On UpdateObjectVerbMenu)

[0158] ON_COMMAND(ID_OLE_EDIT CONVERT, COleDocument::OnEditConvert)

[0159] ON_UPDATE_COMMAND_UI(IDOLE_EDIT LINKS,

[0160] COleDocument::On UpdateEditLinksMenu)

[0161] ON_COMMAND(IDOLE_EDIT LINKS, COleDocument::OnEditLinks)

[0162] ON_UPDATE_COMMAND_UI RANGE(IQOLE_VERB_FIRST,

[0163] ID_OLE_VERB_LAST, COleDocument::OnUpdateObjectVerbMenu)

[0164] END_MESSAGE-MAP(

[0165] In a typical IOH configuration, the following menus as illustrated in FIG. 11 and FIG. 12 are available: File, Edit, View, Select, Options, Control, Analyze, Query, Validate, Report, Link, User, Maintain, Window, and Help.

[0166] In FIG. 11, the menu of FIG. 10 is expanded using a menu pull-down feature. The FILE menu provides selections such as for creating, opening, closing, import or export of data; for printing, print preview or setup and to logout for user changes. The EDIT menu provides selections such as for cutting, copying, pasting, object insertion, linking and such for Undo of the last operation. The VIEW menu provides selections such as those for enabling of diverse toolbars, viewing of connections, graphical thumbnails; and such for viewing of specific lookup tables (LUTs) in individual windows such as object state, content attributes, database list, sample definitions, calibration functions and the like. The SELECT menu provides selections such as those for connection type, database or instrument integration and such to select devices for live data acquisition. The OPTIONS menu provides selections to preview individual results, aggregate results, enable distributed learning or to customize result aggregation. The CONTROL menu provides selections to control diverse instruments, cameras, imagers and for setup of experimental parameters in the analyzers or imagers. The ANALYZE menu provides selections for analytical modules, plug-ins or tools which provide content-specific analytical functions and data viewer. The QUERY menu provides selections to perform queries in form-based or graphical drag-and-drop fashion and a selection to launch a query profiler. The VALIDATE menu provides selections to verify data authenticity and integrity and to electronically sign object and raw data sets. The REPORT menu provides selections for a variety of reporting options as displayed in the example. The LINK menu provides selections to link experiments, libraries, public resources and external applications. The USER menu provides selections for user management as described for user definition and administration (UDA) 2000. The MAINTAIN menu provides selections such as those for backup, redundancy removal, manual metadata index update and performance-related parameter monitoring. The WINDOW menu provides selections such as those for arrangement of diverse windows across the main application window and a list of currently open windows. The HELP menu provides selections such as those for generic help topics, acronyms, contact, web link, check for updates and version information.

[0167] These components and access interfaces comprise methods for automated and/or interactive applications access, routing, translation, integration, viewing and management; automated and/or interactive data and data resource access, routing, processing, translation, integration, viewing, analysis and management.

[0168] The user definition and administration (UDA) 2000 component is functionally linked to a “User”menu comprised by the unified presentation layer (UPL) 206 within the Intelligent Object Handler (IOH) 202. The user definition and administration (UDA) 2000 component provides a set of instructions, advantageously enabled in software, comprising methods including bi-directional information interchange with components and access interfaces including the User menu, Intelligent Object generator (IMO-G) 2002 component; object state engine (OSE) 208 component; and master query component (MQC) 2012; and which provides a user interface and functionality to set up and govern User preferences and privileges, including but not limited to password settings; look preference; color preference; local cache size; local cache clear; import settings; auto setup; connectivity profile (peer-to-peer, client/server, etc.); database access preference; applications list; personal data storage; and global user administration including a dynamically update list of user names; a dynamically update list of user levels including; Add User; Edit User; Export User; Import User; Lock/Unlock User; Retire User; Clear User; and Set Password.

EXAMPLE 2

[0169] Example 2 shows a specific instantiation of enabling code, providing instructions utilized in the user definition and administration (UDA) 2000 Shell. A process provides arrays for connection, user access tracking, logging and displaying.

{
CPlatformApp* app = (CPlatformApp*)AfxGetApp();
TCHAR computer_name[MAX_COMPUTERNAME_LENGTH + 1] = {0};
DWORD size = MAX_COMPUTERNAME_LENGTH + 1;,
GetComputerName(computer_name, &size);
CONNECTEDUSERS cu = {0};
_tcscpy(cu.szComputerName, computer_name);
_tcscpy(cu.szName, app->m_stUser.szName);
_tcscpy(cu.szSessionID, app->m_stUser.szSessionID);
_tcscpy(cu.szIpAddress, app->m_strHostIp);
cu.uuid = app->m_stUser.uuid;
cu.timeLoginTime = app->m_stUser.timeLoginTime;
m_arrayConnectedUsers.Add(cu); // add to list
for(int i = 0; i < 3; i++) // write to file
{
CONNECTEDUSERS tmp_cu = {0};
key.Format(fmt, i,);
GetPrivateProfileStruct(_T(“Connection”), key, &tmp_cu, sizeof(tmp_cu),fileName);
if(_tcslen(tmp_cu.szSessionID) == 0)
{
WritePrivateProfileStruct(_T(“Connection”), key, &cu, sizeof(cu),fileName);
break;
}
}

[0170] The User Definition and Administration (UDA) shell provides dialog-based tools to add, edit, export, import, lock, unlock, retire user or to clear or request renewal of user passwords.

BEGIN_MESSAGE_MAP(CAdministrationDlg, CDialog)
//{{AFX_MSG_MAP(CAdministrationDlg)
ON_NOTIFY(LVN_ITEMCHANGED, IDC_USERLIST, OnItemChangedUserList)
ON_BN_CLICKED(IDC_CLEARPASSWORD, On ClearPassword)
ON_BN_CLICKED(IDC_EDITUSER, OnEditUser)
ON_BN_CLICKED(IDC_DELETEUSER, OnDeleteUser)
ON_BN_CLICKED(IDC_ADDUSER, OnAddUser)
ON_BN_CLICKED(IDC_LOCKUSER, OnLockUser)
ON_BN_CLICKED(IDC_SHOWACTIVE, OnShowActive)
ON_BN_CLICKED(IDC_SHOWALL, OnShowAll)
ON_BN_CLICKED(IDC_SHOWINACTIVE, OnShowInactive)
ON_BN_CLICKED(IDC_EXPORTUSER, OnExportUser)
ON_BN_CLICKED(IDC_IMPORTUSER, OnImportUser)
//}}AFX_MSG_MAP
END_MESSAGE_MAP()
.....
void CAdministrationDlg::InitUserList()
{
m_listUser.DeleteAllItems();
m_listUser.DeleteColumn(5);
m_listUser.DeleteColumn(4);
m_listUser.DeleteColumn(3);
m_listUser.DeleteColumn(2);
m_listUser.DeleteColumn(1);
m_listUser.DeleteColumn(0);
DWORD flags = m_listUser.GetExtendedStyle();
m_listUser.SetExtendedStyle(flags | LVS_EX_FULLROWSELECT | LVS_EX_GRIDLINES);
m_listUser.InsertColumn(0, _T(“User”), LVCFMT_LEFT);
m_listUser.InsertColumn(1, _T(“Level”), LVCFMT_LEFT);
m_listUser.InsertColumn(2, _T(“Group”), LVCFMT_LEFT);
m_listUser.InsertColumn(3, _T(“Status”), LVCFMT_LEFT);
m_listUser.InsertColumn(4, _T(“Creation”), LVCFMT_LEFT);
m_listUser.InsertColumn(5, _T(“Termination”), LVCFMT_LEFT);
m_listUser.SetColumnWidth(0, LVSCW_AUTOSIZE_USEHEADER);
m_listUser.SetColumnWidth(1, LVSCW_AUTOSIZE_USEHEADER);
m_listUser.SetColumnWidth(2, LVSCW_AUTOSIZE_USEHEADER,);
m_IistUser.SetColumnWidth(3, LVSCW_AUTOSIZE_USEHEADER);
m_listUser.SetColumnWidth(4, LVSCW_AUTOSIZE_USEHEADER),
m_listUser.SetColumnWidth(5, LVSCW_AUTOSIZE_USEHEADER);
int txt_width = 0;
int col_width = 0;
for(int i = 0; i < m_arrayUsers.GetSize(); i++)
{
if((m_nShowUsers == SHOWUSERS_ACTIVE) && (m_arrayUsers[i].byteStatus !=
USERSTATUS_ACTIVE) ||
(m_nShowUsers == SHOWUSERS_INACTIVE) && (m_arrayUsers[i].byteStatus ==
USERSTATUS_ACTIVE))
continue;
int index = m_listUser.InsertItem(i, m_arrayUsers[i].szUser);
m_listUser.SetItemData(index, i);
txt_width = m_listUser.GetStringWidth(m_arrayUsers[i].szUser) + 15;
col_width = m_listUser.GetColumnWidth(0);
if(txt_width > col_width) m_listUser.SetColumnWidth(0, txt_width);
CString str = _T(“”);
switch(m_arrayUsers[i].byteLevel)
{
case 1: str = _T(“Assistant”); break;
case 2: str = _T(“Technician”); break;
case 3: str = _T(“Researcher”); break;
case 4: str = _T(“Validator”); break;
case 5: str = _T(“Chief”); break;
case 8: str = _T(“Department Head”); break;
case 16: str = _T(“Maintenance”); break;
case 20: str = _T(“Internal Technical Support”); break;
case 32: str = _T(“Administrator”); break;
case 64: str = _T(“Super User”); break;
default: ASSERT(FALSE);
}
m_listUser.SetItem(index, 1, LVIF_TEXT, str, 0, 0, 0, 0);
txt_width = m_listUser.GetStringWidth(str) + 15;
col_width = m_listUser.GetColumn Width(1);
if(txt_width > col_width) m_listUser.SetColumnWidth(1, txt_width);
switch(m_arrayUsers[i].byteType)
{
case 1: str = _T(“Administration”); break;
case 2: str = _T(“Finance”); break;
case 3: str = _T(“Human Resources”); break;
case 4: str = _T(“Inventory”); break;
case 5: str = _T(“Logistics”); break;
case 6: str = _T(“Management”); break;
case 7: str = _T(“Marketing”); break;
case 8: str = _T(“Production”); break;
case 9: str = _T(“Purchasing”); break;
case 10: str = _T(“Regulatoty Compliance”); break;
case 11: str = _T(“Research & Development”); break;
case 12: str = _T(“Quality Control / QA”); break;
default: ASSERT(FALSE);
}
m_listUser.SetItem(index, 2, LVIF_TEXT, str, 0, 0, 0, 0);
txt_width = m_listUser.GetStringWidth(str) + 15;
col_width = m_listUser.GetColumnWidth(2);
if(txt_width > col_width) m_listUser.SetColumnWidth(2, txt_width);
switch(m_arrayUsers[i].byteStatus)
{
case 0: str = _T(“Locked”); break;
case 1: str = _T(“Active”); break;
case 255: str = _T(“Retired”); break;
default: ASSERT(FALSE);
}
m_listUser.SetItem(index, 3, LVIF_TEXT str, 0, 0, 0, 0);
txt_width = m_listUser.GetStringWidth(str) + 15;
col_width = m_listUser.GetColumnWidth(3);
if(txt_width > col_width) m_listUser.SetColumnWidth(3, txt_width);
if(m_arrayUsers[i].timeCreation > 0)
{
CTime t(m_arrayUsers[i].timeCreation);
str = t.Format(“%B %d, %Y”);
m_listUser.SetItem(index, 4, LVIF_TEXT, str, 0, 0, 0, 0);
txt_width = m_listUser.GetStringWidth(str) + 15;
col_width = m_listUser.GetColumnWidth(4);
if(txt_width > col_width) m_listUser.SetColumnWidth(4, txt_width);
}
if(m_arrayUsers[i].timeTermination > 0)
{
CTime t(m_arrayUsers[i].timeTermination);
str = t.Format(“%B %d, %Y”);
m_list User.SetItem(index, 5, LVIF_TEXT, str, 0, 0, 0, 0);
txt_width = m_listUser.GetStringWidth(str) + 15;
col_width = m_listUser.GetColumnWidth(5);
if(txt_width > col_width) m_listUser.SetColumnWidth(5, txt_width);
}
}
m_nCurListIndex = 0;
m_listUser.SetItemState(m_nCurListIndex, LVIS_SELECTED, LVIS_SELECTED);
}

[0171] Subsequently, the user definition and administration (UDA) 2000 shell component also handles user-selective preference setting. An example of such preferences, the output selection for a specific user profile is listed below.

BEGIN_MESSAGE_MAP(CPreferenceDlg, CDialog)
//{{AFX_MSG_MAP(CPreferenceDlg)
ON_BN_CLICKED(IDC_OUTPUT_BROADCAST,
OnOutputBroadcast)
ON_BN_CLICKED(IDC_OUTPUT_FILELOCAL,
OnOutputFileLocal)
ON_BN_CLICKED(IDC_OUTPUT_FILEPRINT,
OnOutputFilePrint)
ON_BN_CLICKED(IDC_OUTPUT_PRINTER,
OnOutputPrinter)
ON_BN_CLICKED(IDC_OUTPUT_SCREEN,
OnOutputScreen)
//}}AFX_MSG_MAP
END_MESSAGE_MAP()

[0172] Additionally, the user definition and administration (UDA) 2000 shell component provides a unified environment for user interactivity, importation and/or information entry regarding access and user privileges for local and/or remote data sources; applications; and other user activities within heterogeneous and/or homogeneous computing and/or network information environments.

[0173] A master query component (MQC) 2012 comprises methods including bi-directional information interchange with components and access interfaces including the unified presentation layer (UPL) 206, including but not limited to menus; toolbars; and query interfaces; object state engine (OSE) 208 component; Intelligent Object handle (IMO-H) 2014 component; Intelligent Object application framework (IMO-A) 2016 component; master query interface (MQD) 218; direct instrument acquisition and control (DIAC) 2006 interface; and object translation engine (OTE) 214. The Master Query component presents externally defined security, access and interactivity protocols to the appropriate menus, toolbars and/or other elements comprised within the unified presentation layer (UPL) 206; and fields and directs automated and/or user-directed queries and commands, including but not limited to data acquisition; retrieval; viewing, and/or analysis.

[0174] An Intelligent Object generator (IMO-G) 2002 (IMO-G) component comprises methods including bi-directional information interchange with components and access interfaces including the user definition and administration (UDA) 2000 component; direct instrument acquisition and control (DIAC) 2006 component; object state engine (OSE) 208 component; and data type translator (DTT) 2008 component. The Intelligent Object generator (IMO-G) 2002 interacts with the data type translator (DTT) 2008 component to automate transformation of heterogeneous data sources and types into Intelligent Object (IMO) 200 data in real-time. Additionally, the Intelligent Object generator (IMO-G) 2002 interacts with such as the user definition and administration (UDA) 2000 shell, the unified presentation layer (UPL) 206 and the Object State engine to field such as data import requests; user-based queries and/or commands; and/or automated queries provided by components and access interfaces, and to dynamically generate Intelligent Objects (IMO) 200 based on fielded requirements and available data resources. Simultaneously, this Intelligent Object generator (IMO-G) 2002 activates and updates the object state history via the object state engine (OSE) 208.

[0175] An exemplary embodiment of an object state history comprised of time-sequential set of object activity records is depicted in Table I. The table represents an embodiment of the object state history, comprising an object activity record. A typical record is shown from data object creation prior to data acquisition from an analytical instrument, several steps of calibrated analysis carried out by different users within and outside the local network. Note, that same state codes can occur within the object state history for different users, for example, output requests and the like.

[0176] With reference to FIG. 6, there is illustrated an embodiment of an object state engine (OSE). The central element of the object state engine is the active listening process (ALM), an processing thread or set of threads that is “always-on” or nearly always on, that is, running whenever the host machine is active. (Some non-on time may be provided for maintenance, power-savings, or according to some other rules or policies.) The object state engine governs activity on the object data level, via interaction with the status management component contained within an external Intelligent Object.

[0177] In FIG. 6, the two state processing elements are query state processing and object access processing, which handle Intelligent Object root addressing and interactive content routing, object-to-object interaction states, data information interchange definitions and workspace vector assignment. Object state processing includes storage of current state, history update functions, assignment of GLP/GMP-compliance via lookup table and ranking based on validation assessments. The outer pane represents the universal presentation layer (UPL), which contains non-time critical components for I/O operation and utilizes the state provided from the OSE for tasking. Object creation processes are only triggered by the OSE, but may be carried out within UPL for specific tasking such as user entry of ownership terms, or the like.

TABLE 1
depicts an embodiment of an object state history, comprised of time-
sequential set of object activity records.
Ob-
ject: User/ Net-
State level work Date/time stamp (Explanation)
000 RAS/05 00220 12/20/2000 14:33:05 (object created)
011 WUD/02 00220 12/20/2000 14:33:07 (data: acquisition in
progress)
014 WUD/02 00220 12/20/2000 16:53:07 (data: acquisition
completed)
022 WUD/02 00220 12/20/2000 16:55:22 (data: matrix defined)
056 GOT/03 00220 12/21/2000 08:00:57 (image: dynam. range
verified)
052 GOT/03 00220 12/21/2000 08:01:46 (image: fluoresc.
intens. calib.)
041 GOT/03 00220 12/21/2000 08:16:31 (bio: quantitation
calib.)
061 GOT/03 00220 12/21/2000 08:18:58 (image: origin calib.)
062 GOT/03 00220 12/21/2000 08:20:25 (image: size x calib.)
063 GOT/03 00220 12/21/2000 08:23:19 (image: size y calib.)
101 GOT/03 00220 12/21/2000 08:25:44 (std/norm: detection
threshold)
164 GOT/03 00220 12/21/2000 08:41:12 (std/norm:
measurement x)
165 GOT/03 00220 12/21/2000 08:45:30 (std/norm:
measurement y)
901 KRE/05 00080 12/21/2000 08:45:31 (access denied)
911 AAH/02 04092 12/21/2000 08:45:44 (user: access to object
granted)
071 AAH/02 04092 12/21/2000 08:45:50 (anno: descript. text)
024 GOT/03 00220 12/21/2000 08:52:12 (data: vector defined)
911 BLD/03 00693 12/21/2000 09:02:36 (user: access to object
granted)
073 BLD/03 00693 12/21/2000 09:02:39 (anno: AA protein
sequence)
045 GOT/03 00220 12/21/2000 09:14:08 (bio: immunol.
activity)
046 GOT/03 00220 12/21/2000 09:39:41 (bio: other bio-
activity)
410 GOT/03 00220 12/21/2000 09:42:31 (output: numerical
output)
411 GOT/03 00220 12/21/2000 09:44:07 (output: graphical
output)
430 GOT/03 00220 12/21/2000 09:42:31 (output: printed)
. . .

[0178] The object state engine 208 (OSE) comprises methods including bi-directional information interchange with components and access interfaces including the Status Management Components comprised by Intelligent Objects (IMO) 200; master query component (MQC) 2012; Intelligent Object generator (IMO-G) 2002; Intelligent Object standardization component; object and image normalization components; object translation engine (OTE) 214 component; data type translator (DTT) 2008 component; direct instrument acquisition and control (DIAC) 2006 interface; and legacy synchronization interface (LSI) 2018.

[0179] The object state engine (OSE) 208 provides continuously-running (always-on) sets of processes, or activity listening mode (ALM) which enable creation and identification, monitoring, recordation, governing, synchronization, validation and alerting activities for Intelligent Objects (IMO) 200 in real-time and/or within latency environments.

[0180] The object state engine (OSE) 208 comprises methods for active listening (activity listening mode - ALM) 2028; state processing (State Processing) 2030; query processing (Query Processing) 2032; and access processing (Access Processing) 2034.

[0181] Initially, the object state engine (OSE) 208 comprises methods for triggering the creation (Object Creation) 2024 of a new Intelligent Object (IMO) 200 via the Intelligent Object generator (IMO-G) 2002 and assigning a unique identifier to it (UID Assignment) 2026.

[0182] The object state engine (OSE) 208 comprises state processing (State Processing) 2030 methods such as recording Intelligent Object (IMO) 200 activity or transaction to provide activity history (State Memory) 2036; assigning a defined state to the Intelligent Object (IMO) 200 to synchronize the current action (Update History) 2038; and in advantageous embodiments, relating the activity history to GLP/GMP-compliant data states (G*P Assignment) 2040; and providing a validation state-based information ranking component (G*P Ranking) 2042. Additionally, the object state engine (OSE) 208 may provide status memory over state-less networks by transmitting action consequences back to the backend system.

[0183] The object state engine (OSE) 208 also comprises query processing (Query Processing) 2032 methods such as handling of network requests (Network Request) 2050 and external query submissions (External Submission) 2046 to the Intelligent Object (IMO) 200; governing query access (User Access Privilege) 2048 and output generation (Output Generation) 2054 according to provided user access privileges; providing query status updating (Query Status Update) 2044; and providing query result synchronization (Result Synchronization) 2052.

[0184] The object state engine (OSE) 208 also comprises access processing (Access Processing) 2034 methods such as Intelligent Object root and data content addressing and routing (Object Routing) 2056; Intelligent Object-to-Intelligent Object linking and synchronization (Object: Object) 2058; state-related vector definition of object data subsets for dynamic information interchange (DII Definition) 2060; and synchronized accessing to raw data matrix vectors (RDM Vectors) 2062.

[0185] An object standardization technique (IMO-S) 2004 comprises methods including bi-directional information interchange with components and access interfaces including the object state engine (OSE) 208; object normalization engine (ONE) 210 component; global image normalization component; and object translation engine (OTE) 214. The object standardization technique (IMO-S) 2004 activates and interacts with these components to provide automated standardization; and normalization of data; by methods including calibration by standardized empirical criteria; calibration functions including but not limited to linear; non-linear; polynomial; exponential; logarithmic; cubic spline; adaptive; weighted point-to-point fit; and a variety of multi-parametric functions.

[0186] An object normalization engine (ONE) 210 component comprises methods including bi-directional information interchange with components and access interfaces including the object state engine (OSE) 208 and the object standardization technique (IMO-S) 2004 component. The object normalization engine (ONE) 210 component provides methods, protocols and processing components which normalize scientific data contained in objects for comparison independent of procedural errors. These methods allow for accurate and precise comparison by eliminating the variability due to multiple sources of errors in the process of performing experiments and inherent in multiple datasets of different origins.

[0187] These methods, protocols and processing components comprise automated and/or event-driven processes and algorithms which generate a normalized global standard to provide algorithms to which all similar data can be referenced to in regard to their field parameters contained within the raw data matrix; apply these algorithms to user-defined workspaces addressed by dynamically generated vector subsets to minimize data exchange and increase processing speed significantly, allowing for use of these algorithm even in network environments with limited data exchange capabilities; utilize a workspace cache area for this processing to maintain data content integrity at all times; provide algorithms for processing a variety of scientific data configurations such as timeline-related; spectra or wavelength-related; kinetics-related; migration- or separation-related data content matrices in single and multidimensional variations; locational deviations within arrays, bioassay-related and gene and/or protein sequence-related raw data matrices; multi-parameter normalization in respect to color, intensity, dynamic range and x/y/z distortions in 2D and 3D scientific images; x/y/z-alignment and component distance adjustments in molecular structures; and acoustic wave pattern and/or video signals.

[0188] Another aspect of the object normalization engine (ONE) 210 provides a component comprised of one or several algorithms which detect non-obvious data redundancies in diverse data resources, databases, data marts or data warehouses; and eliminate or otherwise retire such multiple records. In another aspect of the object normalization engine (ONE) 210, algorithms are applied to subsets of decompressed workspaces within loss-free compressed raw data providing normalization to compressed data without the need for decompression of the entity of such data sets. In yet another aspect of the object normalization engine (ONE) 210, algorithms are used to track deviations from an established global standard; and to correct them in real-time for use in calibrated on-the-fly analysis applications. The object normalization engine (ONE) 210 also provides means for saving or transferring workspace cache area data converted by these algorithms between applications.

[0189] A direct instrument acquisition and control (DIAC) 2006 comprises methods including bi-directional information interchange with components and access interfaces including but not limited to the Master Query; Intelligent Object generator (IMO-G) 2002; object state engine (OSE) 208 component and external instruments and devices. The direct instrument acquisition and control (DIAC) 2006 interface comprises methods including automated detection and/or user definition of instrument and device dependencies, parameters, and/or operational method definitions; definition and functional integration of dependencies, parameters, and/or operational method definitions for interactive remote and/or local user interactivity and instrument control; an Instrument Control comprised by the unified presentation layer (UPL) 206, which presents information including but not limited to Connection status; such as presence or absence of connection; connection type information; instrument activity information such as run-time-hours, minutes, seconds; experiment status information such as validation status; instrument status information such as various operating parameters; and user interactivity such as start, pause, resume, stop; and which enables the acquisition of data content via instrumentation; and the generation of Intelligent Objects (IMO) 200 corresponding to data content.

EXAMPLE 3

[0190] Example 3 shows a specific instantiation of enabling code, providing instructions utilized in the direct instrument acquisition and control (DIAC) 2006 interface to remotely operate and/or monitor connected instrumentation in real-time. Functions such as status of the instrumentation, parameter queries, start-stop or pause-resume and the like are provided. A remote-control styled dialog and message handler are implemented.

// RemoteDlg dialog
RemoteDlg::RemoteDlg(CWnd* pParent /*=NULL*/)
:CDialog(RemoteDlg::IDD, pParent)
{
//{{AFX_DATA_INIT(RemoteDlg)
//}}AFX_DATA_INIT
}
void RemoteDlg::DoDataExchange(CDataExchange* pDX)
{
CDialog::DoDataExchange(pDX);
//{{(AFX_DATA_MAP(RemoteDlg)
//}}AFX_DATA_MAP
}
BEGIN_MESSAGE_MAP(RemoteDlg, CDialog)
//{{AFX_MSG_MAP(RemoteDlg)
ON_COMMAND(ID_SELECT_ANALYZEINTEG_REMOTE,
OnSelectAnalyzeIntegRemote)
//}}AFX_MSG_MAP
END_MESSAGE_MAP()
// RemoteDlg message handlers
void RemoteDlg::OnSelectAnalyzeIntegRemote()
{
....
}

[0191] The direct instrument acquisition and control (DIAC) 2006 interface provides linking of user-defined and/or automatically detected instrument and/or device dependencies with the instrument control user interface; real-time, pre-programmed and/or latent viewing and interactivity from local and/or remote locations; and recordation of experimental and instrument running parameters via the object state engine (OSE) 208.

[0192] A data type translator (DTT) 2008 component is comprised within the Intelligent Object Handler (IOH) 202, comprising methods including bi-directional information interchange with components and access interfaces including the Intelligent Object generator (IMO-G) 2002; object translation engine (OTE) 214 component and application framework component. The data type translator (DTT) 2008 provides methods to field applications and database environment definitions provided by an application/database definition generator (ADG) 2010 interface; and define data type dependencies as required for components and access interfaces including the Intelligent Object generator (IMO-G) 2002, application framework and object translation engine (OTE) 214.

[0193] With respect to FIG. 7, there is shown an embodiment of object translation engine (OTE) showing its relationships to external databases and to certain required and optional components and access interfaces comprised within the Intelligent Object Handler. The object translation engine interacts with an application/database generator (ADG) 2010 and master query component (MQC) 2012 to provide Intelligent Object translation and functional integration with heterogeneous applications and data resource back-ends. An alternative embodiment of OTE is illustrated in FIG. 8.

[0194] The object translation engine (OTE) 214 component comprises methods including bi- directional information interchange with components and access interfaces including the master query component (MQC) 2012; object state engine (OSE) 208 component; data type translator (DTT) 2008 component; application/database definition generator (ADG) 2010 and master query interface (MQI) 218. The object translation engine (OTE) 214 component also provides methods, protocols and processing components required to enable dynamic, automated translation of previously heterogeneous and/or incompatible data into data types; structures formats; matrices; and various data content access and routing protocols required for functional integration including but not limited to heterogeneous and/or dynamically defined query, viewing or analysis protocols; processing components; access interfaces; data resources; and/or applications environments. Additionally, the object translation engine (OTE) 214 comprises automated and/or event-driven processes, protocols and algorithms including but not limited to data object, data field and raw data matrix structure definition tables; data structure information for non-object data; data type, access and structure definition tables; database type, access and structure definition tables; application type, access and structure definition tables; table lookup to provide real-time translation of the Intelligent Object (IMO) 200 within heterogeneous database and application environments; and linking of structure information and definition tables to dynamically direct Intelligent Object property pane activation and presentation (Property Panes) 1000; data object activation and presentation; data content activation and presentation; application activation and presentation; component activation and presentation; and interface activation and presentation; in real-time, according to defined data structure; database; and application requirements.

[0195] An application/database definition generator (ADG) 2010 component comprises methods including bi-directional information interchange with components and access interfaces including the object translation engine (OTE) 214; Intelligent Object application framework (IMO-A) 2016; application translation interface (Am 216; external data content; databases and data resources; external applications and components. The application/database definition generator (ADG) 2010 enables the detection of structural and functional information necessary for standardization of non-object data; and for the presentation of standardized Intelligent Object (IMO) 200 data for analysis within dynamically defined analytical environments. The application/database definition generator (ADG) 2010 also comprises and provides methods including the: extraction interface to diverse data object, data field and raw data matrix definitions and activation of external components for meta-data extraction; extraction interface to diverse data type, access, structure and functional dependencies; extraction interface to diverse database type, access and structure dependencies; extraction interface to diverse application type, access and structure dependencies; Additionally, the application/database definition generator (ADG) 2010 automates the query of all application and database requirements according to automated and/or user-defined requirements utilizing methods including data table extraction to determine data object, data field and raw data matrix definitions; data type extraction to determine data access and structure dependencies for Intelligent Objects (IMO) 200; database type extraction to determine database access and structure dependencies; application type extraction to determine application type, access and structure; Finally, the application/database definition generator (ADG) 2010 provides table definitions for look-up to provide real-time translation of Intelligent Object (IMO) 200 meta-data and data content between and within heterogeneous computing environments and defines the computing environment for components and access interfaces including the data type translator (DTT) 2008, the application framework and the application translation interface (ATI) 216.

[0196] A master query interface (MQI) 218 comprises methods including bi-directional information interchange with components and access interfaces including the master query component (MQC) 2012; object translation; Intelligent Object handle (IMO-H) 2014 component; external object query interfaces comprised by Intelligent Objects (IMO) 200; components and/or access interfaces comprised by an external Intelligent Object Pool (IOP) 204; an external result aggregation engine; and various data resources. Additionally, the master query interface (MQI) 218 comprises methods including linking of Intelligent Object (IMO) 200 root routing information comprised within external unique object identifier interfaces; linking of components and access interfaces to direct interactive content routing provided by components comprised within external unique object identifier interfaces; linking of components and access interfaces to aggregated query result output provided by external result aggregation engines; linking components and access interfaces to other external components and access interfaces for query processing, such as but not limited to distributed learning engines; and knowledge extraction engines.

[0197] An Intelligent Object handle (IMO-H) 2014 component comprises methods including bi-directional information interchange with components and access interfaces including the master query component (MQC) 2012 ; master query interface (MQI) 218; Intelligent Object application framework (IMO-A) 2016 component; and a report generation interface (RGI) 220. The Intelligent Object handle (IMO-H) 2014 component enables management of Intelligent Object (IMO) 200 data by activating information linking and directing information provided by components and access interfaces, including but not limited to data content attribute definitions; meta-data tags; and address vector pointers; comprised by Intelligent Objects (IMO) 200, according to query and/or command parameters fielded by automated; and/or user-based methods.

[0198] A report generation interface (RGI) 220 comprises methods including bi-directional information interchange with components and access interfaces including the Intelligent Object handle (IMO-H) 2014 component; object translation engine (OTE) 214; distributed learning engines; knowledge extraction engines; and an external result aggregation engine component. The report generation interface (RGI) 220 comprising methods for assembly, tabulation, validation and ranking, according to information received from external processing engines and access interface components, of data content including data objects; specified meta-data indices of the Intelligent Object (IMO) 200 data and data content; and specified data content subsets; defined to levels of granularity as small as a single byte. Additionally, the report generation interface (RGI) 220 relays generated results to external processing engines, access interfaces and pane descriptor components in an automated, synchronized, real-time manner.

[0199] An Intelligent Object application framework (IMO-A) 2016 comprises methods including bi-directional information interchange with components and access interfaces including the master query component (MQC) 2012; data type translator (DTT) 2008 component; Application/Database Definition Generator; Intelligent Object handle (IMO-H) 2014; application translation interface (ATI) 216; Intelligent Objects (IMO) 200 and their content; and the Intelligent Object Pool (IOP) 204; applications comprised within the Intelligent Object Handler (IOH) 202 via modules and/or plug-ins, access interfaces, and processing components. The application framework provides methods including but not limited to fielding of automated and/or user-directed queries; applications assembly commands; processing requests; viewing requests; and other dynamic applications needs, and provides methods including but not limited to; detection; assembly; activation; synchronization and functional integration of required components, interfaces and protocols to enable assembly of unified applications; and activation of a comprised component for automated applications assembly within homogeneous and/or heterogeneous data resources; applications; access interfaces; and processing components environments.

[0200] The component for automated applications assembly comprised by the Intelligent Object application framework (IMO-A) 2016 enables automated assembly of new applications during run-time (“just-in-time”) from sets of components according to specific needs and best suited for complex processing requirements in heterogeneous data and applications environments.

[0201] The automated applications assembly component comprises methods for selection and combination of required I/O components, such as components required to transfer data into and results out of individual analytical and/or descriptive and/or annotative components; selection of algorithms best suited for processing of specifically defined data types or data type descriptors; dynamic combination of these components and algorithms towards automated and/or user-defined analytical performance goals, utilizing distributed subcomponent integration under best-fit conditions; activation of required components, interfaces and protocols to enable functionally integrated analysis utilizing homogeneous and/or heterogeneous data content and applications; synchronization of required components, interfaces and protocols to enable functionally integrated analysis utilizing homogeneous and/or heterogeneous data content and applications; assembly of required components, interfaces and protocols to enable functionally integrated analysis utilizing homogeneous and/or heterogeneous data content and applications memory ranking of performance-optimized component selection; memory ranking of information-optimized component selection; and best choice adjustment according to user-defined functional requirements.

[0202] In addition to its embodiment as comprised by the Intelligent Object application framework (IMO-A) 2016, the automated applications assembly component may be contained in a stand-alone application or module for non-object data; in a stand-alone application or module for object data; or as a plug-in or module for an information technology platform containing Intelligent Object data. The automated applications assembly component may comprise further methods for selection of components based on their functional consistency and accuracy within all components assembled, such as, but not limited to functions for governing raw data precision; handling of mathematical errors; provision of data pointer referencing; matrix operation synchronization in regard to internal or external transformations and dimension descriptions; output rounding; determination of logical processing pathways; accounting for Boolean inheritances; iterative step trace-ing; and controlling and logging of rollback behavior; selection of components based on their immediate availability for real-time use; selection of components is based on the ranking among available components in regard to overall performance, such as, but not limited to: network traffic; local processing; remote processing; process sharing; distributed processing; direct “on-object”-processing; result clustering; and graphics element preprocessing and charting; selection of components based on the ranking among available components in regard to validation required for decisive answers (output knowledge assessment).

[0203] Additionally, the automated applications assembly component may comprise further methods for provision of a vectorized “Application Archive Table” for quick referencing of previously assembled applications with similar processing needs; provision of “on-the-fly”temporary applications memory management for Just-in-Time (JIT) component linking, loading and unloading from the active caching area. The automated applications assembly component may also comprise further methods for provision of an intuitive interactive graphical user interface for drag-&-drop selection of components for process modeling and analytical simulations based on user output requests. The automated applications assembly component may also comprise further methods for provision of active communication with learning engines, such as for example, a distributed learning engine or knowledge extraction engine to optimize iterative processes or loop algorithms based on condition feedback.

[0204] An application translation interface (ATI) 216 comprises methods including bi-directional information interchange with components and access interfaces including the application/database definition generator (ADG) 2010; application framework; external result aggregation engine; and including but not limited to external data resources; applications; access interfaces; and processing components. The application translation interface (ATI) 216 comprises and provides methods including the; interface layer to present defined data object, data field and raw data matrix structure definitions utilizing provided definition look-up tables; interface layer to present defined data type, access, structure and function definitions, via provided look-up tables; interface layer to present defined database type, access, structure and function definitions provided via look-up tables; interface layer to present defined application type, access and structure definitions provided via look-up tables; transferring of requests such as read/write processes within or in-between external applications; Intelligent Object (IMO) 200 and data content property presentation in real-time, according to defined requirements.

[0205] A legacy synchronization interface (LSI) 2018 comprises methods including bi-directional information interchange with components and access interfaces including the object state engine (OSE) 208; and external data content, databases, and data resources. Additionally, the legacy synchronization interface (LSI) 2018 provides comprised components, and interfaces to synchronize object data of various types with other data contained in off-line and/or batch processing legacy databases or external applications; synchronize Intelligent Object (IMO) 200 data with other data contained in off-line and/or batch processing legacy databases or external applications in regard to their integrity, content and state; and to synchronize Intelligent Object (IMO) 200 data content with external, off-line or temporarily unavailable data sets, including but not limited to raw data vector matrices linking; and property pane updating . In another aspect, the legacy synchronization interface (LSI) 2018 reports to the object state engine (OSE) 208 to update state history records for changes during times where activity-listening-mode is temporarily unavailable under conditions, such as, but not restricted to off-line; connection time-out; transaction acknowledgement errors; and/or record locking conflicts on the legacy end. In another aspect, the legacy synchronization interface (LSI) 2018 comprises methods for metadata index updating in batch mode; and for Intelligent Object (IMO) 200 object pane descriptor (OPD) 1024 updating whenever object property panes are added or descriptors need to be modified; by relaying required information to the object state engine (OSE) 208 component. This may for example, be any OPD interface, such as an external OPD interface described with greater particularity relative to exemplary IMO. In another aspect, the legacy synchronization interface (LSI) 2018 provides link functions between “local state machines” and the object state engine (OSE) 208 component to enable real-time synchronous handshaking during connect and disconnect of heterogeneous legacy data and/or applications; transaction management and accounting for such as “once-and-only-once” transactions; linking between “local state machines” and components within the unified presentation layer (UPL) 206 of the Intelligent Object Handler (IOH) 202; to enable real-time platform-integration of external applications, which modify data properties during their execution, for synchronization and update. The described legacy synchronization interface (LSI) 2018 also contains a component which provides feedback on synchronization conditions including but not limited to frequency; updates; and timing preferences towards a variety of internally and/or externally comprised components and interfaces, such as knowledge extraction engines; and distributed learning engines; and for automated synchronization and optimization based on event histories. The legacy synchronization interface (LSI) 2018 also contains a component, which provides logging and reporting of synchronization events to methods comprised within such as Intelligent Objects (IMO) 200; processing components; access interfaces; applications; data resources and/or databases; and which provides the interface to integrate required methods to automatically request synchronization and/or metadata index updates based on provided instructions including protocols and definitions such as user preferences; user profiles; administrative; and/or maintenance actions.

[0206] In an optional embodiment, an information technology platform architecture advantageously enabled in software comprises a unified presentation layer (UPL) 206 graphical user interface, processing components and access interfaces to enable functionally integrated user interactivity. The presentation layer, interfaces and components comprising sets of instructions for methods, processes and/or protocols not limited to user interaction; data content definition, accessing, unified viewing, processing and routing; environment definition, accessing, unified viewing, processing and routing; for homogeneous and/or heterogeneous data and applications environments. The information technology platform allows for fast, efficient, functionally integrated, multidimensional accessing, routing; viewing; querying; analyzing; and other data- enabling operations via the utilization of comprised methods and/or processes including data- enabled parallel processing; via vectorized data content accessing and routing; direct information interchange between data objects; organization, ranking and comparison of data according to Boolean and other statistical analyses of the information interchanged; nested vector table translation; and non-destructive cache “overlay” processing. The architecture utilizes a variety of data objects as core accessing; routing; and processing elements; and providing a set of components and access interfaces including but not limited to definition of the data object and data content according to methods including but not limited to data object and content definition; data matrix structure definition; application requirements definition; data resource (database, data storage) definition; and preparation of the data object and data content according to methods including but not limited to data content and activity synchronization; standardization; translation; validation; ranking; automated and/or interactive data organization; cache-based non- destructive processing; analysis and presentation of the data object and data content according to methods including but not limited to direct data-to-data information interchange; vectorized accessing and routing of data content; meta-data learning and optimization; to enable fast, efficient, functionally integrated interaction of data objects within homogeneous and/or heterogeneous data and applications environments.

[0207] In an optional embodiment, a data object Handler comprises a unified presentation layer (UPL) 206 graphical interface advantageously enabled in software, utilizing processing components and access interfaces to enable functionally integrated user interactivity. The unified presentation layer (UPL) 206, components and interfaces comprising methods not limited to Intelligent Object (IMO) 200 data as core elements, which provide methods advantageous for data object handling, including but not limited to automated and/or interactive data and data resource access, routing, processing, translation, analytical integration, viewing, analysis and management. A multi-platform graphical user interface which functionally integrates plug-ins; components; modules; applications; interfaces; from sources not limited to diverse scientific; business; manufacturing; academic; manufacturing; and laboratory systems environments. The unified presentation layer (UPL) 206 provides methods advantageous for data object handling and analysis of data content, dynamically presented within the handler to enable user interactivity, including but not limited to sets of customizable toolbars; user menus; and various analytical interfaces; such as File New; Open; Open All (in directory); Close; Close All; Print preview; Print; ( . . . ); Edit Undo; Redo; Cut; Copy; Paste; Select; Select All; ( . . . ); ( . . . ); These components and access interfaces comprise methods for automated and/or interactive applications access, routing, translation, integration, viewing and management; automated and/or interactive data and data resource access, routing, processing, translation, integration, viewing, analysis and management.

[0208] Having described many aspects of the invention, it will be apparent to those workers having ordinary skill in the art that various modification may be made to the various structures, organizations, methods, procedures, algorithms, organizations, interfaces, and the like provided by aspects of the invention. For example, other structures and methods may be utilized for the intelligent object handler. FIG. 9, shows one of many alternative embodiments of the Intelligent Object Handler, providing an overview for a more general understanding of the Intelligent Object Handler's functions.

[0209] Through provision of these components and modules, real-time data flow to and from Intelligent Object (IMO) 200 data is described, governed, controlled, secured, and monitored and the data stream is minimized to provide means for highly efficient, non-redundant, global and selective real-time querying and reporting.

[0210] Methods defined and described include but are not limited to: cache-based non- destructive processing; information interchange of defined vector data subsets directly between data objects, applications, components and interfaces; directed meta-data and data content information interchange between data objects, applications, components and interfaces. Additionally, methods are defined and described which enable detection, extraction, definition and functional interaction of and between comprised and/or external applications, components, interfaces and data. The representation definitions create state-relevant data presentation formats in accordance with data type conventions required by detected and/or user defined applications, databases, and analytical environments. The methods comprised within these Intelligent Object Handler (IOH) 202 and Sentient Platform information technology system (See FIG. 5) enable actions including highly secure user interactivity over a variety of connection protocols; automated and/or user-defined data translation; automated and/or user-directed functional integration of data, applications and instrumentation over a variety of network protocols; direct data-to-data interaction; dynamic data content presentation within different Intelligent Object property pane (Property Panes) 1000 layers; and automated applications assembly.

[0211] It is evident from the above description, that this object management architecture allows for efficient real-time processing of complex, multidimensional, interdependent queries by providing the applications and data handling framework and infrastructure on both the user- interface level and object-interaction level, to allow for a comprehensive analysis of otherwise inaccessible, inconsistent data sets.

[0212] Although the foregoing invention has been described in some detail by way of illustration and example for purposes of clarity of understanding, it will be readily apparent to those of ordinary skill in the art in light of the teachings of this invention that certain changes and modifications may be made thereto without departing from the spirit or scope of the appended claims.

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Classifications
U.S. Classification1/1, 707/E17.005, 707/999.1
International ClassificationG06F9/46, G06F9/00, G06N5/02, G06F17/00, G06F17/30
Cooperative ClassificationY10S707/99945, Y10S707/99944, G06F17/30286
European ClassificationG06F17/30S
Legal Events
DateCodeEventDescription
Dec 6, 2001ASAssignment
Owner name: BIOSENTIENTS, INC., CALIFORNIA
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:GOMBOCZ, ERICH A.;STANLEY, ROBERT A.;REEL/FRAME:012373/0906
Effective date: 20011205