Integrated Research Analytics Platform Data Standardization
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Solution Overview
Problem
Higher educational and research institutions face challenges in managing and analyzing research data due to the lack of integrated systems that track and maintain data integrity, consistency, and communication between independent information retrieval systems, leading to duplication of efforts and limitations in research data analytics.
Innovation Solution
The Institutional Research Analytics Platform (IRAP) provides a comprehensive analytics system with an integrated database scheme that standardizes research process flows, organizational tasks, and research outcomes, allowing for the calculation and display of research performance indicators, enabling informed decision-making by tracking and analyzing data from multiple sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If independent information retrieval systems are used to store research information, then each system can be designed according to pre-defined research activities, but data integrity and consistency are lost and duplication of development efforts occurs
Solution Approach 1:
The patent merges multiple independent information retrieval systems into a single integrated research analytics platform that consolidates data from diverse sources while maintaining standardized schemas, thereby preserving data integrity and eliminating duplication while still accommodating different research activities through configurable parameters
2Ease of manufacture
If independent systems are used for each research activity, then system design is simplified for specific purposes, but system communication and integration are limited
Solution Approach 1:
The patent implements a universal research analytics platform that can handle multiple research activities and data types through a single integrated system with configurable parameters and standardized interfaces, eliminating the need for separate independent systems while maintaining ease of use through consistent design patterns
3Loss of information
If multiple heterogeneous data sources are integrated, then comprehensive research analytics are achieved, but data mapping and standardization complexity increases
Solution Approach 1:
The patent employs parameter-based data standardization where heterogeneous data from multiple sources are transformed into a unified schema through configurable mapping parameters and transformation rules, enabling comprehensive data integration while managing complexity through systematic parameter management rather than ad-hoc customization
Data Source
AI summary
A research analytics system and method, includes an Internet-based data storage service maintaining, using an integrated database scheme, standardized research process flows, organizational tasks, and research outcomes for a plurality of research programs. The system maintains definitions of research performance indicators, identifies targets for the research performance indicators that are aligned with goals associated with a research organization, maps performance-related data from various data sources to the integrated database scheme and stores the standardized research process flows, the organizational tasks, and the research outcomes, grouped by the research programs. The system determines values of the research performance indicators using metrics, displays the research performance indicator values and associated targets, performs analysis using the stored performance-related data in order to determine an affect of the performance-related data for the research programs on the research performance indicator values, and adjusts the research performance indicators and the targets.