Energy Management Data Transformation Logging for Traceability
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Solution Overview
Problem
Energy management systems face challenges in accurately tracking and transforming energy data across complex networks, leading to uncertainties in decision-making due to lack of transparent and traceable data transformation processes.
Innovation Solution
The implementation of a data transformation logging component and extension components within the energy management system that generate unique identifiers for data streams, log transformations, and provide interfaces for user input and visualization, enabling users to modify and trace data transformations, and add metadata for context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data transformation processes are implemented in EM systems, then data quality and reliability are improved, but system complexity and difficulty of tracking transformations increase
Solution Approach 1:
The patent segments the data transformation process into distinct, trackable components by implementing logging mechanisms that record each transformation event separately. This includes logging the original data, transformation applied, parameters used, and resulting data, creating discrete units that can be individually tracked and audited without overwhelming system complexity.
Solution Approach 2:
The patent introduces logging components as intermediary elements between data sources and data consumers. These logging components capture and store transformation information without interfering with the primary data flow, acting as mediators that provide transparency and traceability while maintaining system efficiency.
2Loss of information
If comprehensive logging of data transformations is implemented, then data traceability is improved, but data storage requirements and processing overhead increase
Solution Approach 1:
The patent applies local quality by implementing selective logging strategies where not all data transformations are logged with the same level of detail. Instead, logging intensity and detail are adjusted based on the specific transformation type, data sensitivity, and business requirements, optimizing storage usage while maintaining necessary traceability.
Solution Approach 2:
The patent utilizes parameter changes by implementing configurable logging parameters that allow the system to adjust what information is logged, how detailed the logging is, and how frequently transformations are recorded. This enables dynamic optimization of storage requirements based on changing business needs and data characteristics.
3Ease of operation
If users are provided with interfaces to modify and trace data transformations, then ease of operation is improved, but system complexity and processing time increase
Solution Approach 1:
The patent implements preliminary action by pre-generating and storing metadata about data transformations, including transformation types, parameters, and results. This preliminary preparation allows users to quickly query and analyze transformation history without triggering time-consuming real-time processing, thereby improving ease of operation while minimizing processing time impacts.
Data Source
AI summary
Systems and methods for monitoring, logging, and managing data transformations and data streams of energy management (EM) data energy data sources.