Ontology-Based Software Framework Generation
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Solution Overview
Problem
In business software development, the transfer of ideas from business people to system analysts and then to programmers introduces errors and distortions, leading to costly mistakes during implementation, testing, and deployment.
Innovation Solution
A system and method that uses semantic modeling and business rules to generate a software framework by receiving input from users to create ontologies, mapping business requirements to IT ontologies, and generating a software framework that includes business object models and business process models, utilizing tools like ontology-based information extraction and rule-based reasoners to validate and minimize errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If requirements are transferred through multiple hands (business people, analysts, architects, programmers), then the idea can be refined and adapted, but errors and distortions are introduced
Solution Approach 1:
The patent introduces an ontology-based semantic model as an intermediary artifact that captures requirements in a standardized format. This mediator allows multiple stakeholders to contribute their expertise while maintaining a single source of truth, reducing distortions caused by manual transfers between different roles.
Solution Approach 2:
The system creates a formal ontology copy of the business requirements that can be independently validated and processed. This copied representation serves as a reliable reference that can be shared across all stakeholder groups without introducing additional errors during transmission.
2Adaptability or versatility
If manual conversion from business perspective to IT perspective is performed, then business requirements can be translated into technical specifications, but errors and distortions occur during conversion
Solution Approach 1:
The patent changes the parameter representation by mapping business requirements into a standardized ontology framework with defined classes, properties, and relationships. This parameter transformation enables automated validation and reduces conversion errors by providing a structured target format for the translation process.
Solution Approach 2:
The manual mechanical process of requirement conversion is replaced with an automated semantic mapping system that uses ontology alignment algorithms. This substitution eliminates human error in the conversion process while maintaining the ability to translate between business and IT perspectives.
3Adaptability or versatility
If existing software tools are used without integration, then tool functionality is available, but errors and distortions occur during manual integration
Solution Approach 1:
The patent merges multiple existing software tools into an integrated framework where ontologies serve as the common data structure. This integration allows tools to work together seamlessly, sharing requirements and specifications through the standardized ontology interface, thereby eliminating errors from manual integration processes.
Data Source
AI summary
A software framework based on semantic modeling and business rules, in which a method implemented in a data processing system, includes: receiving input from one or more first users to generate a first ontology describing a software requirement; and receiving input from one or more second users to map the first ontology to a second ontology describing software tools. The data processing system generates a software framework using the input that is received to map the first ontology that describes the software requirement to the second ontology that describes the software tools.