Database Access Through Ontologies With Semi-Automatic Semantic Mapping

• US 20080033993A1
• Filed: 08/04/2006
• Published: 02/07/2008
• Est. Priority Date: 08/04/2006
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Uceda-Sosa, Rosario A.
• Application Number:
  US11/462,385
• Publication Number:
  US 20080033993A1
• Time in Patent Office: Days
• US Class Current: 707/104.1
• CPC Class Codes: G06F 16/242 Query formulation

Abstract

A method for accessing databases through ontologies by using an IRIS (Information Representation, Inferencing and Sharing) architecture that includes nodes and links, the method comprising: representing a graph model of the ontologies, where the ontologies include concepts, properties, and relations; defining the graph model through high-level constraints; using a plurality of agents to formulate queries of the ontologies; allowing sections of the ontologies to be named and used as classes; creating an interface module based on definitions of the relations created by the plurality of agents for evaluating the high-level constraints; allowing the semi-automatic mapping of data into the ontologies; loading the data into the ontologies; allowing the plurality of agents to access the ontologies through the queries; and customizing the ontologies through views derived from the queries.

Claims

1. A method for accessing databases through ontologies by using an IRIS (Information Representation, Inferencing and Sharing) architecture that includes nodes and links, the method comprising:

representing a graph model of the ontologies, where the ontologies include concepts, properties, and relations;

defining the graph model through high-level constraints;

using a plurality of agents to formulate queries of the ontologies;

allowing sections of the ontologies to be named and used as classes;

creating an inferencing module based on definitions of the relations created by the plurality of agents for evaluating the high-level constraints;

allowing the semi-automatic mapping of data into the ontologies;

loading the data into the ontologies;

allowing the plurality of agents to access the ontologies through the queries; and

customizing the ontologies through views derived from the queries.

2. The method of claim 1, wherein the ontologies are RDF (Resource Description Framework) ontologies.

3. The method of claim 1, wherein the IRIS stores information in networks of entities, such as the classes, and the relations among the networks of entities together with inferencing knowledge.

4. The method of claim 3, wherein the inferencing knowledge is defined in IRIS Relation Algebra or I-Algebra.

5. The method of claim 1, wherein the nodes of the IRIS represent any RDF resource.

6. The method of claim 5, wherein each of the nodes of the IRIS includes two types of content, neighbor content and member content.

7. The method of claim 1, wherein the links of the IRIS represent the relations that are first-order objects in the graph model.

8. The method of claim 1, wherein the relations are represented as nodes with slots that describe structural properties.

9. The method of claim 1, wherein the high-level constraints retrieve instance data and metadata information in the queries.

10. The method of claim 1, wherein the high-level constraints define new classes, views, and contexts in the ontologies.

11. The method of claim 1, wherein the high-level constraints are categorized into sets, each set having an anchor node, the anchor node being a node where evaluation commences.

12. The method of claim 1, wherein the inferencing module allows a query of a space without the need to derive all details of an ontology organization.