Surveillance, monitoring and real-time events platform

• US 20050055330A1
• Filed: 07/07/2004
• Published: 03/10/2005
• Est. Priority Date: 05/15/2001
• Status: Active Grant

• Current Assignee: Objectstore Incorporated
• Original Assignee: Objectstore Incorporated
• Inventors: Britton, Colin P., Greenblatt, Howard, Greenblatt, Alan
• Granted Patent: US 8,572,059 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/338 Presentation of query results
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/80 for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
• CPC Class Codes: H04L 67/01 Protocols

Abstract

Systems and methods according to the invention provide a surveillance, monitoring and real-time events platform to (i) enable the integration and communication of information between government agencies and organizations specifically tasked with ensuring the security and safety of our nation and its communities, (ii) to integrate information systems from federal, state and/or local agencies (from disparate data sources if necessary) in order to obtain a single, real-time view of the entire organization, and (iii) to extract more complete, actionable information from their existing systems, thereby dramatically improving decision making speed and accuracy.

Claims

1. A digital data processing system for surveillance, monitoring and real-time events handling, the system comprising

a plurality of data sources,

query functionality, coupled to the data sources, to identify information from the data sources responsive to one or more queries,

a framework server, coupled to the query functionality, that presents information selected identified by the expert engine to a web browser.

2. The digital data processing system of claim 1, wherein the data sources comprise network nodes at one or more clinical care providers, laboratories, governmental health departments, centers for disease control, and law enforcement offices.

3. The digital data processing system of claim 1, wherein the query functionality comprises any of a graph generator, algorithmic search and an expert engine,

4. The digital data processing system of claim 3, wherein

the query functionality comprises an expert engine, and wherein

the expert engine classifies the information from the data sources to be ignored, stored and/or logged for alert.

5. The digital data processing system of claim 1, comprising a data store that maintains resource description framework (RDF) triples representing at least selected data from the data sources.

6. The digital data processing system of claim 5, wherein the data sources are compliant with a public health information network (PHIN) protocol, a health area network (HAN) protocol, National Electronic Disease Surveillance System (NEDSS) protocol, or other protocol for communication of health and/or bioterrorism data and wherein the system comprises interconnect functionality that applies requests to, and receives information from, one or more of the data sources utilizing an API or interface mechanism dictated by the PHIN, HAN or NEDSS or other protocol communication of information used in communication of health and bioterrorism data.

7. The digital data processing system of claim 6, wherein the interconnect applies SQL queries to selected ones of the data sources.

8. The digital data processing system of claim 7, wherein the interconnect provides for the automated exchange of information with one or more selected data sources.

9. The digital data processing system of claim 8, wherein the interconnect provides for the automated exchange of information between public health partners on a PHIN network.

26. The digital data processing system of claim 1, wherein the data sources comprise network nodes at one or more clinical care providers, laboratories, governmental health departments, centers for disease control, and law enforcement offices and wherein the data sources are compliant with a public health information network (PHIN) protocol, a health area network (HAN) protocol, National Electronic Disease Surveillance System (NEDSS) protocol, or other protocol for communication of health and/or bioterrorism data.

35. The digital data processing system of any of claims 1, 10, 16 and 25 wherein the framework server generates a border/port security display comprising a plurality of panels, a first of which displays information relating to an alert, a second of which displays information from a particular data source or an aggregation of data from several data sources, a third of which displays real-time data from a data source superimposed on a map of a locale.

36. The digital data processing system of claim 35, wherein the framework server responds to a selected user input with respect to an item displayed in one of the panels by display additional information about that item.

37. The digital data processing system of claim 35, wherein the framework server responds to an alert by displaying a zoomed-in portion of a locale shown in one of the panels and wherein the system includes additional functionality for alerting people, agencies or other entities of such alert.

38. The digital data processing system of any of claims 1, 10, 16 and 25 wherein the system is configured for any of border &

port security, public &

community safety, and government data integration applications.

10. A digital data processing system for surveillance, monitoring and real-time events handling, the system comprising

a plurality of data sources,

an expert engine, coupled to the data sources, to identify related information received therefrom, the expert engine executing the steps of

(i) identifying as related data substantially matching a criteria;

(ii) identifying as related data that is a direct ancestor of data identified in any of steps (i), (ii) and (iii), and that is not in substantial conflict with the criteria;

(iii) identifying as related data (hereinafter “

identified descendent”

) that is a direct descendent of data (hereinafter “

identified ancestor”

) identified as related in any of steps (i), (ii) and (iii), and which identified descendent

(a) does not have a named relationship with the identified ancestor substantially matching a relationship named in the criteria, if any, and

(b) is not in substantial conflict with the criteria;

(c) does not have a named relationship with the identified ancestor matching a relationship the identified ancestor has with a data, if any, as a result of which the identified ancestor was identified during execution of step (ii),

a framework server, coupled to the expert engine, that presents selected information identified as related by the expert engine to a web browser.

11. The digital data processing system of claim 10, wherein the data sources comprise network nodes at one or more clinical care providers, laboratories, governmental health departments, centers for disease control, and law enforcement offices, and wherein the data sources are compliant with a public health information network (PHIN) protocol, a health area network (HAN) protocol, National Electronic Disease Surveillance System (NEDSS) protocol, or other protocol for communication of health and/or bioterrorism data.

12. The digital data processing system of claim 10, comprising query functionality, comprising any of a graph generator and algorithmic search, to identify information from the data sources responsive to one or more queries.

13. The digital data processing system of claim 12, wherein the expert engine is coupled to the query functionality to classify information received therefrom to be ignored, stored and/or logged for alert.

14. The method of claim 10, wherein the criteria specifies a named relationship and a characteristic of that named relationship, and wherein

step (ii) includes comparing at least one of the relationship and the characteristic named in a criteria with any of attributes of the direct ancestor, and

a relationship between the direct ancestor and any data that descends therefrom, in order to determine whether the director ancestor is in substantial conflict with the criteria.

15. The method of claim 10, wherein

the criteria specifies a named relationship and a characteristic of that named relationship, and wherein

step (iii) includes comparing at least one of the relationship and the characteristic named in a criteria with any of

attributes of the identified descendent, and

a relationship between the identified descendent and any data that descends therefrom,

in order to determine whether the identified descendent ancestor is in substantial conflict with the criteria.

16. A digital data processing system for surveillance, monitoring and real-time events handling, the system comprising

a plurality of data sources,

a data store that maintains resource description framework (RDF) triples representing at least selected data from the data sources

data reduction functionality, coupled to the data sources and to the data store, to identify information from the data sources responsive to one or more queries and to summarize that information in one or more selected epochs of differing length, the data reduction functionality generating RDF triples characterizing the summarized information and storing those triples to the data store,

a framework server, coupled to the query functionality, that presents information selected identified by the expert engine to a web browser.

17. The digital data processing system of claim 16, wherein the data reduction functionality queries one or more data sources in an SQL format.

18. The digital data processing system of claim 16, wherein the data reduction functionality parses an XML file that identifies one or more of the data sources, one or more fields thereof to be summarized, and/or one or more epochs for which those fields are to be summarized.

19. The digital data processing system of claim 16, wherein the data reduction functionality responds to data received from a data source by updating a store associated with an epoch of shorter duration.

20. The digital data processing system claim 16, wherein the framework server generates a display or other presentation based on the RDF triples characterizing the summarized data.

21. The digital data processing system of claim 20, query functionality, coupled to the data sources and to the data reduction functionality, to identify information from the data sources responsive to one or more queries,

a framework server, coupled to the query functionality, that presents information selected identified by the expert engine to a web browser.

22. The digital data processing system of claim 20, wherein the data sources comprise network nodes at one or more clinical care providers, laboratories, governmental health departments, centers for disease control, and law enforcement offices.

23. The digital data processing system of claim 20, wherein the query functionality comprises any of a graph generator, algorithmic search and an expert engine,

24. The digital data processing system of claim 23, wherein

the query functionality comprises an expert engine, and wherein

the expert engine classifies the information from the data sources to be ignored, stored and/or logged for alert.

25. A digital data processing system for surveillance, monitoring and real-time events handling, the system comprising

A. a plurality of data sources,

B. query functionality, coupled to the data sources, to identify information from the data sources responsive to one or more queries, the query functionality translating a schema-less input query in a first language to an output query in a second language by the steps of:

i) examining the schema-less input query for one or more tokens that represent data to be used in generating the output query;

ii) dispatching context-specific grammar events containing that data; and

iii) populating portions of the output query according to the events and data;

iv) generating the output query in the second language comprising those populated portions, wherein the output query represents a schema of a relational database storing RDF triples,

C. a framework server, coupled to the query functionality, that presents information selected identified by the expert engine to a web browser.

27. The digital data processing system of claim 25, wherein in connection with dispatching events the query functionality generates any of a logical condition event, a selection term declaration event, and a triple declaration event.

28. The digital data processing system of claim 25, wherein in connection with generating a logical condition event the query functionality generates an event containing data which, when applied to the relational database via the output query, identifies RDF triples according to a Boolean condition.

29. The digital data processing system of claim 25, wherein in connection with generating a selection term declaration event the query functionality generates an event containing data which, when applied to the relational database via the output query, identifies RDF triples including a specified term.

30. The digital data processing system of claim 25, wherein in connection with generating a triple declaration event the query functionality generates an event containing data which, when applied to the relational database via the output query, identifies RDF triples according to a specified subject, predicate and object.

31. The digital data processing system of claim 25, wherein the query functionality comprises any of a graph generator, algorithmic search and an expert engine,

32. The digital data processing system of claim 31, wherein

the query functionality comprises an expert engine, and wherein

the expert engine classifies the information from the data sources to be ignored, stored and/or logged for alert.

33. The digital data processing system of claim 25, further comprising data reduction functionality, coupled to the data sources and to the data store, to identify information from the data sources responsive to one or more queries and to summarize that information in one or more selected epochs of differing length, the data reduction functionality generating RDF triples characterizing the summarized information and storing those triples to the data store.

34. The digital data processing system of claim 31, wherein

the query functionality comprises an expert engine, and wherein

the expert engine classifies the information from the data sources to be ignored, stored and/or logged for alert.

39. (cancelled).