Configurable ontology to data model transformation
View Patent ↗A computer system, storage medium, and method are disclosed for transforming an ontology into a data model. A user may configure transformation rules and ontology to data model mapping. In the first embodiment, the system comprises components for extraction from a source ontology, transformation into an entity-relationship model, load into particular data modeling tools. Other embodiments comprise an extended configuration, analytics, and user interface component. The storage medium holds standardized metadata sets for source ontology, a generic entity-relationship model representation, and data modeling tool tool-specific metadata, with machine-readable instructions to self-populate. The method may use SPARQL to extract ontology metadata, 4GL language to transform ontology into data model metadata sets, and import files or direct access to load metadata into the data modeling tool. The system, storage medium, and method can operate in reverse, transforming a data model into an ontology.
1. A system, comprising:
a non-transitory storage medium that stores computer-executable components and a processor that executes the computer-executable components stored on the non-transitory storage medium, wherein the computer-executable components comprise:
a configuration component that enables a user to configure settings for a transformation of elements of an ontology into elements of a data model;
an extraction component that retrieves ontology metadata and converts ontology metadata into ontology metadata sets;
a transformation component that transforms the ontology metadata sets into entity-relationship metadata sets and the entity-relationship metadata sets into modeling tool-specific metadata sets; and
whereby said system transforms ontology metadata into modeling tool-specific metadata according to configuration settings.
2. The system of claim 1 , wherein the extraction component can retrieve the ontology metadata from an ontology platform executing SPARQL metadata queries.
3. The system of claim 1 , wherein the extraction component can retrieve ontology metadata by parsing ontology files.
4. The system of claim 1 , further comprising:
a load component that can connect to a modeling tool and populate a data model with data model elements from the modeling tool-specific metadata set.
5. A non-transitory storage medium storing ontology metadata sets, entity-relationship metadata sets, and data modeling tool-specific metadata sets coupled with machine-readable instructions that cause one or more processors to:
enable a user to configure settings for a transformation of elements of an ontology into elements of a data model;
populate ontology metadata sets with extracted ontology metadata;
populate entity-relationship metadata sets by transforming metadata from the ontology metadata sets;
populate data modeling tool-specific metadata sets by transforming metadata from a generic entity-relationship metadata set; and
whereby a coupling of a metadata sets and instructions makes the metadata sets self-populating, reducing the complexity of machine-readable instructions.
6. The non-transitory storage medium of claim 5 , wherein the instructions populate the ontology metadata sets with extracted ontology metadata further comprise instructions that cause the one or more processors to:
retrieve ontology metadata from an ontology platform by executing SPARQL metadata queries.
7. The non-transitory storage medium of claim 5 , wherein the instructions populate the ontology metadata sets with extracted ontology metadata further comprise instructions that cause the one or more processors to:
parse ontology files to retrieve ontology metadata.
8. The non-transitory storage medium of claim 5 , wherein the instructions populate data modeling tool-specific modeling tool-specific metadata sets by transforming metadata from the generic entity-relationship metadata set, further comprise instructions that cause the one or more processors to:
connect to a data modeling tool;
create or open a data model specified in the configuration settings; and
create elements in the data model.
9. The non-transitory storage medium of claim 7 , wherein the instructions to enable a user to configure settings for a transformation of elements of the ontology into elements of a data model further comprise instructions that cause the one or more processors to enable the user to:
select, preview and modify transformation rules;
specify a scope of source ontology metadata;
review the metadata; and
correct and override metadata.
10. The non-transitory storage medium of claim 5 , wherein machine-readable instructions further cause the one or more processors to:
enable a user to configure settings for a transformation of elements of a data model into elements of an ontology;
populate the modeling tool-specific metadata sets with extracted data model metadata;
populate the entity-relationship metadata sets by transforming metadata from the modeling tool-specific metadata sets; and
populate the ontology metadata sets by transforming metadata from the entity-relationship metadata sets; and
generating SPARQL construct statements to create an ontology schema; and
whereby a coupling of metadata sets and computer instructions makes said metadata sets self-populating in a reverse direction, transforming data model metadata into ontology metadata.
11. A computer-implemented method, comprising:
enabling a user to configure settings for a transformation of elements of an ontology into elements of a data model;
extracting ontology metadata and convert the ontology metadata into ontology metadata sets;
transforming the ontology metadata sets into entity-relationship metadata sets; and
transforming the entity-relationship metadata sets into modeling tool-specific metadata sets;
whereby a user can transform an ontology into a data model.
12. The computer-implemented method of claim 11 , wherein extracting ontology metadata and converting the ontology metadata into ontology metadata sets further comprises:
connecting to an ontology platform;
opening a source ontology specified in the configuration settings;
executing SPARQL metadata queries; and
retrieving query ontology metadata.
13. The computer-implemented method of claim 11 , wherein converting the ontology metadata into ontology metadata sets further comprises:
opening an ontology file or Namespace URI;
parsing the ontology to extract ontology metadata; and
analyzing parsed ontology structure and populate the ontology metadata sets.
14. The computer-implemented method of claim 11 , wherein transforming the entity-relationship metadata sets into modeling tool-specific metadata sets further comprises:
connecting to a data modeling tool;
creating or opening the data model specified in the configuration settings; and
loading tool-specific metadata sets into the data modeling tool, creating elements in the data model.
15. The computer-implemented method of claim 11 , wherein enabling a user to configure settings for a transformation of elements of the ontology into elements of a data model further comprises:
selecting, previewing and modifying transformation rules;
specifying a scope of source ontology elements;
reviewing metadata; and
correcting and overriding the metadata.
16. The computer-implemented method of claim 11 , further comprising:
enabling a user to configure settings for a transformation of elements of a data model into elements of an ontology;
generating a list report in a data modeling tool to populate the modeling tool-specific metadata sets;
transforming the modeling tool-specific metadata sets into entity-relationship metadata sets;
transforming the entity-relationship metadata sets into ontology metadata sets;
executing SPARQL construct statements on an ontology platform to create the ontology; and
whereby a user can utilize metadata sets in a reverse direction and transform a data model into an ontology.