Higher Education Data Model Standardizing Identifier Structures
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Solution Overview
Problem
Higher education institutions face complexity in sharing information across disparate data systems due to unique data structures, leading to limited interoperability and difficulty in understanding the true system of record, hindering effective data analysis and management.
Innovation Solution
A method is introduced to normalize various higher education data structures using a common language and identifiers, creating a single organizational structure that allows different systems to share and analyze data, enabling a comprehensive view of student information from recruitment to alumni activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If each application uses a uniquely defined data structure with no commonality, then each system can be independently designed and maintained, but interoperability between systems becomes virtually impossible without significant investment in complex technology
Solution Approach 1:
The patent applies universality by creating a common data structure framework that can serve multiple different applications and systems. The framework defines universal data elements and relationships that work across recruitment, academic affairs, student services, and alumni relations systems, allowing one standardized structure to fulfill multiple specialized needs without requiring separate custom implementations for each system
Solution Approach 2:
The patent uses an intermediary approach by introducing a standardized data structure framework that acts as a mediator between disparate application systems. This framework layer translates and harmonizes data between different systems, enabling interoperability without requiring direct complex integrations between each pair of systems, thus reducing overall integration complexity
2Adaptability or versatility
If each application has its own unique data structure, then each system can be customized for specific functions, but understanding which system is the true system of record becomes nearly impossible
Solution Approach 1:
The framework provides universal data element definitions that maintain consistency across systems while allowing system-specific implementations. Each system can customize its use of the standardized elements for its specific functions, but the underlying universal structure ensures that the system of record for each data element is clearly identified and consistent across all applications
Solution Approach 2:
The patent applies homogeneity by standardizing data element definitions, data types, and relationships across all systems. This homogeneous approach ensures that the same data element (e.g., student name, enrollment status) has the same meaning and structure regardless of which system contains it, making it possible to clearly identify the system of record and maintain data consistency across the institution
3Quantity of substance
If multiple data sources with different data structures are used, then comprehensive data coverage is achieved, but the ability to manage operations through complex data analysis is very limited
Solution Approach 1:
The framework enables comprehensive data coverage by providing a universal structure that can accommodate data from multiple sources including academic affairs, student services, financial aid, and alumni relations systems. The standardized structure allows data from these diverse sources to be integrated and analyzed together without requiring complex custom integration logic for each data source
Solution Approach 2:
The patent merges multiple data sources into a unified data model by combining data from various institutional systems into the standardized framework. This merging process consolidates previously siloed data into a coherent whole that can be analyzed comprehensively, reducing the complexity that would otherwise be required to integrate and analyze data from separate systems
Data Source
AI summary
A method of organizing higher education data is provided. The method includes: (a) providing a plurality of higher education data sources, each of the plurality of higher education data sources including respective higher education data organized using corresponding higher education identifiers; and (b) generating a single higher education identifier organizational structure for accessing the respective higher education data from each of the plurality of higher education data sources.