Correlating Instance Data Across Applications via Continuation Tables
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Solution Overview
Problem
Existing systems face challenges in maintaining consistent data for multiple instances of an activity across various applications, as these applications often operate independently and are not configured to share or correlate data using a common identifier, leading to issues in tracking and processing activities across different departments or organizations.
Innovation Solution
The solution involves using Payload/Milestone events and Enable-Continuation events to transmit and correlate data, where identifiers from one application are used to index records in a continuation data table, allowing for synchronization of data across different applications, and implementing a continuation data table to manage out-of-order data by hiding it until sequential data is received.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple application programs process instances independently without a common identifier system, then each application can operate autonomously and maintain its own data consistency, but data correlation across applications becomes impossible and tracking activity instances across departments fails
Solution Approach 1:
The patent introduces a database server as an intermediary component that receives instance data from multiple application programs and maintains a unified view of all instances. The database server correlates data across applications using instance identifiers stored in the database, enabling cross-application tracking without requiring changes to the autonomous application programs. This mediator approach resolves the contradiction by providing data correlation capability while preserving application independence.
2Loss of information
If a common identifier system is implemented across all applications to correlate data, then data correlation and tracking across applications improves, but applications must modify their software which increases implementation complexity and cost
Solution Approach 1:
The patent segments the data correlation function into a separate database server component, distinct from the application programs. Each application program generates instance identifiers locally and stores them in the database, but the actual correlation logic resides in the database server. This segmentation allows applications to remain unchanged while still achieving data correlation through the centralized database structure, thereby reducing implementation complexity.
Solution Approach 2:
Each application program generates its own instance identifiers autonomously without requiring coordination with other applications or external systems. The applications self-service by creating and storing their own identifiers in the database, enabling correlation without modifying their core processing logic. This self-service approach simplifies implementation as each application can be configured independently.
3Productivity
If out-of-order data is processed immediately upon receipt, then data processing speed improves, but data accuracy decreases as sequential data may not be complete
Solution Approach 1:
The patent implements preliminary buffering of out-of-order instance data in the database server before final processing. When data arrives out of sequence, it is temporarily stored in the database with its original timestamp and sequence information preserved. Once all expected data arrives in the correct sequence, the system processes the complete dataset, ensuring data accuracy while maintaining the ability to handle varying arrival speeds.
Solution Approach 2:
The system uses feedback mechanisms to monitor data arrival patterns and determine when complete sequential data is available for processing. The database server tracks which instances have received all expected data events, and only triggers final processing when completeness is confirmed. This feedback-based approach balances processing speed with data accuracy by processing data as soon as it is complete rather than immediately upon partial receipt.
Data Source
AI summary
Instance data is transmitted for Payload/Milestone events and for Enable-Continuation events. Payload/Milestone event data contains information describing an instance and/or providing a time of one or more portions of the processing of an instance. Included in the Enable-Continuation event data is an identifier associated with an instance by a first application and an identifier associated with the same instance by another application. The identifiers are placed in a continuation data table which is used to index the appropriate record of an instance data table. Out-of-order data for an instance is hidden from view until sequentially prior data for the instance is received.