Analysis System Redundancy Elimination for Time Series Data
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Solution Overview
Problem
In data analysis, sharing processes and data between users is challenging due to differences in analysis target time segments, sensors, process orders, programs, and parameters, leading to redundant data generation and inefficiencies.
Innovation Solution
An analysis system executes processes using time-series data and past analysis data through an analysis chain graph structure, implementing redundancy elimination by skipping processes that match past objects or data blocks, and storing only new data outputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If analysis processes are executed for each user independently using their favorite tools and languages, then each user can perform analysis according to their preferences, but data conversion takes considerable time and analysis efficiency is reduced
Solution Approach 1:
The patent introduces a standardized data exchange format as an intermediary between different analysis tools and languages. This format acts as a common language that enables seamless data conversion without time loss, resolving the contradiction between maintaining user analysis preferences and eliminating conversion time.
Solution Approach 2:
The patent creates a universal data exchange standard that can be used across different analysis tools, languages, and user preferences. This multi-functional format allows any user to exchange analysis data with any other user without conversion issues, maintaining adaptability while eliminating conversion time.
2Adaptability or versatility
If each user performs analysis from scratch using the same data source, then analysis can be customized for each user's specific needs, but analysis efficiency is reduced due to redundant processing
Solution Approach 1:
The patent implements a mechanism where analysis results are pre-calculated and stored in a standardized format. When a user needs analysis data, the system checks if the analysis has already been performed and retrieves the pre-calculated results, eliminating redundant processing while maintaining the ability to customize analysis when needed.
Solution Approach 2:
The patent merges individual user analysis processes into a shared analysis framework. By combining multiple analysis requests into a single analysis execution when possible, the system achieves both customization for individual users and efficiency through shared processing resources.
3Adaptability or versatility
If analysis data is stored in various locations in various formats, then data can be stored according to different tool requirements, but data understanding becomes difficult and data exchange efficiency is reduced
Solution Approach 1:
The patent applies local quality by maintaining different storage formats in different locations according to specific tool requirements, while simultaneously introducing a standardized exchange format that ensures data understanding. Each location can store data in its optimal format, but the standardized format ensures interoperability and comprehension across the system.
Data Source
AI summary
The analysis system executes an analysis process which takes as input data at least portions of: time series data of a plurality of instances of value data which each include times and values; and analysis data which includes data which has been outputted by previous analysis processes. Each of the one or more objects is a process definition conforming to a user operation. In the analysis process, the analysis system skips at least one of: an execution of a process conforming to an object which matches any previous object; an execution of a process conforming to an object for a scope block and process description, among a plurality of scope blocks which constitute the scope to be analyzed, which match a scope block and process description which are associated with any stored data block; and/or the storage of a data block which matches any stored data block.