Bi-directional data mapping tool

• US 7,827,205 B2
• Filed: 05/27/2004
• Issued: 11/02/2010
• Est. Priority Date: 05/27/2004
• Status: Expired due to Fees

• Current Assignee: LinkedIn Corporation (Microsoft Corporation)
• Original Assignee: International Business Machines Corporation
• Inventors: Okunseinde, Folu, Stading, Tyron
• Primary Examiner(s): Morrison; Jay A
• Application Number:
  US10/855,724
• Publication Number:
  US 20060004854A1
• Time in Patent Office: 2,350 Days
• Field of Search: None
• US Class Current: 707/802
• CPC Class Codes: G06F 16/25 Integrating or interfacing systems involving database management systems

Abstract

A computer implemented method is provided for a bi-directional data mapping tool. The method for mapping between at least two data models comprises selecting a source including a first data model, selecting a target including a second data model and defining a relationship between the data in the source and the data in the target. The method further comprises generating a bi-directional map from at least portions of the source, the target, and the defined relationship.

Claims

1. A computer-implemented method, in a data processing system having a processor and a data storage device, for mapping between at least two data models, comprising:

selecting, by a user via a user interface of the data processing system, a source document in a computing system having a first data model having a first structure;

selecting, by the user via the user interface, a target format or target document in a computing system having a second data model having a second structure;

defining, by the user via the user interface, a relationship between the first data model and the second data model based on the first structure and the second structure, wherein the first structure and second structure are different;

generating, by the processor of the data processing system, a bi-directional map between the first and second data models from at least portions of the source document, the target format or document, and the defined relationship, wherein the bi-directional map converts the content of a data store from the first data model to the second data model and converts the content of a data store from the second data model to the first data model; and

storing the bi-directional map in the data storage device of the data processing system, wherein generating a bi-directional map between the first and second data models comprises;

assigning, to each data element in contents of the source document, a variable, thereby defining a first set of variables for the source document;

assigning, to each data element in the target format or target document, a variable, thereby defining a second set of variables for the source document;

receiving a first user input selecting a first subset of variables from the first set of variables;

receiving a second user input selecting a second subset of variables from the second set of variables to which the first subset of variables are to be mapped, wherein the first subset of variables and second subset of variables have different numbers of variables from each other;

performing a bi-directional interpolation between the first subset of variables and the second subset of variables based on the defined relationship;

generating a first map for mapping the first subset of variables to the second subset of variables based on results of the bi-directional interpolation; and

generating a second map for mapping the second subset of variables to the first subset of variables based on results of the bi-directional interpolation.

2. The computer-implemented method of claim 1, wherein defining the relationship comprises defining at least one function operating on the first data model, the second data model, or both the first and second data models to yield a result in the second data model, the first data model, or both the second and first data models, respectively.

3. The computer-implemented method of claim 2, wherein the at least one defined function includes a concatenate function for conversion from the first data model to the second data model and a parse function for conversion from the second data model to the first data model.

4. The computer-implemented method of claim 3, wherein the first data model has a structure comprising three data elements comprising a ‘

FirstName’

data element, a ‘

MiddleName’

data element, and a ‘

LastName’

data element;

the second data model has a structure comprising one data element comprising a ‘

FullName’

data element; and

the bi-directional map both converts the FirstName’

data element, the ‘

MiddleName’

data element, and the ‘

LastName’

data element to the ‘

FullName’

data element and converts the ‘

FullName’

data element to the ‘

FirstName’

data element, the ‘

MiddleName’

data element, and the ‘

LastName’

data element.

5. The computer-implemented method of claim 2, wherein the at least one defined function comprises:

at least one function to transform data from a numeric data model to an ordinal data model and from the ordinal data model to the numeric data model;

or

at least one function to convert data from a first time zone data model to a second time zone data model and from the second time zone data model to the first time zone data model;

or

at least one function to convert data from a first date format data model to a second date format data model and from the second date format data model to the first date format data model, and

wherein the at least one function is stored in a function library and invoked from the function library when converting the content of a data store from the first data model to the second data model and the content of a data store from the second data model to the first data model.

6. The computer-implemented method of claim 1, further comprising:

generating one or more additional bi-directional data maps, to yield a plurality of bi-directional data maps, each additional map mapping bi-directionally between two data models other than between the first data model and the second data model; and

storing the generated bi-directional data maps in a map library, wherein the plurality of bi-directional maps converts the content of a data store from the first data model to the second data model or a third data model, converts the content of a data store from the second data model to the first data model or the third data model, and converts the content of a data store from the third data model to the first data model or the second data model.

25. The computer implemented method of claim 1, wherein receiving a first user input selecting a first subset of variables from the first set of variables comprises receiving a user selection of a representation of a subset of data elements from the source document, corresponding to the first subset of variables, via the user interface.

26. The computer implemented method of claim 25, wherein receiving a second user input selecting a second subset of variables from the second set of variables comprises detecting a user operation to drag the representation of the selected subset of data elements to a representation of one or more data elements of the target format or target document corresponding to the second subset of variables, via the user interface.

27. The computer implemented method of claim 25, wherein receiving a first user input selecting a first subset of variables from the first set of variables comprises receiving a user selection of a representation of a subset of data elements from the source document, corresponding to the first subset of variables, via the user interface, and wherein receiving a second user input selecting a second subset of variables from the second set of variables comprises receiving a user selection of a function, from a function library, and one or more target elements of the target format or target document.

7. A computing system, comprising:

a processor communicatively coupled to a memory, wherein the processor is adapted to;

receive a source selection for a source document in a computing system having a first data model having a first structure;

receive a target selection for a target format or for a target document in a computing system having a second data model having a second structure;

define a relationship between the structures of the first data model and the second data model, wherein the first structure and second structure are different; and

generate a bi-directional map between the first data model and the second data model from at least portions of the source document, the target format or target document, and the defined relationship, wherein the bi-directional map converts the content of a data store from the first data model to the second data model and converts the content of a data store from the second data model to the first data model, wherein the bi-directional map is generated between the first and second data models by;

assigning, to each data element in contents of the source document, a variable, thereby defining a first set of variables for the source document;

assigning, to each data element in the target format or target document, a variable, thereby defining a second set of variables for the source document;

receiving a first user input selecting a first subset of variables from the first set of variables;

receiving a second user input selecting a second subset of variables from the second set of variables to which the first subset of variables are to be mapped, wherein the first subset of variables and second subset of variables have different numbers of variables from each other;

performing a bi-directional interpolation between the first subset of variables and the second subset of variables based on the defined relationship;

generating a first map for mapping the first subset of variables to the second subset of variables based on results of the bi-directional interpolation; and

generating a second map for mapping the second subset of variables to the first subset of variables based on results of the bi-directional interpolation.

8. The computing system of claim 7, wherein the processor is adapted to define the relationship by actions comprising defining at least one function operating on the first data model, the second data model, or both the first and second data models to yield a result in the second data model, the first data model, or both the second and first data models, respectively.

9. The computing system of claim 8, wherein the at least one defined function includes a concatenate function for conversion from the first data model to the second data model and a parse function for conversion from the second data model to the first data model.

10. The computing system of claim 9, wherein the first data model has a structure comprising three data elements comprising a ‘

FirstName’

data element, a ‘

MiddleName’

data element, and a ‘

LastName’

data element;

the second data model has a structure comprising one data element comprising a ‘

FullName’

data element; and

the bi-directional map both converts the ‘

FirstName’

data element, the ‘

MiddleName’

data element, and the ‘

LastName’

data element to the ‘

FullName’

data element and converts the ‘

FullName’

data element to the ‘

FirstName’

data element, the ‘

MiddleName’

data element, and the ‘

LastName’

data element.

11. The computing system of claim 8, wherein the at least one defined function comprises:

at least one function to transform data from a numeric data model to an ordinal data model and from the ordinal data model to the numeric data model;

or

at least one function to convert data from a first time zone data model to a second time zone data model and from the second time zone data model to the first time zone data model;

or

at least one function to convert data from a first date format data model to a second date format data model and from the second date format data model to the first date format data model, and

wherein the processor is adapted to store the at least one function in a function library and invoke the at least one function from the function library when converting the content of a data store from the first data model to the second data model and the content of a data store from the second data model to the first data model.

12. The computing system of claim 7, wherein the processor is further adapted to:

generate one or more additional bi-directional data maps, to yield a plurality of bi-directional data maps, each additional map mapping bi-directionally between two data models other than between the first data model and the second data model; and

store the generated bi-directional data maps in a map library,

wherein the plurality of bi-directional maps converts the content of a data store from the first data model to the second data model or a third data model, converts the content of a data store from the second data model to the first data model or the third data model, and converts the content of a data store from the third data model to the first data model or the second data model.

13. The computing system of claim 7, wherein the processor is further adapted to:

generate one or more additional bi-directional data maps, to yield a plurality of bi-directional data maps, each additional map mapping bi-directionally between two data models other than between the first data model and the second data model;

and

store the generated bi-directional data maps in a map library,

wherein the plurality of bi-directional maps converts the content of a data store from the first data model to the second data model or a third data model, converts the content of a data store from the second data model to the first data model or the third data model, and converts the content of a data store form the third data model to the first data model or the second data model;

wherein the processor is adapted to define the relationship by actions comprising defining at least one function operating on at least one data model to yield a result in at least one other data model;

wherein the processor is adapted to generate the plurality of bi-directional maps by actions comprising generating from at least portions of the source document, the target format or document, and the at least one defined function; and

wherein the processor is adapted to store the at least one function in a function library and invoke the at least one function from the function library when converting the content of a data store from the first data model to the second data model and the content of a data store from the second data model to the first data model.

14. A program storage medium encoded with instructions that, when executed by a computing apparatus, perform a method for mapping between data models, the method comprising:

receiving a source selection, for a source document in the program storage medium having a first data model having a first structure;

receiving a target selection for a target format or for a target document in the program storage medium having a second data model having a second structure;

defining a relationship between the structures of the first data model and the second data model; and

generating a bi-directional map between the first data model and the second data model from at least portions of the source document, the target format or target document, and the defined relationship, wherein the bi-directional map converts the content of a data store from the first data model to the second data model and converts the content of a data store from the second data model to the first data model, wherein the bi-directional map is generated between the first and second data models by;

assigning, to each data element in contents of the source document, a variable, thereby defining a first set of variables for the source document;

assigning, to each data element in the target format or target document, a variable, thereby defining a second set of variables for the source document;

receiving a first user input selecting a first subset of variables from the first set of variables;

receiving a second user input selecting a second subset of variables from the second set of variables to which the first subset of variables are to be mapped, wherein the first subset of variables and second subset of variables have different numbers of variables from each other;

performing a bi-directional interpolation between the first subset of variables and the second subset of variables based on the defined relationship;

generating a first map for mapping the first subset of variables to the second subset of variables based on results of the bi-directional interpolation; and

generating a second map for mapping the second subset of variables to the first subset of variables based on results of the bi-directional interpolation.

15. The program storage medium of claim 14, wherein defining the relationship comprises defining at least one function operating on the first data model, the second data model, or both the first and second data models to yield a result in the second data model, the first data model, or both the second and first data models, respectively.

16. The program storage medium of claim 15, wherein the at least one defined function includes a concatenate function for conversion from the first data model to the second data model and a parse function for conversion from the second data model to the first data model.

17. The program storage medium of claim 16, wherein the first data model has a structure comprising three data elements comprising a ‘

FirstName’

data element, a ‘

MiddleName’

data element, and a ‘

LastName’

data element;

the second data model has a structure comprising one data element comprising a ‘

FullName’

data element; and

the bi-directional map both converts the ‘

FirstName’

data element, the ‘

MiddleName’

data element, and the ‘

LastName’

data element to the ‘

FullName’

data element and converts the ‘

FullName’

data element to the ‘

FirstName’

data element, the ‘

MiddleName’

data element, and the ‘

LastName’

data element.

18. The program storage medium of claim 15, wherein the at least one defined function comprises:

at least one function to transform data from a numeric data model to an ordinal data model and from the ordinal data model to the numeric data model;

or

at least one function to convert data from a first time zone data model to a second time zone data model and from the second time zone data model to the first time zone data model;

or

at least one function to convert data from a first date format data model to a second date format data model and from the second date format data model to the first date format data model, and

wherein the at least one function in a function library and invoked from the function library when converting the content of a data store from the first data model to the second data model and the content of a data store from the second data model to the first data model.

19. A computer-implemented method, in a data processing system comprising a processor and a hardware data storage device, of converting the content of the hardware data storage device from a first data model to a second data model, the method comprising:

storing, in the hardware data storage device, a bi-directional data map, the bi-directional map being generated between the first and second data models from at least portions of a source document, a target format or document, and a defined relationship between the source document and the target format or document;

mapping, by the processor, data in a target format or target document including the second data model into the first data model of a source, and

converting, by the processor, both the content of a data store from the first data model to the second data model using the bi-directional map and the content of a data store from the second data model to the first data model using the bi-directional map, wherein the bi-directional map is generated between the first and second data models by;

assigning, to each data element in contents of the source document, a variable, thereby defining a first set of variables for the source document;

assigning, to each data element in the target format or target document, a variable, thereby defining a second set of variables for the source document;

receiving a first user input selecting a first subset of variables from the first set of variables;

receiving a second user input selecting a second subset of variables from the second set of variables to which the first subset of variables are to be mapped, wherein the first subset of variables and second subset of variables have different numbers of variables from each other;

performing a bi-directional interpolation between the first subset of variables and the second subset of variables based on the defined relationship;

generating a first map for mapping the first subset of variables to the second subset of variables based on results of the bi-directional interpolation; and

generating a second map for mapping the second subset of variables to the first subset of variables based on results of the bi-directional interpolation.

20. The computer-implemented method of claim 19, wherein the defined relationship is defined by defining at least one function operating on the first data model, the second data model, or both the first and second data models to yield a result in the second data model, the first data model, or both the second and first data models, respectively.

21. The computer-implemented method of claim 20, wherein the at least one defined function includes a concatenate function for conversion from the first data model to the second data model and a parse function for conversion from the second data model to the first data model.

22. The computer-implemented method of claim 21, wherein the first data model has a structure comprising three data elements comprising a ‘

FirstName’

data element, a ‘

MiddleName’

data element, and a ‘

LastName’

data element;

the second data model has a structure comprising one data element comprising a ‘

FullName’

data element; and

the bi-directional map both converts the ‘

FirstName’

data element, the ‘

MiddleName’

data element, and the ‘

LastName’

data element to the ‘

FullName’

data element and converts the ‘

FullName’

data element to the ‘

FirstName’

data element, the ‘

MiddleName’

data element, and the ‘

LastName’

data element.

23. The computer-implemented method of claim 20, wherein the at least one defined function comprises:

at least one function to transform data from a numeric data model to an ordinal data model and from the ordinal data model to the numeric data model;

or

at least one function to convert data from a first time zone data model to a second time zone data model and from the second time zone data model to the first time zone data model;

or

at least one function to convert data from a first date format data model to a second date format data model and from the second date format data model to the first date format data model, and

wherein the at least one function in a function library and invoked from the function library when converting the content of a data store from the first data model to the second data model and the content of a data store from the second data model to the first data model.

24. A computer-implemented method of mapping between at least two data models, comprising:

defining a relationship between the first data model for a first source document and a second data model for a target format, including;

receiving a user-specified target format;

or

in the absence of the user-specified target format, defaulting to a predetermined target format;

generating a bi-directional map between the first data model and the second data model from at least portions of the source document, the target format, and the defined relationship;

storing the bi-directional map; and

converting the content of a data store from the first data model to the second data model and converting the content of a data store from the second data model to the first data model, wherein the bi-directional map is generated between the first and second data models by;

assigning, to each data element in contents of the source document, a variable, thereby defining a first set of variables for the source document;

assigning, to each data element in the target format, a variable, thereby defining a second set of variables for the source document;

receiving a first user input selecting a first subset of variables from the first set of variables;

receiving a second user input selecting a second subset of variables from the second set of variables to which the first subset of variables are to be mapped, wherein the first subset of variables and second subset of variables have different numbers of variables from each other;

performing a bi-directional interpolation between the first subset of variables and the second subset of variables based on the defined relationship;

generating a first map for mapping the first subset of variables to the second subset of variables based on results of the bi-directional interpolation; and

generating a second map for mapping the second subset of variables to the first subset of variables based on results of the bi-directional interpolation.