A Comprehensive Evaluation Framework for Virtual Reality Applications in Biological Data Visualization: Metrics, Validation, and Expert Assessment

The absence of standardized evaluation frameworks for virtual reality applications in specialized domains makes it difficult to assess quality and compare different systems. This research develops a complete evaluation framework for immersive VR applications with special emphasis on biological data visualization systems. The evaluation framework integrates standard software engineering metrics with domain-specific VR measurement tools. The framework provides measurable metrics for immersion depth and interaction accuracy to address existing assessment challenges in VR methodologies. The approach was validated through a VR application designed for biological network visualization, enabling researchers to explore gene-disease associations using real data from the National Center for Biotechnology Information. The evaluation process involved 20 biology domain experts who specialized in molecular biology and genetics as well as bioinformatics and cell biology. The results showed excellent performance across all metrics with 99.29% task success rate, 86.375 System Usability Scale score, 4.61/5 immersion rating, and 98.2% interaction accuracy across seven VR interaction types. The framework delivers essential objective measures for VR-specific characteristics while maintaining compatibility with established usability metrics. The framework fills the existing need for standardized VR evaluation methods by offering practical tools to assess immersive scientific applications. The research develops evaluation standards for VR in scientific visualization and creates a validated framework which other specialized VR applications can use with domain-specific assessment methods.