# A Systematic Review of Cyber Range Taxonomies: Trends, Gaps, and a Proposed Taxonomy
## 5 Discussion
### Design Decisions  
We argue that introducing generalized technology concepts (like virtualization, automation, scalability) still allows for adaptability without binding the taxonomy to specific tools (e.g., Docker, Chef). By formally introducing _Technology_ as a stand-alone dimension, our taxonomy now explicitly covers the complex range of tools and systems that enable robust simulation, monitoring, and scaling capabilities.  
In parallel, we opted to exclude testbeds from our taxonomy, acknowledging that their usage has evolved too broadly to pinpoint modern cyber range concepts effectively. Although this decision likely omitted certain historical works where \"testbed\" was synonymous with \"cyber range,\" it allowed us to keep our focus on core concepts surrounding _Technology_, _Infrastructure_, and _Architecture_.  
Likewise, we chose a taxonomy rather than an ontology to maintain a relatively accessible hierarchical structure for practitioners. While an ontology could have captured deeper interrelationships (e.g., synergy between AI-based agents and scenario design), it would also have introduced another level of complexity. Throughout this process, our findings consistently underscored the dynamic nature of cyber ranges, driven both by technological advances and evolving training demands.  
The question of whether to include _Econometrics_ in our proposed taxonomy was one of the dilemmas of this study. On the one hand, financial and economic considerations--such as cost-benefit analyses, return on investment, and budgetary constraints--can significantly influence how organizations adopt cyber range solutions ([PERSON] et al., 2018). On the other hand, our scoping review revealed that these factors appear only sporadically in the literature, with insufficient empirical grounding or standardized methodologies to measure them.  
Moreover, _Econometrics_ represents just one facet of a broader socio-technical landscape, encompassing political, organizational, and human behavioral factors. Including _Econometrics_ as the sole socio-technical dimension might skew classification unduly toward financial considerations while overlooking important influences like policy, governance, and workforce structures. Consequently, to maintain a focused, technologically grounded taxonomy, we opted to exclude _Econometrics_ from the final framework, prioritizing the more widely covered technological and functional dimensions. At the same time, we acknowledge that financial modeling and cost-benefit analyses are promising avenues for future work, potentially informing how resource constraints, risk assessments, and long-term sustainability factor into cyber range design and implementation.  
Finally, the iterative approach that led from an initial baseline taxonomy to the present proposed taxonomy illustrates how classification efforts in this domain are both systematic and exploratory. Consolidating _Technology_ under a separate dimension greatly reduced duplication and yet introduced new challenges, including naming overlaps (e.g., how \"tools\" appeared under _Scenario_, _Monitoring_, and _Technology_) and a higher level of abstraction in certain areas. Such trade-offs are inherent in taxonomy development and point to the need for ongoing re-validations as the cyber range landscape continues to evolve technologically, organizationally, and regulatory-wise.