Assertional Simulation for Alternative Semantic Data Views
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Solution Overview
Problem
Current systems for decision-making in business and other situations lack the ability to effectively handle and present alternative points of view, as they do not readily facilitate the presentation of various potential structures or organizations, and existing simulation systems fail to enable the handling of such alternatives.
Innovation Solution
A system for decision support that includes a reference data set configured from multiple data sources, where constraints such as semantic constraints are intentionally omitted, and a method of de-referencing that extracts data elements independent of their ontology-specific definitions or structure-specific relationships, allowing for the creation of a flat data file that represents both ontology-derived and structure-derived constraints, enabling the generation of a reference data model that is independent of the original structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is organized according to a fixed ontology and structure in source data systems, then data consistency and meaning are preserved, but the ability to present alternative points of view and diverse organizational structures is limited
Solution Approach 1:
The patent segments data into two independent components: content (the actual data elements) and structure (the ontology and relationships). By separating these components, the system can present the same content in multiple structural configurations, enabling alternative points of view without compromising data consistency. The content is extracted from its original ontological constraints and can be reorganized into different structures as needed.
Solution Approach 2:
The patent introduces an intermediary layer (the simulation system) that sits between the source data and the presentation layer. This intermediary can load data in its original structured form, then transform and reorganize it into alternative structures for different points of view. The intermediary handles the complexity of multiple ontologies and structures, shielding users from this complexity while enabling versatile data presentation.
2Adaptability or versatility
If semantic constraints are imposed on data items to ensure meaningful interpretation, then data accuracy is maintained, but flexibility in reorganizing and presenting data is reduced
Solution Approach 1:
The patent segments the data system into content elements and semantic constraints. Content elements are extracted and stored independently of their original semantic constraints. When data is presented, the system can apply different semantic constraints or interpretations to the same content, enabling flexible reorganization while maintaining reliability through controlled application of constraints during presentation rather than during storage.
Solution Approach 2:
The patent makes the application of semantic constraints dynamic rather than static. Instead of permanently binding content to specific semantic constraints in the source system, the system allows constraints to be applied, modified, or removed dynamically during the data loading and presentation process. This enables the same content to be reliably interpreted in multiple different semantic frameworks.
3Adaptability or versatility
If data is extracted independent of its original ontology and structure, then versatility in data presentation is improved, but loss of contextual information and relationships may occur
Solution Approach 1:
The patent uses an intermediary system that captures and preserves contextual information during the extraction process. When data is extracted from source systems, the intermediary records not just the content elements but also metadata about their original context, relationships, and constraints. This contextual information is stored separately and can be applied or referenced during presentation, ensuring that versatility in reorganization does not lead to loss of meaningful context.
Solution Approach 2:
The patent implements a nested structure where content elements are extracted from their original ontological containers, but the ontological context is preserved as a separate layer. The system creates a nested representation where the core content can be freely reorganized while the original contextual information remains available as an outer layer that can be applied or referenced as needed, preventing information loss while enabling versatility.
Data Source
AI summary
Semantic mediation is accomplished by initially constructing a model of domain-specific requirements associated with one or more nodes in a hierarchy of semantically linked nodes representing encoded aspects of a domain. Followed by determining a target node in the hierarchy for application of at least one property characterized in a topical profile of a first entity. And further followed by producing a first-entity, target node-specific application model that reflects impacts of properties and characteristics of the topical profile with the model of domain-specific requirements through informatic convolution of the model of domain-specific requirements with the topical profile of the first entity.