Hierarchical Time Series Tile Visualization
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Solution Overview
Problem
Managing and visualizing large volumes of operational data from industries such as oil and gas, metals, and semiconductors is challenging due to storage and processing limitations, requiring an efficient solution for data processing, storage, and visualization.
Innovation Solution
A computer-implemented method involving the generation of tiles and supertiles from time-series data at various resolutions, allowing for efficient storage and retrieval of aggregated data, enabling fast visualization and reducing computational load by organizing data in a hierarchical structure for responsive and interactive visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large volumes of operational data are stored and processed in traditional formats, then data completeness is maintained, but storage requirements and processing time increase significantly
Solution Approach 1:
The patent segments time series data into discrete tiles organized in a hierarchical tree structure. Each tile represents a specific time range and resolution level, allowing the system to process and retrieve only the necessary data segments rather than entire datasets. This segmentation enables efficient navigation to specific time periods and resolutions without loading unnecessary data into memory.
Solution Approach 2:
The patent introduces a resolution dimension to the traditional time-series data structure by creating multiple resolution levels (e.g., high resolution for detailed views, low resolution for overview). This dimensional transformation allows the system to serve different visualization needs from the same underlying data, reducing processing time for overview displays while maintaining access to detailed data when needed.
2Measurement precision
If high resolution data is retrieved for detailed visualization, then data precision is improved, but memory usage and network traffic increase
Solution Approach 1:
The patent implements local quality by storing and transmitting data at different resolution levels based on the specific viewing requirements. The system determines the appropriate resolution level needed for a given time range and visualization context, then retrieves only that specific resolution level rather than always using the highest resolution. This allows detailed visualization where needed while using lower resolution for broader contexts, optimizing memory usage.
3Ease of operation
If complete time series data is loaded into memory for analysis, then data accessibility is improved, but CPU cycles and memory consumption increase
Solution Approach 1:
The patent performs preliminary organization of time series data into a hierarchical tile structure during data ingestion, creating multiple resolution levels and organizing tiles in a tree structure with metadata. This preliminary action enables rapid retrieval of specific data segments without requiring loading of complete datasets into memory, improving both accessibility and efficiency during analysis operations.
4Speed
If data is organized in a detailed hierarchical structure for fast retrieval, then retrieval speed is improved, but device complexity increases
Solution Approach 1:
The patent implements a nested hierarchical structure where tiles are organized in a tree with multiple levels of aggregation. Each parent tile contains or references child tiles at higher resolution, creating a nested structure similar to Matryoshka dolls. This nesting enables the system to quickly retrieve overview data from parent tiles while providing seamless access to detailed child tiles when needed, achieving fast retrieval without requiring complex ad-hoc data aggregation during query processing.
Data Source
AI summary
A method comprises generating, from time series data, a plurality of tiles for each resolution of a plurality of resolutions, a first plurality of tiles associated with one resolution covering the same time period as a second plurality of tiles associated with another resolution, each tile having a common number of N values representing all measurements associated with a duration of time covered by the tile in the time series data; receiving a first user request specifying a first timestamp and a first resolution; determining that no tile is available based on the first timestamp and the first resolution; generating a first tile covering a first duration of time based on the first timestamp and the first resolution, a first number of measurements associated with the first duration of time being less than a second number of measurements associated with a second duration of time based on the first resolution; transmitting the first tile.