Lateral Data Propagation for Form Field Consistency
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Solution Overview
Problem
Existing automated form fill-in solutions fail to address consistency and nuanced issues among fields, adapt to specialized formatting rules, and provide form validation or quality assurance, leading to errors and inefficiencies in completing complex governmental forms.
Innovation Solution
A computer-implemented method utilizing Equivalence and Formatting rules to automatically propagate and format data across equivalent fillable fields within and across documents, reducing human error and increasing efficiency by minimizing interactions with data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated form fill-in products are used with extensive mapping from data sources to fillable fields, then form completion efficiency is improved, but the system fails to address consistency and nuanced issues among fields and requires continuous link availability
Solution Approach 1:
The patent segments the form completion process into distinct phases: data extraction from available sources, equivalence rule-based propagation across fields, and formatting rule-based adaptation. This segmentation allows the system to maintain reliability through structured data flow while achieving productivity through automated propagation, resolving the contradiction by making the system work effectively even when data source links are unavailable or intermittent.
Solution Approach 2:
The patent establishes equivalence rules and formatting rules in advance before form completion begins. These pre-defined rules create a robust framework that ensures data consistency across fields regardless of data source availability. The preliminary setup of propagation pathways allows the system to maintain reliability while achieving efficient form completion.
2Adaptability or versatility
If forms are updated periodically by governmental agencies, then forms remain current and compliant, but significant work is required to remap data to newly released forms, increasing complexity and time investment
Solution Approach 1:
The patent creates a universal equivalence rule framework that can adapt to different form versions and governmental agency requirements. The equivalence rules are designed to be form-agnostic, focusing on the logical relationships between fields rather than specific form structures. This universality allows the system to handle form updates with minimal remapping effort, reducing complexity while maintaining adaptability to new forms.
Solution Approach 2:
The patent uses formatting rules that can be adjusted to accommodate changes in form parameters and field requirements. When forms are updated, the system can modify formatting parameters (such as data formats, validation rules, and field mappings) without requiring complete remapping of the underlying equivalence relationships. This parameter-based approach reduces the complexity of adapting to new form versions.
3Reliability
If manual form filling is performed, then attention to detail can be applied, but the process is time-consuming and increases the likelihood of human error including inconsistencies and typographical errors
Solution Approach 1:
The patent implements automated validation and verification mechanisms that provide feedback on data consistency across fields. The equivalence rule propagation ensures that data entered in one field is automatically reflected in equivalent fields, with automated checks for consistency. This feedback mechanism maintains high data accuracy while eliminating the time-consuming nature of manual verification, resolving the contradiction between reliability and time loss.
Solution Approach 2:
The system performs self-service through automated equivalence rule propagation, where data entered in one field automatically populates equivalent fields without human intervention. This self-propagation mechanism eliminates typographical errors and inconsistencies while significantly reducing the time required for form completion compared to manual filling, while maintaining high data accuracy through automated consistency checks.
Data Source
AI summary
Systems and methods for efficient completion of form-fillable documents are presented. To minimize interactions with remote sources, in initializing a set of form-fillable documents, a single data access to a data source is made for field data of equivalent fillable fields in a set of form-fillable documents, of which there may be many that are equivalent (using the same base data). The accessed field data is then propagated throughout the equivalent fillable fields in the set of fillable documents. Similarly, upon the modification of the field data of a fillable field, the modified field data is then “laterally” propagated to equivalent fillable fields within the set of form-fillable documents. Still further, in saving data from the fillable fields, a single data access with the data source is made for each distinct field type among the form-fillable documents. Advantageously, consistency among equivalent fillable fields is maintained.