Biodiversity genomics research increasingly relies on multi-view visualization tools to support comparative analyses spanning species identification, evolutionary factors, hierarchical taxonomic relationships, wildlife forensics, population structure analysis, and conservation planning, which place distinct demands on visualization design. Despite the growing prevalence of multi-view layouts in the genomics domain, systematic understanding of how they support domain-specific biological goals through task abstractions remains limited. This systematic literature review addresses these gaps by establishing a domain-task mapping framework that explicitly connects biodiversity genomics biological goals to visualization task abstractions through an evidence-based software engineering approach. Applying a dual-task taxonomy that includes genomic-specific tasks and comparative actions, this review analyzed 34 papers identified through a structured search across five databases, using active-learning-assisted screening and an LLM-assisted data-extraction workflow. The results identify characteristic task-flow structures for four biological goals using Markov chain analysis and summarize their universal and unique structural patterns. Furthermore, five challenge-solution themes are documented across the included papers, encompassing visualization, tool features, tasks, data integration, and user interface and experience. These findings provide evidence-based guidance for visualization designers creating biodiversity genomics tools and bioinformaticians seeking to understand how multi-view designs support complex analytical workflows.
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Siang et al. (2026) studied this question.
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