Displays are a useful tool for users and operators to understand information quickly. Configural displays are effective in supporting focus and divided attention tasks through the use of emergent features. Emergent features are highly salient and are generally used to support divided attention task However, due to the salience of emergent features, a potential performance costs to focused attention tasks arises with configural displays. To address this cost, semantic mapping has been used to map salience techniques to information needed by focus attention tasks to increase their saliency (Bennett & Walters, 2001; Bennett et al., 2000). Semantic mapping is the process of mapping the domain constrains to the display, which in turn is mapped to the users capabilities and limitations to understand that domain data. The objective of this dissertation is to extend the use of semantic mapping to address potential performance costs of configural displays for hierarchical domains using the scenario-based training (SBT) instructor domain. Two studies were conducted to examine the effects of salience application and salience type on data extraction accuracy and response time performances at low-level, mid-level, high-level, and a remediation task. The first study examined the effects of one salience technique mapped to the display. This study employed a 2(low or mid application) X 3(baseline, color techniques, and alphanumeric techniques) mixed model design in which 63 participants completed 3 blocks of 32 trails each using displays with the salience techniques mapped to either low- or mid-level data. Results from the first study showed that salience type had a significant impact on multi-level data extraction performance, but interactions were not found. The second study changed the manipulation of application and mapped two salience techniques display at the same time, using either the same technique or a combination of different techniques. The same experimental design was utilized and 65 participants completed study 2. Results of study 2 showed that different application resulted in greater improvements of performance and specific salience combinations were found better support data extraction performance. Across study analyses were also performed and revealed that more salience is not better than less salience. Instead it is the specific mapping of salience type and application which improves performance the most. Overall, these findings have major implications for theories of semantic mapping, attention and performance, and display design of hierarchical domains.