Generating object time series from data objects

• US 10,453,229 B2
• Filed: 09/29/2017
• Issued: 10/22/2019
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Palantir Technologies Incorporated
• Original Assignee: Palantir Technologies Incorporated
• Inventors: Sharma, Tilak, Chuang, Steve, Chiu, Rico, Shi, Andrew, Canfield, Lindsay, Kumar, Adit
• Primary Examiner(s): Nguyen, Vu
• Application Number:
  US15/720,455
• Publication Number:
  US 20180122112A1
• Time in Patent Office: 753 Days
• Field of Search: None
• CPC Class Codes: G06F 16/41 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/9027 Trees
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs

Abstract

Systems and methods are presented for representing non-numerical data objects in an object time series. An object time series of can be created by establishing one or more associations, each association including a mapping of at least one point in time with one or more objects that include properties and values. Visual representation of an object time series may include displaying non-numerical values associated with objects in the object time series in association with respective points in time.

Claims

1. A computer implemented method comprising:

by a computer system comprising one or more computer hardware processors and one or more storage devices,

receiving a plurality of objects, wherein each object of the plurality objects comprises a data container for properties, and wherein each property of the properties comprises one or more property types corresponding to one or more property values;

determining, from among the plurality of objects, a non-event object comprising a property value which has a non-numerical value;

determining, from among the plurality of objects, an event object based on an association of the event object with the non-event object;

generating an object time series based on a plurality of points in time, wherein a first point in time of the plurality of points in time is associated with at least the event object; and

causing presentation of a visual representation of the object time series including representations of the event object with the first point in time, the non-event object with at least one respective point in time, and the non-numerical value, and wherein the visual representation of the object time series further comprises the event object and the non-event object as connected with at least one respective point in time.

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

retrieving the non-numerical value from the non-event object, wherein retrieving the non-numerical value further comprises;

executing a function of the non-event object, wherein output of the function comprises the non-numerical value.

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

retrieving an additional non-numerical value from the object time series, wherein retrieving the additional non-numerical value further comprises;

executing a function of the object time series, wherein output of the function comprises the additional non-numerical value, and wherein the visual representation of the object time series further comprises the additional non-numerical value.

4. The computer implemented method of claim 3, wherein input of the function comprises a date or time corresponding to the first point in time.

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

retrieving at least one of the event object or the non-event object from the object time series, wherein retrieving the at least one of the event object or the non-event object further comprises;

executing a function of the object time series, wherein output of the function comprises the at least one of the event object or the non-event object.

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

slicing the object time series, wherein slicing the object time series further comprises;

identifying a subset of the plurality of points in time; and

generating a second object time series comprising the subset of the plurality of points in time, wherein generating the second object time series further comprises;

associating some points in time from the subset of the plurality of points in with one or more objects associated with the object time series.

7. The computer implemented method of claim 6, wherein the subset of the plurality of points in time correspond to at least one time period of a week, bi-week, month, quarter, or year.

8. A system comprising:

at least one computer hardware processor; and

data storage comprising instructions executable by the at least one computer hardware processor to cause the system to;

receive a plurality of objects, wherein each object of the plurality objects comprises a data container for properties, and wherein each property of the properties comprises one or more property types corresponding to one or more property values;

determine, from among the plurality of objects, a non-event object comprising a property value which has a non-numerical value;

determine, from among the plurality of objects, an event object based on an association of the event object with the non-event object;

receive an object time series comprising a plurality of points in time, wherein a first point in time of the plurality of points in time is associated with at least the event object; and

cause presentation of a visual representation of the object time series including representations of the event object with the first point in time, the non-event object with at least one respective point in time, and the non-numerical value, and wherein the visual representation of the object time series further comprises the event object and the non-event object as connected with at least one respective point in time.

9. The system of claim 8, wherein the instructions executable by the at least one computer hardware processor further cause the system to:

retrieve the non-numerical value from the non-event object, wherein retrieving the non-numerical value further comprises;

executing a function of the non-event object, wherein output of the function comprises the non-numerical value.

10. The system of claim 8, wherein the instructions executable by the at least one computer hardware processor further cause the system to:

retrieve an additional non-numerical value from the object time series, wherein retrieving the additional non-numerical value further comprises;

executing a function of the object time series, wherein output of the function comprises the additional non-numerical value, and wherein the visual representation of the object time series further comprises the additional non-numerical value.

11. The system of claim 8, wherein the instructions executable by the at least one computer hardware processor further cause the system to:

retrieve at least one of the event object or the non-event object from the object time series, wherein retrieving the at least one of the event object or the non-event object further comprises;

executing a function of the object time series, wherein output of the function comprises the at least one of the event object or the non-event object, and wherein input of the function comprises a date or time corresponding to the first point in time.

12. The system of claim 8, wherein the instructions executable by the at least one computer hardware processor further cause the system to:

slice the object time series, wherein slicing the object time series further comprises;

identifying a subset of the plurality of points in time; and

generating a second object time series comprising the subset of the plurality of points in time, wherein generating the second object time series further comprises;

associating some points in time from the subset of the plurality of points in with one or more objects associated with the object time series.

13. The system of claim 12, wherein identifying the subset of the plurality of points in time further comprises:

determining a time interval; and

selecting the subset from the plurality of points in time that are within the time interval.

14. The system of claim 8, wherein the instructions executable by the at least one computer hardware processor further cause the system to:

sample the object time series, wherein sampling the object time series further comprises;

determining a time interval;

identifying a subset of the plurality of points in time according to the time interval, wherein at least two points in time from the subset are separated by the time interval; and

generating a second object time series comprising the subset of the plurality of points in time, wherein generating the second object time series further comprises;

associating some points in time from the subset of the plurality of points in with one or more objects associated with the object time series.