Adaptive ontology driven dimensions acquisition, automated schema creation, and enriched data in time series databases
Various embodiments described herein relate to a contextualized time series database and/or contextualized time series data consumption. In this regard, a request to generate contextualized time series data related to one or more assets is received. The request includes a user identifier indicating an identity of a user associated with the request. In response to the request, telemetry data associated with the one or more assets is contextualized, based on metadata and a set of data dimensionality filters associated with the user identifier, to generate the contextualized time series data. Furthermore, the contextualized time series data is allocated within a datastore configured for the user identifier to facilitate obtaining one or more insights with respect to the contextualized time series data.
1. A system, comprising:
one or more processors;
a memory; and
one or more programs stored in the memory, the one or more programs comprising instructions configured to:
receive, via a user-interactive electronic interface, an application programming interface (API) command request to generate contextualized time series data related to one or more assets, the API command request comprising a user identifier indicating an identity of a user associated with the API command request; and
in response to the API command request:
determine whether telemetry data associated with the one or more assets is enriched with metadata;
enrich the telemetry data with functional metadata, spatial metadata, asset metadata, and algorithm parameters based on the determination that the telemetry data is not enriched with the metadata, wherein the metadata includes functional metadata, spatial metadata, asset metadata, and algorithm parameters related to contextualization of the telemetry data;
contextualize, based on (i) the metadata related to the one or more assets and (ii) a set of data dimensionality filters configured based on respective dimensionality information associated with a format structure for a datastore configured for the user identifier, the enriched telemetry data associated with the one or more assets to generate the contextualized time series data;
allocate the contextualized time series data within the datastore configured for the user identifier;
obtain one or more insights with respect to the contextualized time series data allocated within the datastore associated with the user identifier; and
render a visual representation of the one or more insights via the user-interactive electronic interface.
2. The system of claim 1 , wherein the metadata is first metadata, and the one or more programs further comprising instructions configured to:
parse the telemetry data based on second metadata associated with dimensionality for the set of data dimensionality filters.
3. The system of claim 1 , the one or more programs further comprising instructions configured to:
parse the telemetry data based on event data associated with the one or more assets.
4. The system of claim 1 , the one or more programs further comprising instructions configured to:
parse the telemetry data based on alarm data associated with the one or more assets.
5. The system of claim 1 , the one or more programs further comprising instructions configured to:
format the contextualized time series data based on the user identifier.
6. The system of claim 1 , the one or more programs further comprising instructions configured to:
filter the contextualized time series data based on the set of data dimensionality filters.
7. The system of claim 1 , the one or more programs further comprising instructions configured to:
organize the contextualized time series data based on an ontological tree structure that captures relationships among different portions of the contextualized time series data.
8. The system of claim 1 , the one or more programs further comprising instructions configured to:
process the telemetry data related to the one or more assets to determine data related to the one or more assets; and
generate attributes for the one or more assets based on one or more classifications with respect to the data related to the one or more assets.
9. The system of claim 1 , the one or more programs further comprising instructions configured to perform a specific type of operation corresponding to the contextualized time series data based on header data.
10. A method, comprising:
at a device with one or more processors and a memory:
receiving, via a user-interactive electronic interface, an application programming interface (API) command request to generate contextualized time series data related to one or more assets, the API command request comprising a user identifier indicating an identity of a user associated with the API command request; and
in response to the API command request:
determining whether telemetry data associated with the one or more assets is enriched with metadata;
enriching the telemetry data with functional metadata, spatial metadata, asset metadata, and algorithm parameters based on the determination that the telemetry data is not enriched with the metadata, wherein the metadata includes functional metadata, spatial metadata, asset metadata, and algorithm parameters related to contextualization of the telemetry data;
contextualizing, based on (i) the metadata related to the one or more assets and (ii) a set of data dimensionality filters configured based on respective dimensionality information associated with a format structure for a datastore configured for the user identifier, the enriched telemetry data associated with the one or more assets to generate the contextualized time series data;
allocating the contextualized time series data within the datastore configured for the user identifier;
obtaining one or more insights with respect to the contextualized time series data allocated within the datastore associated with the user identifier; and
rendering a visual representation of the one or more insights via the user-interactive electronic interface.
11. The method of claim 10 , wherein the metadata is first metadata, and the contextualizing comprising parsing the telemetry data based on second metadata associated with dimensionality for the set of data dimensionality filters.
12. The method of claim 10 , the contextualizing comprising parsing the telemetry data based on event data associated with the one or more assets.
13. The method of claim 10 , the contextualizing comprising parsing the telemetry data based on alarm data associated with the one or more assets.
14. The method of claim 10 , the contextualizing comprising formatting the contextualized time series data based on the user identifier.
15. The method of claim 10 , the contextualizing comprising filtering the contextualized time series data based on the set of data dimensionality filters.
16. The method of claim 10 , the allocating the contextualized time series data comprising organizing the contextualized time series data based on an ontological tree structure that captures relationships among different portions of the contextualized time series data.
17. The method of claim 10 , further comprising:
processing the telemetry data related to the one or more assets to determine data related to the one or more assets; and
generating attributes for the one or more assets based on one or more classifications with respect to the data related to the one or more assets.
18. A computer program product comprising at least one computer-readable storage medium having program instructions embodied thereon, the program instructions executable by a processor to cause the processor to:
receive, via a user-interactive electronic interface, an application programming interface (API) command request to generate contextualized time series data related to one or more assets, the API command request comprising a user identifier indicating an identity of a user associated with the API command request; and
in response to the API command request:
determine whether telemetry data associated with the one or more assets is enriched with metadata;
enrich the telemetry data with functional metadata, spatial metadata, asset metadata, and algorithm parameters based on the determination that the telemetry data is not enriched with the metadata, wherein the metadata includes functional metadata, spatial metadata, asset metadata, and algorithm parameters related to contextualization of the telemetry data;
contextualize, based on (i) the metadata related to the one or more assets and (ii) a set of data dimensionality filters configured based on respective dimensionality information associated with a format structure for a datastore configured for the user identifier, the enriched telemetry data associated with the one or more assets to generate the contextualized time series data;
allocate the contextualized time series data within the datastore configured for the user identifier;
obtain one or more insights with respect to the contextualized time series data allocated within the datastore associated with the user identifier; and render a visual representation of the one or more insights via the user-interactive electronic interface.
19. The computer program product of claim 18 , wherein the metadata is first metadata, and the program instructions further executable by the processor to cause the processor to:
parse the telemetry data based on second metadata associated with dimensionality for the set of data dimensionality filters.
20. The computer program product of claim 18 , the program instructions further executable by the processor to cause the processor to:
parse the telemetry data based on event data associated with the one or more assets.
21. The computer program product of claim 18 , the program instructions further executable by the processor to cause the processor to:
parse the telemetry data based on alarm data associated with the one or more assets.