Spatio-temporal data processing systems and methods
View Patent ↗This disclosure relates to systems and methods for collecting, integrating, processing, distributing, and analyzing spatial and/or spatio-temporal information associated with a variety of data sources and/or locations. In some embodiments, systems and methods described herein allow for collection and integration of information included in one or more spatial and/or spatio-temporal data streams and/or other related information that may be utilized in connection with one or more analytical processes. In certain embodiments, the disclosed embodiments may allow a user to, among other things, interact with spatio-temporal information associated with a variety of diverse data sources, generate visualizations using such data, and/or perform desired analytical queries based on the data.
1. A method of processing spatio-temporal data performed by a system comprising a processor and a non-transitory computer-readable storage medium storing instructions that, when executed, cause the system to perform the method, the method comprising:
receiving a plurality of data streams associated with a plurality of diverse distributed data sources, the plurality of data streams comprising data having a spatial component and a temporal component;
extracting from the plurality of data streams a plurality of metadata segments and a plurality of data segments, wherein extracting the plurality of metadata segments and the plurality of data segments further comprises:
generating a plurality of intermediate segments based on the plurality of data streams using transformation information included in at least one transformation library; and
extracting the plurality of metadata segments and the plurality of data segments from the plurality of intermediate segments;
generating a response to a user request using an service engine based on the extracted plurality of metadata segments and plurality of data segments; and
transmitting the response to a system associated with the user.
2. The method of claim 1 , wherein the plurality of data segments comprise measured data information.
3. The method of claim 1 , wherein the plurality of data segments comprise modeled data information.
4. The method of claim 1 , wherein the response comprises a visualization based on the plurality of metadata segments and the plurality of data segments.
5. The method of claim 1 , wherein the response comprises a computation result from a predictive model based on the plurality of metadata segments and the plurality of data segments.
6. The method of claim 1 , wherein the response comprises at least one metric based on the plurality of metadata segments and the plurality of data segments.
7. The method of claim 1 , wherein the method further comprises storing the metadata segments in a metadata database and the data segments in a data segment database.
8. The method of claim 1 , wherein the metadata segments comprise one or more data samples of the data included in the plurality of data streams.
9. The method of claim 1 , wherein the metadata segments comprise aggregated information associated with the data included in the plurality of data streams.
10. The method of claim 1 , wherein the method further comprises identifying a portion of the plurality of data segments comprising outlier data based on data associated with the portion exceeding a threshold relative to data associated with other data segments within a particular temporal and spatial range relative to the portion.
11. The method of claim 10 , wherein the method further comprises generating the response based on data segments other than the identified portion.
12. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor of a computer system, cause the computer system to perform a method comprising:
receiving a plurality of data streams associated with a plurality of diverse distributed data sources, the plurality of data streams comprising data having a spatial component and a temporal component;
extracting from the plurality of data streams a plurality of metadata segments and a plurality of data segments, wherein extracting the plurality of metadata segments and the plurality of data segments further comprises:
generating a plurality of canonical segments based on the plurality of data streams using transformation information included in at least one transformation library;
extracting the plurality of metadata segments and the plurality of data segments from the plurality of canonical segments;
generating a response to a user request using an service engine based on the extracted plurality of metadata segments and plurality of data segments; and
transmitting the response to a system associated with the user.
13. The non-transitory computer-readable storage medium of claim 12 , wherein the response comprises a visualization based on the plurality of metadata segments and the plurality of data segments.
14. The non-transitory computer-readable storage medium of claim 12 , wherein the response comprises at least one analytical metric based on the plurality of metadata segments and the plurality of data segments.
15. The non-transitory computer-readable storage medium of claim 12 , wherein the plurality of data segments comprise at least one of measured data information and modeled data information.
16. The non-transitory computer-readable storage medium of claim 12 , wherein the metadata segments comprise one or more data samples of the data included in the plurality of data streams.
17. The non-transitory computer-readable storage medium of claim 12 , wherein the metadata segments comprise aggregated information associated with the data included in the plurality of data streams.
18. The non-transitory computer-readable storage medium of claim 12 , wherein the non-transitory computer-readable storage medium further comprises instructions configured to cause the computer system to perform a method comprising identifying a portion of the plurality of data segments comprising outlier data based on data associated with the portion exceeding a threshold relative to data associated with other data segments within a particular temporal and spatial range relative to the portion and generating the response based on data segments other than the identified portion.