Smart Integration Engine And Metadata-Oriented Architecture For Automatic EII And Business Integration

• US 20080082569A1
• Filed: 08/09/2007
• Published: 04/03/2008
• Est. Priority Date: 08/11/2006
• Status: Active Grant

• Current Assignee: Majed Amer, Munir Badir, Rabia Mansour, Talea Sarsour
• Original Assignee: Bizwheel Ltd.
• Inventors: Mansour, Rabia, Sarsour, Talea, Amer, Majed, Badir, Munir, Badir, Naila
• Granted Patent: US 7,580,946 B2
• Time in Patent Office: Days
• US Class Current: 707/102
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

The present invention discloses systems and methods for automating the EII, using a smart integration engine based on metadata. On-line execution (i.e. data access, retrieval, or update) is automated by integrating heterogeneous data sources via a centralized smart engine based on metadata of all data sources managed in a metadata repository. The data-source assets are mapped to business metadata (terminology) giving programmers the ability to use business terms, and overcome technical terms. IT departments can use the business-level terms for easy and fast programming of all services “at the business level”. The integration is performed by the engine (via pre-configuration) automatically, dynamically, and on-line, regardless of topology or technology changes, without user or administrator intervention. MDOA is a high-level concept in which the metadata maps the technical low-level terms to business high-level terms. MDOA is used for seamless integration of a fully-distributed organization with many data sources and technologies.

Claims

1. A method for automatically generating data-service-execution solution flows for executing data services from heterogeneous data sources using metadata objects, the method comprising the steps of:

(a) providing a smart integration engine, having at least one smart integration server with a solution resolver residing therein, configured to receive DSS requests for executing the data services from the heterogeneous data sources, wherein said solution resolver has access to data assets stored in a metadata repository; and

(b) generating the solution flows of said DSS requests based on metadata criteria and on said data assets.

2. The method of claim 1, the method further comprising the step of:

(c) optimizing the solution flows based on client-defined criteria, on said metadata criteria, and on said data assets.

3. The method of claim 1, the method further comprising the step of:

(c) aggregating common data-source requests into a request bundle to be sent for execution from a specific data source.

4. The method of claim 1, the method further comprising the step of:

(c) sending an internal request, based on the solution flows, to smart integration agents for executing data from the data sources.

5. The method of claim 4, the method further comprising the steps of:

(d) discovering new data sources using said agents; and

(e) modifying the solution flows based on said new data sources.

6. The method of claim 4, wherein said agents include sensors for monitoring status information from the data sources.

7. The method of claim 4, wherein said status information includes at least one item selected from the group consisting of:

a data-source availability, a data-source validity, and an execution performance.

8. The method of claim 6, the method further comprising the step of:

(d) modifying the solution flows based on said status information.

9. The method of claim 4, wherein said agents include smart integration workers for operationally connecting to the data sources.

10. The method of claim 9, wherein said workers include adapters for facilitating connection to the data sources.

11. The method of claim 1, the method further comprising the step of:

(c) recovering from incomplete-request faults, upon said incomplete-request faults occurring, by redirecting incomplete-request elements of said incomplete-request faults to alternate data sources for execution.

12. The method of claim 1, the method further comprising the step of:

(c) storing said DSS requests and user-defined requests and previously executed requests in a schema store for faster execution via alias calls and/or web services.

13. The method of claim 1, the method further comprising the steps of:

(c) before generating the solution flows, verifying said DSS requests are allowed to be executed by a client application; and

(d) upon failing to obtain verification, ignoring said DSS requests in said step of generating the solution flows.

14. The method of claim 1, the method further comprising the step of:

(c) monitoring said DSS requests to obtain execution information.

15. The method of claim 14, the method further comprising the step of:

(d) using said execution information in order to generate new solution flows.

16. The method of claim 14, wherein said execution information includes at least one item selected from the group consisting of:

an execution time, an execution duration, and an execution status.

17. The method of claim 14, the method further comprising the step of:

(d) auditing said execution information for use in obtaining a history rollback and/or to search said execution information.

18. The method of claim 1, the method further comprising the step of:

(c) triggering an operation upon execution of a designated request.

19. The method of claim 1, the method further comprising the step of:

(c) automatically updating the data sources upon updating said data assets.

20. The method of claim 1, the method further comprising the step of:

(c) modeling execution of the data services using the solution flows.

21. The method of claim 1, the method further comprising the step of:

(c) aggregating returned data values from all the data sources into a single DSS response according to an output format.

22. The method of claim 1, wherein said metadata criteria include at least one criterion selected from the group consisting of:

a priority rule, a data-source availability, a data quality, a number of request steps, a data-source validity, and an execution performance.

23. The method of claim 1, wherein said metadata repository includes technical metadata and business metadata, wherein said technical metadata provide data-source information for executing said DSS requests, and wherein said business metadata represent said technical metadata in client terms.

24. The method of claim 23, wherein said technical metadata and business metadata include metadata selected from the group consisting of:

metadata objects, metadata components, metadata fields, compound metadata objects, organizational information, site information, data-source information, MDO-MDF association information, MDO-MDO association information, MDF-MDF association information, association transformation information, security, permission privilege information, policy information, validation information, and data-schema alias information.

25. A system for automatically generating data-service-execution solution flows for executing data services from heterogeneous data sources using metadata objects, the system comprising:

(a) a smart integration engine for executing the solution flows;

(b) at least one smart integration server for receiving at least one DSS request for executing the data services from the heterogeneous data sources;

(c) a metadata repository having at least one data asset that serves as an input for the solution flows; and

(d) a solution resolver for generating the solution flows of said at least one DSS request based on metadata criteria and said at least one data asset.

26. A computer-readable storage medium having computer-readable code embodied on the computer-readable storage medium, the computer-readable code comprising:

(a) SIE program code for enabling a smart integration engine to execute a solution flow using metadata objects;

(b) SIS program code for enabling a smart integration server to receive at least one DSS request for executing data services from heterogeneous data sources;

(c) MDR program code for enabling a metadata repository to have at least one data asset that serves as an input for said solution flow; and

(d) SR program code for enabling a solution resolver to generate said solution flow of said at least one DSS request based on metadata criteria and said at least one data asset.