Mashup Data Snapshot Capture for Decision Audit Trails
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Solution Overview
Problem
Storing and sharing live data from mashups presents challenges, particularly in understanding the reasoning behind decisions made using this data, as existing technologies lack mechanisms for capturing and retrieving live data snapshots effectively.
Innovation Solution
A computer system and method for taking and sharing snapshots of mashups, which includes a display interface, user input device interface, and a processor to facilitate displaying mashups, allowing users to input indications to take snapshots, store live data, and optionally provide reasons for snapshot capture, along with scheduling and sharing capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If live data from mashups is stored and shared, then data availability and accessibility are improved, but the ability to understand decision-making reasoning deteriorates due to lack of context capture
Solution Approach 1:
The system captures snapshots of mashup data at specific moments before decisions are made or changes occur. By proactively capturing the state of live data, user inputs, and contextual information in advance, the system preserves the decision-making context without requiring complex post-hoc analysis tools.
Solution Approach 2:
The snapshot artifact serves as an intermediary that bridges the gap between live mashup data and decision-making analysis. It captures and stores contextual information, user inputs, and data states in a structured format that can be later retrieved and analyzed to understand the reasoning behind decisions.
2Reliability
If snapshots of mashup data are captured and stored, then data retrieval and analysis capabilities are improved, but storage requirements and system complexity increase
Solution Approach 1:
The system extracts only the essential and relevant information from live mashup data to create snapshot artifacts. Instead of storing complete copies of all data, it captures key parameters, user inputs, contextual metadata, and decision-relevant information, reducing storage requirements while maintaining retrieval accuracy.
Solution Approach 2:
The snapshot system transforms live continuous data into discrete captured states with specific parameters. By changing the data representation from continuous live streams to discrete snapshot artifacts with defined metadata structures, the system optimizes storage efficiency while preserving analytical value.
3Adaptability or versatility
If users are prompted to provide reasons for snapshot capture, then collective intelligence and knowledge sharing are improved, but user interaction time and operational complexity increase
Solution Approach 1:
The system implements optional user prompts for providing reasons or contextual information about snapshot captures. Users can provide partial information (just essential reasons) or excessive information (detailed contextual data) based on their needs, rather than being required to complete comprehensive forms. This reduces time loss while still capturing valuable knowledge for collective intelligence.
Data Source
AI summary
A computer system includes a display interface, a user input device interface, and a processor cooperatively operable with the display interface and the user input device interface. The processor is configured to facilitate displaying, via the display interface, a mashup or service; interacting with the user to input, via the user input device interface, an indication to take a snapshot of the mashup or service being currently displayed via the display interface; and storing a snapshot artifact of live data from the mashup or service at the instant the snapshot is taken.