Data Management System Using Template-Based Construct Automation
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Solution Overview
Problem
Conventional data management systems require users to manually define each data collection and storage construct without sharing commonalities, leading to inefficiencies and the need for repeated manual redefinition when constructs change.
Innovation Solution
A system that allows users to input data sets and automatically defines data collection and storage constructs, including user interfaces and queries, based on user input, enabling updates and validation without additional user input for storage constructs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If users manually define each data collection construct without sharing commonalities, then each construct can be precisely customized, but the time and effort required for definition increases significantly
Solution Approach 1:
The patent segments data collection constructs into reusable templates and individual customizations. Templates contain commonalities that can be shared across multiple constructs, while specific fields can be customized as needed. This segmentation allows users to define once and reuse multiple times, reducing definition time while maintaining precision.
Solution Approach 2:
The patent implements copying mechanisms where users can create templates from existing data collection constructs and reuse them across multiple instances. This copying approach preserves the original precision while eliminating redundant definition work, as commonalities are copied rather than redefined.
2Stability of the object's composition
If users manually redefine entire data collection constructs when changes are needed, then consistency across the system is maintained, but the complexity and time required for updates increases
Solution Approach 1:
The patent segments data collection constructs into templates and instances, allowing updates to be applied at the template level. When a template is updated, all instances automatically inherit the changes, maintaining system consistency without requiring manual updates to each instance, thus reducing update complexity.
Solution Approach 2:
The patent creates universal templates that serve multiple data collection instances. A single template update propagates universally to all instances, maintaining consistency across the system while simplifying the update process from complex individual updates to a single universal update.
3Manufacturing precision
If users manually define each data storage construct without sharing commonalities, then each storage construct can be precisely configured, but the effort and time for definition increases
Solution Approach 1:
The patent segments data storage constructs into reusable templates that capture common configuration patterns. These templates can be applied to multiple storage constructs, preserving precise configuration where needed while eliminating redundant definition work through template-based inheritance.
Solution Approach 2:
The patent implements copying of storage construct templates to create new storage constructs with pre-configured commonalities. This allows precise configuration to be copied and reused, maintaining accuracy while significantly reducing the time required to define new storage constructs.
4Adaptability or versatility
If the system requires user input for defining both data collection and data storage constructs, then user control over the system is maximized, but the ease of operation decreases
Solution Approach 1:
The patent performs preliminary actions by automatically generating data storage construct templates based on user-defined data collection templates. This preliminary automation maintains user control over the data model while eliminating the need for users to manually define storage constructs, thereby improving ease of operation without sacrificing adaptability.
Solution Approach 2:
The patent implements self-service where the system automatically generates storage construct definitions from collection construct definitions. The system serves itself by inferring storage requirements from collection requirements, reducing the burden on users while maintaining flexibility through configurable template relationships.
Data Source
AI summary
Systems and methods for entering and storing data. User input defining a data set is received. A data collection construct including a data entry user interface for inputting data in the data set is defined using the user input. A data storage construct including queries for retrieving the data is automatically defined based on the user input. Additional user input indicating modifications to the data set is received. The data collection construct, the data storage construct, and the queries are automatically updated based on the additional user input indicating modifications to the data set.