## 7 Case Studies
This breakdown led to the creation of image I in Figure 5. Initially, without prioritising any aspects, all elements were treated equally, requiring users to adjust the weightings to achieve their desired outcome. Image II shows the result of placing more weight on the graph's aesthetics, leading to a more stylised look. Image III then shifts focus, reducing the weight on aesthetics while increasing it on situation and purpose, demonstrating a balance between these elements. Finally, image IV illustrates the successful balance among aesthetics, situation, and purpose, resulting in an inspiring visualisation. The VisAlchemy tool proved its worth in this case study by enabling us to refine our visual output to meet specific goals. This method allowed us to create an informative, innovative, and inspiring visual. The success of this approach in our first case study highlights its flexibility and effectiveness in tackling various data visualisation challenges. Figure 4: Using our five-part framework (see Figure 2), phrases can be built using the keywords, see Section 5. We suggest concatenating key terms together with appropriate transition words and linking phrases. For instance, generate a “visualisation (subject) with a grid-like shape (aesthetics)for a research report (context) to explain the data (task/application) and for a desktop user (user), shown with keywords in **bold** and linking phrases in _italics_. These steps directly map to the Radio buttons in VisAlchemy and are individually controlled by adapting their weighting, see Figure 3.  
Figure 5: **(I) The first image was generated with equal weighting on all stages. (II) More emphasis on the aesthetics. (III) We removed any priority to the aesthetics and style and focused on the data itself. (IV) Once we were happy with the data, we began to focus specifically on overlaying the data as a meaningful visualisation while trying to avoid standard chart types. (V) is the final output**  
The second case study began with the following: \"Data that the students union collated from a student survey. Make tables for charting the data and an attractive pie chart for describing the data below in a fun way\", see Figure 6. Image I was produced using the prompt created by methodically deconstructing the original prompt into our seven-stage framework: **Subject:** fun and attractive. **Aesthetics:** tables and pie chart. **Situation:** students union survey. **Purpose:** data description. **User:** students and decision makers. **Blacklist:** presentation. **Parameters:** accuracy and aesthetic appeal. Image II was created by adding the term infographic to the prompt. **Subject:** fun and attractive infographic, which resulted in a cluttered infographic. Image III was created by adding some vocabulary to the prompt: **aesthetics**: tables, pie, bar, line; **blacklist**: cluttered, which resulted in a less cluttered infographic with more chart types. IV. at this stage, we had a less cluttered infographic, but the other chart types distracted us from the purpose of visualising the responses to the questions. Therefore, **aesthetics**: tables and pie chart was restored. It resulted in an infographic that could inspire the creation of a visualisation to display student data in a fun and attractive way. VisAlchemy once again proved its prowess in transforming complex data into engaging visual outputs tailored to inspiration. Its success in addressing the unique requirements of the students union survey underscores its adaptability and effectiveness in turning data visualisation challenges into opportunities for innovative, inspirational, and purposeful design. We began with a straightforward request: \"Visualise the annual migration patterns of birds across the UK, highlighting their flight paths and nesting grounds\", with the outcomes illustrated in Figure 7. The initial image [I] was produced after restructuring the original prompt into the VisAlchemy structure.