TRUST FRAMEWORK FOR PLATFORM DATA

• US 20170054611A1
• Filed: 04/11/2016
• Published: 02/23/2017
• Est. Priority Date: 08/17/2015
• Status: Active Grant

• Current Assignee: Accenture Global Solutions Limited (Accenture PLC)
• Original Assignee: Accenture Global Solutions Limited (Accenture PLC)
• Inventors: Tiell, Steven C.
• Granted Patent: US 9,928,290 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/113 Details of archiving lifecycle management in storage systems G06F3/0649; backup systems G06F11/1446
• CPC Class Codes: G06F 16/162 Delete operations erasing in storage systems G06F3/0652
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 21/6227 where protection concerns the structure of data, e.g. records, types, queries
• CPC Class Codes: G06F 21/6236 between heterogeneous systems
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: H04L 43/04 Processing captured monitoring data, e.g. for logfile generation
• CPC Class Codes: H04L 43/0876 Network utilisation, e.g. volume of load or congestion level
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Techniques are described for determining and employing trust metrics for entities interacting with a super-platform. An end-user may interact with multiple individual platforms of different types. The individual platforms may generate data based on the interactions with end-user(s). The data from the various individual platforms may be received, ingested, stored, analyzed, aggregated, and/or otherwise processed by a super-platform. The super-platform may provide the data, aggregate data, and/or data analysis results to data consumer(s) through a marketplace associated with the super-platform. In some implementations, entities such as data providers, data manipulators, and/or data consumers may rate one another and, based on the rating(s), a trust metric may be determined that indicates a trust level of an entity.

Claims

1. A computer-implemented method comprising:

storing, on one or more storage devices associated with a super-platform, data generated at a plurality of individual platforms, the data associated with at least one end-user of the plurality of individual platforms;

determining data tracking information including one or more events associated with the data, the one or more events including a distribution of the data to a data consumer;

based at least partly on the data tracking information, determining a data consumer trust metric that indicates a level of trust in the data consumer; and

presenting the data consumer trust metric to the at least one end-user.

2. The method of claim 1, wherein the data tracking information includes a blockchain associated with the data.

3. The method of claim 1, further comprising:

determining a data provider trust metric that indicates a level of trust in at least one of an end-user or an individual platform that generated the data, the data provider trust metric based at least partly on at least one trust rating provided by at least one data consumer; and

incorporating the data provider trust metric into the data tracking information associated with the data.

4. The method of claim 1, further comprising:

aggregating the data from multiple individual platforms to generate aggregate data; and

determining aggregate data tracking information including one or more events associated with the aggregate data.

5. The method of claim 4, wherein the data tracking information includes an event that indicates the aggregating of the data and that includes a pointer to the aggregate data tracking information associated with the aggregate data.

6. The method of claim 4, further comprising:

determining an aggregate trust metric for the aggregate data based at least partly on individual trust metrics for portions of the data that are aggregated to generate the aggregate data; and

incorporating the aggregate trust metric into the aggregate data tracking information associated with the aggregate data.

7. The method of claim 1, further comprising:

receiving one or more restrictions on use of the data, the one or more restrictions provided by the at least one end-user;

monitoring the use of the data to determine a degree of compliance, by the data consumer, with the one or more restrictions; and

updating the data consumer trust metric based on the determined degree of compliance.

8. The method of claim 1, wherein the data consumer trust metric is further based at least partly on at least one trust rating provided by the at least one end-user.

9. The method of claim 1, wherein the plurality of individual platforms include at least two of:

an e-commerce platform configured to provide an e-commerce service;

a retail platform configured to support retail operations of a physical store;

a media platform configured to provide an online media service;

a mobile computing device;

an Internet of Things (IoT) computing device;

or

an in-vehicle computer.

10. A system comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor, the memory storing instructions which, when executed by the at least one processor, cause the at least one processor to perform operations comprising;

storing, on one or more storage devices associated with a super-platform, data generated at a plurality of individual platforms, the data associated with at least one end-user of the plurality of individual platforms;

determining data tracking information including one or more events associated with the data, the one or more events including a distribution of the data to a data consumer;

based at least partly on the data tracking information, determining a data consumer trust metric that indicates a level of trust in the data consumer; and

presenting the data consumer trust metric to the at least one end-user.

11. The system of claim 10, wherein the data tracking information includes a blockchain associated with the data.

12. The system of claim 10, the operations further comprising:

determining a data provider trust metric that indicates a level of trust in at least one of an end-user or an individual platform that generated the data, the data provider trust metric based at least partly on at least one trust rating provided by at least one data consumer; and

incorporating the data provider trust metric into the data tracking information associated with the data.

13. The system of claim 10, the operations further comprising:

aggregating the data from multiple individual platforms to generate aggregate data; and

determining aggregate data tracking information including one or more events associated with the aggregate data.

14. The system of claim 13, wherein the data tracking information includes an event that indicates the aggregating of the data and that includes a pointer to the aggregate data tracking information associated with the aggregate data.

15. The system of claim 13, the operations further comprising:

determining an aggregate trust metric for the aggregate data based at least partly on individual trust metrics for portions of the data that are aggregated to generate the aggregate data; and

incorporating the aggregate trust metric into the aggregate data tracking information associated with the aggregate data.

16. One or more computer-readable storage media storing instructions which, when executed by at least one processor, cause the at least one processor to perform operations comprising:

storing, on one or more storage devices associated with a super-platform, data generated at a plurality of individual platforms, the data associated with at least one end-user of the plurality of individual platforms;

determining data tracking information including one or more events associated with the data, the one or more events including a distribution of the data to a data consumer;

based at least partly on the data tracking information, determining a data consumer trust metric that indicates a level of trust in the data consumer; and

presenting the data consumer trust metric to the at least one end-user.

17. The one or more computer-readable storage media of claim 16, the operations further comprising:

receiving one or more restrictions on use of the data, the one or more restrictions provided by the at least one end-user;

monitoring the use of the data to determine a degree of compliance, by the data consumer, with the one or more restrictions; and

updating the data consumer trust metric based on the determined degree of compliance.

18. The one or more computer-readable storage media of claim 16, wherein the data consumer trust metric is further based at least partly on at least one trust rating provided by the at least one end-user.

19. The one or more computer-readable storage media of claim 16, wherein the plurality of individual platforms include at least two of:

an e-commerce platform configured to provide an e-commerce service;

a retail platform configured to support retail operations of a physical store;

a media platform configured to provide an online media service;

a mobile computing device;

an Internet of Things (IoT) computing device;

or

an in-vehicle computer.

20. The one or more computer-readable storage media of claim 16, the operations further comprising:

aggregating the data from multiple individual platforms to generate aggregate data; and

determining aggregate data tracking information including one or more events associated with the aggregate data.