Semantic mapping of topic map meta-models identifying assets and events to include weights

• US 9,535,978 B2
• Filed: 06/02/2014
• Issued: 01/03/2017
• Est. Priority Date: 03/29/2012
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Coldicott, Peter A., Hanis, Thomas T., Lane, Eoin
• Primary Examiner(s): Hill, Stanley K
• Assistant Examiner(s): Traktovenko, Ilya
• Application Number:
  US14/293,292
• Publication Number:
  US 20140280228A1
• Time in Patent Office: 946 Days
• Field of Search: 706/52, 706/46, 706/45, 706/62
• US Class Current: 1/1
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

Determining an impact of an event identified in a first topic map meta-model will have on at least one asset identified in a second topic map meta-model representative of weight. A third topic map meta-model is created which maps at least one asset from the second topic map meta-model to an event from the first topic map meta-model and is comprised of: a topic map representation of assets of the second topic map meta-model and events of the first topic map meta-model, a topic map based index with instance ontology of the first and second topic map meta-models, identification of at least one association between an event identified in the first topic map meta-model and at least one asset identified in the second topic map meta-model; and weight assigned to the at least one association.

Claims

1. A method of determining an impact of an event identified in a first topic map meta-model will have on at least one asset identified in a second topic map meta-model representative as a weight, the method comprising the steps of:

a computer creating a third topic map meta-model which maps at least one asset from the second topic map meta-model to an event from the first topic map meta-model, the third topic map meta-model comprising;

a topic map representation of assets of the second topic map meta-model, the second topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of assets;

a topic map representation of events of the first topic map meta-model, the first topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of events;

identification of at least one association mapped between an event identified in the first topic map meta-model and at least one asset identified in the second topic map meta-model; and

weight associated with the identification and assigned to the at least one-association between an event identified in a first topic map meta-model and an asset identified in a second topic map meta-model in various scopes;

the computer receiving a query input from a user identifying an event;

the computer obtaining from the query input, at least an identification of an association between at least one asset and an event in the third topic map meta-model;

the computer searching the third topic map meta-model for the identification from the query input;

the computer displaying all weights assigned to the association between the event in the first topic map meta-model and at least one asset of the second topic map meta-model in at least one scope to the user.

2. The method of claim 1, wherein the identification of the associations comprises the steps of:

assigning an identifier in the third topic map meta-model to each of the associations between at least one asset and at least one event;

identifying and assigning in the third topic map meta-model an identifier to the topics of the association and the roles of the topics in the association; and

identifying and assigning in the third topic map meta-model an identifier to a scope of the association between at least one asset and at least one event of the event topic map meta-model.

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

in response to a new event being added to the topic map meta-model identifying events, the computer re-creating the third topic map meta-model for the new event, adjusting the weight associated with the association in the third topic map meta-model, the re-created third map meta-model including a topic map based index and instance ontology for the new event and the adjusted weight; and

the computer storing the re-created third topic map meta-model into a repository.

4. The method of claim 1, wherein the weights are stored in a data structure.

5. The method of claim 4, wherein the data structure is stored within the third topic map meta-model.

6. A computer program product of determining an impact of an event identified in a first topic map meta-model will have on at least one asset identified in a second topic map meta-model representative as a weight comprising a computer comprising at least one processor, one or more memories, one or more computer readable storage media, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by the computer to perform a method comprising:

creating, by the computer a third topic map meta-model which maps at least one asset from the second topic map meta-model to an event from the first topic map meta-model, the third topic map meta-model comprising;

a topic map representation of assets of the second topic map meta-model, the second topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of assets;

a topic map representation of events of the first topic map meta-model, the first topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of events;

identifying by the computer, of at least one association mapped between an event identified in the first topic map meta-model and at least one asset identified in the second topic map meta-model; and

assigning, by the computer, weight associated with the identification to the at least one association between an event identified in a first topic map meta-model and an asset identified in a second topic map meta-model in various scopes;

receiving, by the computer, a query input from a user identifying an event;

obtaining, by the computer, from the query input, at least an identification of an association between at least one asset and an event in the third topic map meta-model;

searching, by the computer, the third topic map meta-model for the identification from the query input;

displaying, by the computer, all weights assigned to the association between the event in the first topic map meta-model and at least one asset of the second topic map meta-model in at least one scope to the user.

7. The computer program product of claim 6, wherein the program instructions of identification by the computer comprises the steps of:

assigning, by the computer, an identifier in the third topic map meta-model to each of the associations between at least one asset and at least one event;

identifying and assigning, by the computer, in the third topic map meta-model an identifier to the topics of the association and the roles of the topics in the association; and

identifying and assigning, by the computer, in the third topic map meta-model an identifier to a scope of the association between at least one asset and at least one event of the event topic map meta-model.

8. The computer program product of claim 6, further comprising the program instructions to:

in response to a new event being added to the topic map meta-model identifying events, the computer re-creating the third topic map meta-model for the new event, adjusting the weight associated with the association in the third topic map meta-model, the re-created third map meta-model including a topic map based index and instance ontology for the new event and the adjusted weight; and

storing, by the computer, the re-created third topic map meta-model into a repository.

9. The computer program product of claim 6, wherein the weights are stored in a data structure.

10. The computer program product of claim 9, wherein the data structure is stored within the third topic map meta-model.

11. A computer system of determining an impact of an event identified in a first topic map meta-model will have on at least one asset identified in a second topic map meta-model representative as a weight comprising a computer comprising at least one processor, one or more memories, one or more computer readable storage media having program instructions executable by the computer to perform the program instructions comprising:

creating, by the computer a third topic map meta-model which maps at least one asset from the second topic map meta-model to an event from the first topic map meta-model, the third topic map meta-model comprising;

a topic map representation of assets of the second topic map meta-model, the second topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of assets;

a topic map representation of events of the first topic map meta-model, the first topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of events;

identifying, by the computer, identification of at least one association mapped between an event identified in the first topic map meta-model and at least one asset identified in the second topic map meta-model; and

assigning, by the computer, weight associated with the identification to the at least one association between an event identified in a first topic map meta-model and an asset identified in a second topic map meta-model in various scopes;

receiving, by the computer, a query input from a user identifying an event;

obtaining, by the computer, from the query input, at least an identification of an association between at least one asset and an event in the third topic map meta-model;

searching, by the computer, the third topic map meta-model for the identification from the query input;

displaying, by the computer, all weights assigned to the association between the event in the first topic map meta-model and at least one asset of the second topic map meta-model in at least one scope to the user.

12. The computer system of claim 11, wherein the program instructions of identification by the computer comprises the steps of:

assigning, by the computer, an identifier in the third topic map meta-model to each of the associations between at least one asset and at least one event;

identifying and assigning, by the computer, in the third topic map meta-model an identifier to the topics of the association and the roles of the topics in the association; and

identifying and assigning, by the computer, in the third topic map meta-model an identifier to a scope of the association between at least one asset and at least one event of the event topic map meta-model.

13. The computer system of claim 11, further comprising the program instructions to:

in response to a new event being added to the topic map meta-model identifying events, the computer re-creating the third topic map meta-model for the new event, adjusting the weight associated with the association in the third topic map meta-model, the re-created third map meta-model including a topic map based index and instance ontology for the new event and the adjusted weight; and

storing, by the computer, the re-created third topic map meta-model into a repository.

14. The computer system of claim 11, wherein the weights are stored in a data structure.

15. The computer system of claim 14, wherein the data structure is stored within the third topic map meta-model.