An ontology-based approach to designing a NoSQL database for semi-structured and unstructured health data

Area of Science:

• Health Informatics
• Database Management
• Ontology Engineering

Background:

• Healthcare generates massive Big Data from ICT applications.
• NoSQL databases are favored for Big Health Data but lack standardized design methods.
• Efficient data modeling is crucial for NoSQL performance in healthcare.

Purpose of the Study:

• To propose an ontology-based approach for designing NoSQL database schemas for Big Health Data.
• To develop an algorithm for generating NoSQL schemas using ontologies and query characteristics.
• To evaluate the performance of the proposed design against traditional relational models.

Main Methods:

• Developed a primary healthcare ontology to model domain knowledge.
• Proposed an algorithm for NoSQL schema design using ontologies, query sets, and performance requirements.
• Implemented and tested the schema design targeting MongoDB.
• Compared performance with a relational model on the MongoDB cloud platform.

Main Results:

• Demonstrated the effectiveness of the ontology-based approach for Big Health Data.
• The proposed NoSQL design showed improved performance compared to the relational model.
• Successful schema generation and validation on MongoDB.

Conclusions:

• Ontology-driven schema design is a viable method for Big Health Data in NoSQL databases.
• The proposed approach enhances data retrieval efficiency and resource optimization in healthcare.
• This methodology provides a framework for designing effective NoSQL databases for specialized domains.