Cross-model filtering

Patent metadata

Field	Value
Publication number	US-9720972-B2
Application number	US-201313919857-A
Country	US
Kind code	B2
Filing date	Jun 17, 2013
Priority date	Jun 17, 2013
Publication date	Aug 1, 2017
Grant date	Aug 1, 2017

Abstract

Presenting data from different data providers in a correlated fashion. The method includes performing a first query on a first data set controlled by a first entity to capture a first set of data results. The method further includes performing a second query on a second data set controlled by a second entity to capture a second set of data results. The method includes receiving a selection of one or more results from the first data set. The method further includes using the one or more selected results, consulting a relationship ontology that correlates data stored in different data stores controlled by different entities, to identify one or more relationships between data in the selected results set and the second data set.

First claim

What is claimed is:

1. A method of constructing data from different data providers in a correlated fashion, the method being performed by one or more processors of a computer system, the method comprising:
performing a first query on a first data set controlled by a first entity to capture a first set of data results;
performing a second query on a second data set controlled by a second entity to capture a second set of data results, wherein the second query is generated independently from the first query such that the second query is distinct from, and not dependent on, the first query;
receiving a selection of one or more results from the first set of data results;
using the selection from the first set of data results to consult a relationship ontology that correlates data stored in different data stores controlled by different entities and further to identify one or more relationships between data in the selection from the first set of data results and the second set of data results subsequent to performing both the first query and the second query, wherein the identified one or more relationships between the data in the selection from the first set of data results and the second set of data results are stored in the relationship ontology, and wherein at least one of the identified one or more relationships stored in the relationship ontology is manually defined;
constructing a new query over the second data set based on identifying the one or more relationships between the data in the selection from the first set of data results and the second set of data results; and
performing the new query on the second data set such that results from the new query are correlated with the selection from the first set of data results.

2. The method of claim 1 further comprising:
performing additional operations on the second set of data results based on the identified one or more relationships between the data in the selection from the first set of data results and the second set of data results.

3. The method of claim 2 , wherein performing the additional operations on the second set of data results comprises highlighting an element in the second set of data results.

4. The method of claim 2 , wherein performing the additional operations on the second set of data results comprises analyzing results in the second set of data results.

5. The method of claim 2 , wherein performing the additional operations on the second set of data results comprises categorizing results in the second set of data results.

6. The method of claim 2 , wherein performing the additional operations on the second set of data results comprises sorting results in the second set of data results.

7. The method of claim 2 , wherein performing the additional operations on the second set of data results comprises filtering results in the second set of data results.

8. The method of claim 1 , further comprising:
displaying a correlation between the first set of data results and the second set of data results.

9. The method of claim 1 , wherein the second query is performed prior to receiving the selection of the one or more results from the first set of data results.

10. The method of claim 1 , wherein the second set of data results is displayed in a bar chart.

11. A system for constructing data from different data providers in a correlated fashion, the system comprising:
one or more processors; and
one or more computer readable hardware storage devices having stored thereon computer executable instructions that are executable by at least one of the one or more processors to cause the system to:
perform a first query on a first data set controlled by a first entity to capture a first set of data results;
perform a second query on a second data set controlled by a second entity to capture a second set of data results, wherein the second query is generated independently from the first query such that the second query is distinct from, and not dependent on, the first query;
receive a selection of one or more results from the first set of data results;
use the selection from the first set of data results to consult a relationship ontology that correlates data stored in different data stores controlled by different entities and further to identify one or more relationships between data in the selection from the first set of data results and the second set of data results subsequent to performing both the first query and the second query, wherein the identified one or more relationships between the data in the selection from the first set of data results and the second set of data results are stored in the relationship ontology, and wherein at least one of the identified one or more relationships stored in the relationship ontology is manually defined;
construct a new query over the second data set based on identifying the one or more relationships between the data in the selection from the first set of data results and the second set of data results; and
perform the new query on the second data set such that results from the new query are correlated with the selection from the first set of data results.

12. The system of claim 11 , wherein the computer executable instructions further cause the system to perform additional operations on the second set of data results based on the identified one or more relationships between the data in the selection from the first set of data results and the second set of data results.

13. The system of claim 12 , wherein performing the additional operations on the second set of data results comprises highlighting an element in the second set of data results.

14. The system of claim 12 , wherein performing the additional operations on the second set of data results comprises categorizing results in the second set of data results.

15. The system of claim 12 , wherein performing the additional operations on the second set of data results comprises sorting results in the second set of data results.

16. The system of claim 12 , wherein performing the additional operations on the second set of data results comprises filtering results in the second set of data results.

17. The system of claim 11 , wherein the computer executable instructions further cause the system to display a correlation between the first set of data results and the second set of data results.

18. The system of claim 11 , wherein the first data set is stored in a first table that includes column labels and the second data set is stored in a second table that also includes column labels, and wherein the computer executable instructions further cause the system to:
identify a first column of information in the first table, the first column including substantially similar information as a second column of information in the second table;
identify a first column label corresponding to the first column, the first column label being named differently than a second column label corresponding to the second column; and
in the relationship ontology, correlate the first column of information in the first table with the second column of information in the second table even though the first column label is named differently than the second column label.

19. The system of claim 18 , wherein the first column label is expressed using a first language while the second column label is expressed using a second language.

20. A physical computer readable hardware storage device comprising computer executable instructions that are executable by one or more processors to cause

Assignees

• Microsoft Technology Licensing Llc
• Microsoft Technology Licensing Llc

Inventors

• Faghihi Rezaei Pedram
• Netz Amir M
• Baumgartner Patrick J

Classifications

• G06F16/24564 Primary

  Applying rules; Deductive queries · CPC title

• G06Q30/06 Primary

  Buying, selling or leasing transactions · CPC title

• G06F16/24553

  of query operations · CPC title

• G06F16/215

  Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors · CPC title

• G06F17/30507 Primary

  Physics · mapped topic