SCENARIO DRIVEN DATA MODELLING: A METHOD FOR INTEGRATING DIVERSE SOURCES OF DATA AND DATA STREAMS

• US 20130124574A1
• Filed: 10/17/2012
• Published: 05/16/2013
• Est. Priority Date: 10/18/2011
• Status: Active Grant

• Current Assignee: UT-Battelle LLC
• Original Assignee: UT-Battelle LLC
• Inventors: Brettin, Thomas S., Cottingham, Robert W., Griffith, Shelton D., Quest, Daniel J.
• Granted Patent: US 9,129,039 B2
• Time in Patent Office: Days
• US Class Current: 707/798
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G16B 50/00 ICT programming tools or database systems specially adapted for bioinformatics
• CPC Class Codes: G16B 50/20 Heterogeneous data integration
• CPC Class Codes: G16H 50/80 for detecting, monitoring or modelling epidemics or pandemics, e.g. flu

Abstract

A system and method of integrating diverse sources of data and data streams is presented. The method can include selecting a scenario based on a topic, creating a multi-relational directed graph based on the scenario, identifying and converting resources in accordance with the scenario and updating the multi-directed graph based on the resources, identifying data feeds in accordance with the scenario and updating the multi-directed graph based on the data feeds, identifying analytical routines in accordance with the scenario and updating the multi-directed graph using the analytical routines and identifying data outputs in accordance with the scenario and defining queries to produce the data outputs from the multi-directed graph.

Claims

1. A computer readable storage medium storing a program of instructions executable by a machine to perform a method of integrating diverse sources of data and data streams comprising:

selecting a scenario based on a topic;

creating a multi-relational directed graph based on the scenario;

identifying and converting resources in accordance with the scenario and updating the multi-directed graph based on the converted resources;

identifying data feeds in accordance with the scenario and updating the multi-directed graph based on the data feeds;

identifying analytical routines in accordance with the scenario and updating the multi-directed graph using the analytical routines; and

identifying data outputs in accordance with the scenario and defining queries to produce the data outputs from the multi-directed graph.

2. The computer readable storage medium of claim 1, the selecting the scenario comprising:

creating detectors operable to continuously provide data related to the topic; and

obtaining one or more of particular text in accordance with the scenario, geo-location information associated with the particular text, and number of times of occurrence of the particular text.

3. The computer readable storage medium of claim 2, the identifying analytical routines comprising:

using the sensors to compare sequences in a data stream based on alignment;

performing analysis between entities of the multi-relational directed graph, literals and ontologies; and

linking the entities to samples.

4. The computer readable storage medium of claim 1, the identifying and converting resources comprising:

converting the resources into HTML; and

linking the converted resources into the multi-relational directed graph.

5. A method of integrating diverse sources of data and data streams comprising:

selecting a scenario based on a topic;

creating a multi-relational directed graph based on the scenario;

identifying and converting resources in accordance with the scenario and updating the multi-directed graph based on the converted resources;

identifying data feeds in accordance with the scenario and updating the multi-directed graph based on the data feeds;

identifying analytical routines in accordance with the scenario and updating the multi-directed graph using the analytical routines; and

identifying data outputs in accordance with the scenario and defining queries to produce the data outputs from the multi-directed graph.

6. The method of claim 5, the selecting the scenario comprising:

creating detectors operable to continuously provide data related to the topic; and

obtaining one or more of particular text in accordance with the scenario, geo-location information associated with the particular text, and number of times of occurrence of the particular text.

7. The method of claim 6, the identifying analytical routines comprising:

using the sensors to compare sequences in a data stream based on alignment;

performing analysis between entities of the multi-relational directed graph, literals and ontologies; and

linking the entities to samples.

8. The method of claim 5, the identifying and converting resources comprising:

converting the resources into HTML; and

linking the converted resources into the multi-relational directed graph.

9. A system of integrating diverse sources of data and data streams comprising:

a processor; and

a module operable to execute on the processor and to select a scenario based on a topic, create a multi-relational directed graph based on the scenario, identify and convert resources in accordance with the scenario and update the multi-directed graph based on the converted resources, identify data feeds in accordance with the scenario and updating the multi-directed graph based on the data feeds, identify analytical routines in accordance with the scenario and update the multi-directed graph using the analytical routines, and identify data outputs in accordance with the scenario and define queries to produce the data outputs from the multi-directed graph.

10. The system of claim 9, the module further operable to select the scenario by:

creating detectors operable to continuously provide data related to the topic; and

obtaining one or more of particular text in accordance with the scenario, geo-location information associated with the particular text, and number of times of occurrence of the particular text.

11. The system of claim 10, the module further operable to identify analytical routines by:

using the sensors to compare sequences in a data stream based on alignment;

performing analysis between entities of the multi-relational directed graph, literals and ontologies; and

linking the entities to samples.

12. The system of claim 9, the module further operable to identify and convert resources by:

converting the resources into HTML; and

linking the converted resources into the multi-relational directed graph.