Compacted Electronic Data Structures from Declarative Documents

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Solution Overview

Problem

Existing data transformation methods require manual programming to customize electronic data structures, leading to inefficiencies and unnecessary memory consumption due to empty fields, particularly in sparse datasets.

Innovation Solution

A computerized approach that uses a structured document in a declarative language to define data transformation conditions, allowing automatic generation of customized electronic data structures with empty fields removed, thereby reducing storage consumption.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual programming is used to customize electronic data structures, then flexibility and adaptability are improved, but device complexity and time consumption increase

Engineering Contradiction:

Improvedata structure customization flexibilityVSAvoidprogramming complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system allows users to define data transformation conditions through simple structured documents without requiring programming knowledge. The interpreter program automatically generates customized electronic data structures based on user-defined conditions, enabling non-programmers to perform complex data structure customization tasks.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

An interpreter program acts as an intermediary between the user's structured document and the data transformation process. The interpreter translates high-level user conditions into executable data structure generation logic, eliminating the need for users to write complex transformation code directly.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If complete electronic data structures with all possible fields are generated, then adaptability to different programs is improved, but memory consumption increases due to empty fields

Engineering Contradiction:

Improveprogram compatibilityVSAvoidmemory consumption

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The system generates electronic data structures with field-level customization, where only fields that contain relevant data according to user-defined conditions are included. This allows different parts of the data structure to have different properties - populated fields for relevant data and exclusion of empty fields - optimizing both adaptability and memory efficiency.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The compaction process identifies and removes empty fields from electronic data structures while preserving the essential data and structure needed for program compatibility. This discarding of unnecessary empty fields reduces memory consumption without sacrificing the adaptability of the data structure.

Inventive Principle:

Principle #34Discarding and recovering

3Manufacturing precision

If data transformation is performed manually, then precision and control are improved, but productivity decreases

Engineering Contradiction:

Improvedata transformation accuracyVSAvoiddata processing efficiency

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

Users define transformation conditions in advance using structured documents before the actual data transformation occurs. The interpreter program then automatically executes the transformation according to these pre-defined conditions, ensuring both precision and high productivity without manual intervention during the transformation process.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system replaces manual mechanical data transformation processes with an automated interpreter program that reads structured documents and generates transformed data structures automatically. This substitution maintains transformation accuracy while dramatically improving processing efficiency and productivity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12405955B2Automatically transforming data into a compacted electronic data structure

Publication Date: 2025.09.02 SAS INSTITUTE INC

AI summary

One example described herein can involve a system that receives, from a user, a structured document that describes one or more conditions selected by the user to customize one or more electronic data structures. The system can also query a database to retrieve data from the database. The system can then execute an interpreter program, which can ingest the structured document and the data, identify a subset of the data that satisfies the condition(s), and generate the one or more electronic data structures based on the subset of the data. The electronic data structure(s) can include the identified subset of the data and exclude a remainder of the data. The system can compact the electronic data structure(s) by removing empty fields therein. The system can then provide the compacted data structure(s) to the user.