Method and system for capturing, storing and retrieving events and activities

• US 20030120461A1
• Filed: 12/21/2001
• Published: 06/26/2003
• Est. Priority Date: 12/21/2001
• Status: Active Grant

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Montalvo Roel, IIa K., Strilich, James A., Mets, Christiaan M.H.
• Granted Patent: US 7,496,591 B2
• Time in Patent Office: Days
• US Class Current: 702/182
• CPC Class Codes: G05B 23/0264 Control of logging system, e.g. decision on which data to store; time-stamping measurements
• CPC Class Codes: G06F 16/258 Data format conversion from or to a database
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

A method and system for processing the data of any one of a variety of processes without doing a total custom design for each process. The system includes a computer and database that communicates with various monitors of the process to gather, store and retrieve the process data. A user interfaces to the computer via a client device. The computer includes a program that identifies events and activities of the process based on input from the user or from process data collected as the process runs. Attributes of the events and activities are also identified. These events, activities and attributes are classified according to a data structure that includes event types, activity types and attribute types. Storage volumes are allocated to each of the defined event and/or types, activity types for storage and retrieval of the data by attribute type. The composite event or activity data can be retrieved in multiple views, such as row, column, graphical and the like.

Claims

1. A method for processing the data of a process comprising:

(a) identifying one or more events and/or activities of said data and one or more attributes thereof;

(b) classifying each of said events and/or activities and each of said attributes according to a data structure that comprises an event and/or activity type and a plurality of attribute types to provide defined event and/or activity types for said events and/or activities and defined attribute types for said attributes; and

(c) allocating one or more storage volumes to each of said defined event and/or activity types for storage and retrieval of said data by attribute type.

2. The method of claim 1, wherein step (c) allocates at least one storage volume to each of said defined attribute types.

3. The method of claim 2, wherein said data structure further comprises a time stamp, and wherein said at least one storage volume of a first one of said events is accessed according to said time stamp for storage and retrieval of said attributes corresponding to said first event.

4. The method of claim 2, wherein at least one attribute of a plurality of said events and/or activities is common to at least one of said defined attribute types, and wherein step (c) allocates said at least one storage volume to all of said common attributes.

5. The method of claim 1, wherein step (c) allocates a first one of said storage volumes for storage of values of said data for said attributes of at least a first one of said defined attribute types, and further comprising compressing said data which is stored in said first one of said storage volumes according to identity of said values of said attributes of consecutive events and/or activities that have been allocated for storage in said first one of said storage volumes.

6. The method of claim 5, wherein said data structure further comprises a time stamp, and wherein said first one of said storage volumes is accessed according to said time stamp for storage and/or retrieval of said values, and wherein said values of a first event are retrieved from said first storage volume by using the value of a first time stamp for said first event or of a second time stamp value of a second one of said events that is earlier in time than said first time stamp value.

7. The method of claim 1, wherein step (c) allocates a first one of said storage volumes for storage of values of said attributes of at least one of said defined attribute types, wherein said attributes of said at least one defined attribute type are static, and further comprising optimizing data storage in said first one of said storage volumes by omitting storage of a static value.

8. The method of claim 1, wherein said process is one of a plurality of processes, and wherein steps (a), (b) and (c) are performed for each of said plurality of processes using said data structure.

9. The method of claim 8, wherein at least two of said plurality of processes are different from one another.

10. The method of claim 1, further comprising presenting data values of different ones of said events and/or activities that are defined as different event and/or activity types in any one of a plurality of formats.

11. The method of claim 10, wherein said plurality of formats are selected from the group consisting of:

row format, column format and chart format.

12. The method of claim 1, further comprising developing a map structure for mapping diverse external names of said attributes and/or field contents thereof to a common internal attribute name and/or field content.

13. A computer system for processing the data of a process comprising:

means for identifying one or more events and/or activities of said data and one or more attributes thereof;

means for classifying each of said events and/or activities and each of said attributes according to a data structure that comprises an event and/or activity type and a plurality of attribute types to provide defined event and/or activity types for said events and/or activities and defined attribute types for said attributes; and

means for allocating one or more storage volumes to each of said defined event and/or activity types for storage and retrieval of said data by attribute type.

14. The computer system of claim 13, wherein said means for allocating allocates at least one storage volume to each of said defined attribute types.

15. The computer system of claim 14, wherein said data structure further comprises a time stamp, and wherein said at least one storage volume of a first one of said events is accessed according to said time stamp for storage and retrieval of said attributes corresponding to said first event.

16. The computer system of claim 14, wherein at least one attribute of a plurality of said events and/or activities is common to at least one of said defined attribute types, and wherein said means for allocating allocates said at least one storage volume to all of said common attributes.

17. The computer system of claim 13, wherein said means for allocating allocates a first one of said storage volumes for storage of values of said data for said attributes of at least a first one of said defined attribute types, and further comprising compressing said data which is stored in said first one of said storage volumes according to identity of said values of said attributes of consecutive events and/or activities that have been allocated for storage in said first one of said storage volumes.

18. The computer system of claim 17, wherein said data structure further time stamp, and wherein said first one of said storage volumes is accessed according to said time stamp for storage and/or retrieval of said values, and wherein said values of a first event are retrieved from said first storage volume by using the value of a first time stamp for said first event or of a second time stamp value of a second one of said events that is earlier in time than said first time stamp value.

19. The computer system of claim 13, wherein said means for allocating allocates a first one of said storage volumes for storage of values of said attributes of at least one of said defined attribute types, wherein said attributes of said at least one defined attribute type are static, and further comprising optimizing data storage in said first one of said storage volumes by omitting storage of a static value.

20. The computer system of claim 13, wherein said process is one of a plurality of processes, and wherein said means for classifying provides for each of said plurality of processes defined event and/or activity types and defined attribute types using said data structure.

21. The computer system of claim 20, wherein at least two of said plurality of processes are different from one another.

22. The computer system of claim 13, further comprising means for presenting data values of different ones of said event and/or activities that are defined as different event and/or activity types in any one of a plurality of formats.

23. The computer system of claim 22, wherein said plurality of formats is selected from the group consisting of:

row format, column format and chart format.

24. the computer system of claim 13, further comprising means for developing a map structure for mapping diverse external names of attributes and/or field contents thereof to a common internal attribute name and/or field content.

25. A memory media for controlling a computer that processes the data of a process, said memory media comprising:

first means for controlling said computer to identify one or more events and/or activities of said data and one or more attributes thereof;

second means for controlling said computer to classify each of said events and/or activities and each of said attributes according to a data structure that comprises an event and/or activity type and a plurality of attribute types to provide defined event and/or activity types for said events and/or activities and defined attribute types for said attributes; and

third means for controlling said computer to allocate one or more storage volumes to each of said defined event and/or activity types for storage and retrieval of said data by attribute type.