Quality-aware data interfaces for unstructured data

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Solution Overview

Problem

Current data visualization systems for unstructured data often filter out lower quality or relevance data, preventing users from viewing variability and potentially important information, and do not allow interactive exploration of data quality levels.

Innovation Solution

A method and system that analyze unstructured data to infer structural elements, assign quantized data quality levels, and generate structured data with associations, enabling user interfaces to visually display varying data qualities and allow users to filter based on quality levels, thus avoiding premature commitment to quality thresholds and allowing interactive exploration.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If only higher quality data structures are displayed to the user, then the clarity of data presentation is improved, but the user loses access to potentially important information and cannot view variability in data quality

Engineering Contradiction:

Improvedata quality thresholdVSAvoidlower quality data

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The patent segments data quality into discrete quantized levels (e.g., 1-5 scale) and allows users to filter by specific quality thresholds. This segmentation enables users to selectively view data at different quality levels rather than receiving a binary filtered view, thus preserving access to potentially important lower-quality information while maintaining the ability to focus on high-quality data when needed.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically adjusts data presentation by allowing users to interactively change quality thresholds and filters. Users can move between different quality level configurations, enabling them to explore data variability and calibrate quality standards against their own judgment without being locked into a fixed filtering approach.

Inventive Principle:

Principle #15Dynamics

2Productivity

If a fixed quality threshold is applied to filter data, then the amount of data presented to the user is reduced, but the user cannot interactively explore data quality levels or calibrate against their own judgment

Engineering Contradiction:

Improvedata processing efficiencyVSAvoiduser interaction flexibility

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The system replaces fixed quality thresholds with dynamic, user-adjustable filters. Users can interactively modify quality level thresholds and apply different filter configurations based on their specific needs and judgment, enabling both efficient data processing and flexible exploration of data quality dimensions.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system provides feedback mechanisms that allow users to view data at different quality levels and adjust their filtering preferences accordingly. Users can explore how different quality thresholds affect the data presentation and calibrate the system's quality assessment against their own judgment through iterative interaction.

Inventive Principle:

Principle #23Feedback

3Measurement precision

If lower quality data is completely filtered out, then the presentation clarity is improved, but the user loses the ability to view data variability and potentially important information

Engineering Contradiction:

Improvedata quality standardVSAvoiduser control over data viewing

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

By segmenting data into quantized quality levels rather than applying a single binary filter, the system enables users to selectively view data across the full quality spectrum. Users can choose to examine lower-quality data when needed while maintaining the ability to focus on high-quality data for routine operations, thus preserving both presentation clarity and user control.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system allows users to apply partial filtering by quality level rather than complete filtering. Users can view data at specific quality thresholds or ranges, enabling them to access potentially important lower-quality information without being overwhelmed by all data, thus balancing presentation clarity with user control.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11580129B2Quality-aware data interfaces

Publication Date: 2023.02.14 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

A set of unstructured data is analyzed to infer structural elements from the unstructured data, and quantized data quality levels, indicative of data quality in the structural elements, are assigned to the structural elements. A set of structured data is generated to include the structural elements inferred from the unstructured data and associations between respective ones of the structural elements in the set of structured data and the corresponding quantized quality levels assigned to the structural elements. The set of structured data, including the associations between respective ones of the structural elements and the corresponding quantized quality levels assigned to the structural elements, is provided to a user interface application to enable the user interface application to visually display varying data qualities in the set of structured data.