IP Library Granted Patent US 7,890,517
Granted Patent B2
US 7,890,517 · App. 11/064,438 · Granted Feb 15, 2011

Appliance for enterprise information integration and enterprise resource interoperability platform and methods

Assignee: Metatomix, Inc.
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Quick Facts
Patent No.
US 7,890,517
App. No.
11/064,438
Granted
Feb 15, 2011
Kind
B2
Abstract

The invention provides apparatus, platforms 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 (59)

1. A method of enterprise integration, the method comprising, with one or more digital data processors having one or more programmed processors, executing the steps of:

A. obtaining data from one or more first data sources, the data being encoded in a first set of Resource Description Framework (RDF) triples;

B. executing a rules engine to process the first set of RDF triples in order to identify data from the one or more first data sources that relates to a criteria and to classify that data to be one or more of ignored, stored, logged for alert, broadcast, and displayed, wherein identifying data from the one or more first data sources that relates to a criteria comprises:

(i) identifying as related data substantially matching the criteria, and

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

C. responding to at least selected data classifications by obtaining data from one or more second data sources, the data being encoded in a second set of RDF triples;

D. executing the rules engine to process at least the second set of triples in order to any of further classify the data, ignore the data, store the data, generate an alert, generate a broadcast, and generate a message, and display the data.

2. The method of claim 1 , wherein any of the first and second data sources is a data stream.

3. The method of claim 1 , wherein any of the first and second data sources is a database.

4. The method of claim 1 , wherein the rules engine identifies RDF triples that are related to a selected criteria.

5. The method of claim 1 , wherein the rules engine generates alerts and/or messages for presentation to an operator based on the classification of the data.

6. The method of claim 1 , further comprising extracting data from one or more data sources, and a converting the data into the RDF triples.

7. The method of claim 1 , wherein any of the one or more first data sources and the one or more second 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.

8. The method of claim 1 , wherein the one or more digital data processors comprise a data processing station resident at a node of a public health information network (PHIN), a health area network (HAN), National Electronic Disease Surveillance System (NEDSS) network, or other network for communication of health and/or bioterrorism data.

9. The method of claim 1 , wherein the one or more digital data processors comprise an integration appliance.

10. A method of enterprise integration, the method comprising, with one or more digital data processors having one or more programmed processors, executing the steps of:

A. receiving one or more RDF data streams comprising data encoded in RDF triples; executing a rules engine to find related RDF triples by the steps of:

(i) identifying as related data substantially matching a criteria, and

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

B. responding to related RDF triples by the rules engine applying further processing of the data when certain relationships between the RDF triples are detected by the rules engine.

11. The method of claim 10 , wherein the rules engine identifies RDF triples that are related to criteria in a query.

12. The method of claim 11 , wherein the rules engine generates alerts and/or messages for presentation to an operator based on the identified RDF triples.

13. The method of claim 10 , further comprising a extracting data from one or more data sources, and a converting the data into the RDF triples.

14. The method of claim 10 , wherein the rules engines determines a classification level of data in the RDF data streams, where the classification level determines the further action taken by the rules engine.

15. The method of claim 10 , wherein the one or more RDF data streams comprise information received in accordance 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.

16. The method of claim 10 , wherein the one or more digital data processors comprise a data processing station resident at a node of a public health information network (PHIN), a health area network (HAN), National Electronic Disease Surveillance System (NEDSS) network, or other network for communication of health and/or bioterrorism data.

17. The method of claim 10 , wherein the one or more digital data processors comprise an integration appliance.

18. A method of enterprise integration, the method comprising, with one or more digital data processors having one or more programmed processors, executing the steps of:

A. receiving one or more RDF data streams comprising data encoded in RDF triples;

B. executing a rules engine to process the RDF triples in order to identify data from the one or more RDF data streams that relates to a criteria and to classify that data to be one or more of ignored, stored, logged for alert, broadcast, and displayed, wherein identifying data from the one or more RDF data streams that relates to a criteria comprises:

(i) identifying as related data substantially matching the criteria, and

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

C. responding to the classification of the data and the related RDF triples by the rules engine applying further processing of the data.

19. The method of claim 18 , wherein the rules engine identifies RDF triples that are related to criteria in a query.

20. The method of claim 19 , wherein the rules engine generates alerts and/or messages for presentation to an operator based on the identified RDF triples.

21. The method of claim 18 , further comprising extracting data from one or more data sources, and converting the data into the RDF triples.

22. The method of claim 18 , wherein the rules engines determines a classification level of data in the RDF data streams, where the classification level determines the further action taken by the rules engine.

23. The method of claim 18 , wherein the one or more RDF data streams comprise information received in accordance 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.

24. The method of claim 18 , wherein the one or more digital data processors comprise a data processing station resident at a node of a public health information network (PHIN), a health area network (HAN), National Electronic Disease Surveillance System (NEDSS) network, or other network for communication of health and/or bioterrorism data.

25. The method of claim 18 , wherein the one or more digital data processors comprise an integration appliance.

26. A data processing system for enterprise integration, the system comprising:

a plurality of data sources; and

one or more digital data processors having one or more processors, storage units, and/or communication devices, said one or more digital data processors being coupled to the data sources and comprising:

conversion functionality to convert data from the data sources into Resource Description Framework (RDF) triples; and

a rules engine coupled to the data sources to process the RDF triples, the processing comprising identifying data from the one or more data sources that relates to a criteria and to classify that data to be one or more of ignored, stored, logged for alert, broadcast, and displayed, wherein identifying data from the one or more data sources that relates to a criteria comprises:

(i) identifying as related data substantially matching the criteria, and

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

wherein the classification of the RDF triples can trigger additional function of the rules engine.

27. The method of claim 26 , wherein one or more of the plurality of 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.

28. The method of claim 26 , wherein the one or more digital data processors comprise a data processing station resident at a node of a public health information network (PHIN), a health area network (HAN), National Electronic Disease Surveillance System (NEDSS) network, or other network for communication of health and/or bioterrorism data.

29. The method of claim 26 , wherein the one or more digital data processors comprise an integration appliance.

30. A data processing system for enterprise integration, the system comprising:

a plurality of data sources; and

one or more digital data processors having one or more processors, storage units, and/or communication devices, said one or more digital data processors being coupled to the data sources and comprising:

conversion functionality to convert data from the data sources into Resource Description Framework (RDF) triples; and

a rules engine coupled to the data sources to process the RDF triples, the processing comprising identifying data from the one or more data sources that relates to a criteria and to classify that data to be one or more of ignored, stored, logged for alert, broadcast, and displayed, wherein identifying data from the one or more data sources that relates to a criteria comprises:

(i) identifying as related data substantially matching the criteria, and

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

wherein the rules engine generates alerts and/or messages for presentation to an operator based on the identified RDF triples.

Assignments (5)
CHANGE OF NAME Recorded Jan 25, 2016
From: METATOMIX, INC.
To: OBJECTSTORE, INC.
Reel/Frame 037587/0587 →
RELEASE OF SECURITY INTEREST Recorded Feb 13, 2015
From: NUTTER MCCLENNEN & FISH LLP
To: METATOMIX, INC.
Reel/Frame 034957/0613 →
LIEN Recorded Feb 23, 2011
From: METATOMIX, INC.
To: NUTTER MCCLENNEN & FISH LLP
Reel/Frame 025846/0744 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 27, 2006
From: BAJPAI, CHANDRA
To: METATOMIX, INC.
Reel/Frame 018130/0129 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 2, 2005
From: ANGELO, ROBERT F.; AZMI, AMIR; BRITTON, COLIN P.; KAUFMAN, NOAH W.M.; KUMAR, ASHOK; RAYBOURN, DARREN
To: METATOMIX, INC.
Reel/Frame 017291/0799 →
Continuity (21)
Continuation In Part 11029164 · Jan 4, 2005
Continuation 10051619 · Oct 29, 2001
Continuation In Part 09917264 · Jul 27, 2001
Continuation In Part 11064438
Continuation In Part 10302727 · Nov 21, 2002
Continuation In Part 10302764 · Nov 21, 2002
Continuation In Part 09917264 · Jul 27, 2001
Continuation In Part 10051619 · Oct 29, 2001
Continuation In Part 11064438
Continuation In Part 10680049 · Oct 7, 2003
Continuation In Part 11064438
Continuation In Part 10886515 · Jul 7, 2004
Continuation In Part 11064438
Continuation In Part 10138725 · May 3, 2002
Provisional Application 60324037 · Sep 21, 2001
Provisional Application 60291185 · May 15, 2001
Provisional Application 60332053 · Nov 21, 2001
Provisional Application 60332219 · Nov 21, 2001
Provisional Application 60416616 · Oct 7, 2002
Provisional Application 60485200 · Jul 7, 2003
Related Publication 20060271563A1 · Nov 30, 2006