Quality-Enriched Event Annotation in Complex Event Processing
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Solution Overview
Problem
Business experts and decision-makers face challenges in trusting and understanding aggregated event data from complex event processing systems, which affects their ability to make informed decisions due to the lack of quality information about event sources and their contributions.
Innovation Solution
The implementation of methods to manage data quality by generating quality-enriched events through complex event processing rules, annotating them with quality information, and providing event source quality information, allowing for better decision-making and adaptation of business processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If event data is aggregated to higher abstraction levels using complex event processing systems, then the accessibility and business relevance of event data is improved, but the trustworthiness and comprehensibility of the aggregated data deteriorates due to lack of quality information
Solution Approach 1:
The patent introduces quality information as an intermediary element that mediates between the raw event data and the aggregated complex events. This quality information acts as a trust indicator that accompanies aggregated events, allowing business experts to assess the reliability of the data without needing to understand the complex aggregation process. The quality information serves as a bridge that maintains trustworthiness while enabling accessibility.
Solution Approach 2:
The patent segments the quality information into distinct components that can be independently evaluated. By breaking down the quality assessment into separate attributes, the system provides granular quality information that helps business experts understand specific aspects of data reliability while maintaining the overall accessibility of aggregated events.
2Reliability
If quality information is added to enriched events through annotation, then the decision-making reliability is improved, but the data processing complexity increases
Solution Approach 1:
The patent applies preliminary action by computing and attaching quality information to events at the point of aggregation, rather than performing separate quality assessment operations later. This approach integrates quality computation into the event processing pipeline itself, avoiding additional processing steps and reducing overall system complexity while maintaining high decision-making reliability.
3Adaptability or versatility
If event data is consolidated from multiple distributed sources, then the business process adaptability is improved, but the difficulty of assessing event value increases due to heterogeneous data quality
Solution Approach 1:
The patent creates a universal quality information framework that works across multiple heterogeneous event sources. The quality information structure is designed to be source-agnostic, providing a unified approach to assessing event value regardless of the originating system. This universal framework enables business experts to evaluate events from diverse sources using the same quality metrics, reducing assessment difficulty while maintaining business process adaptability.
Data Source
AI summary
Implementations of the present disclosure include methods for managing data quality for event data. In some implementations, methods include receiving, at one or more computing devices, a plurality of events, each event comprising event data and being generated by an event source in response to a real-world activity, processing, using the one or more computing devices, the plurality of events using one or more complex event processing (CEP) rules to generate a complex event, in response to generating the complex event, annotating the complex event with quality information corresponding to each of the plurality of events to provide a quality-enriched event, and publishing the quality-enriched event.