Formulating Your Brief Kirk 2019 Presented The List Of

Under Formulating Your Brief Kirk 2019 Presented The List Of Roles

Under Formulating Your Brief, Kirk (2019) presented the list of roles or “hats” of data visualization design. In 2012, the author presented the same topic but with a total of 8 “hats”. After reading the information from 2012 (his discussion and the slide presentation he includes), compare the information discussed in our text. Please provide your perspective why there is a change from 2012 to 2019. This perspective would be your own opinion. This would not be research discovered about the differences from another source. Please include the following: 1. What are the similarities and the differences in these two lists of roles? 2. Why do you think the list has been refined to the list presented in 2019? 3. What is your suggestion for the next revision and why?

Paper For Above instruction

Introduction

The evolution of roles or "hats" associated with data visualization design, as outlined by Kirk in 2012 and later in 2019, reflects the field's ongoing development and increasing complexity. Comparing these two lists provides insights into how the discipline has matured, incorporating broader perspectives, technological advancements, and a deeper understanding of the multifaceted nature of effective data visualization. This essay analyzes the similarities and differences between the 2012 and 2019 lists, explores the reasons behind the refinement, and offers suggestions for future revisions to better accommodate the evolving landscape of data visualization.

Similarities and Differences Between the 2012 and 2019 Lists

The 2012 list by Kirk comprised eight distinct roles, emphasizing fundamental aspects of data visualization such as data handling, storycrafting, and visual design. These roles included data acquirer, data transformer, story creator, visualizer, and evaluator, which collectively outlined the end-to-end process of designing effective visualizations. The 2019 list, by contrast, expanded and nuanced these roles, introducing additional responsibilities such as ethical considerations, storytelling nuances, and user experience design.

One core similarity is that both lists recognize the importance of data management and storytelling as central elements of visualization. They emphasize understanding the data, transforming it appropriately, and communicating insights clearly. However, the 2019 list diverges by explicitly incorporating roles that address the human-centered aspects of visualization, including accessibility, clarity, and user engagement.

The differences are also notable in the granularity of roles. While the 2012 list presents broader categories, the 2019 list subdivides these into more specific functions—for example, distinguishing between visual design and interpersonal communication or between data ethics and technical implementation. This reflects a deeper appreciation for the multifaceted skill set needed for modern data visualization, which must navigate technical, aesthetic, ethical, and contextual considerations.

Reasons for the Refinement to the 2019 List

The refinement from the 2012 to the 2019 list can be attributed to several factors. First, the field of data visualization has grown increasingly sophisticated, driven by technological advancements such as interactive visualizations, real-time data processing, and new tools that require specialized roles. As a result, the original eight roles needed to be expanded to encapsulate these new dimensions.

Second, there is a broader recognition of the importance of ethical responsibility and accessibility in data visualization. With the rise of social media and digital platforms, visualizations have a significant societal impact, necessitating roles that address misinformation, bias, and inclusivity.

Third, the evolution reflects a more user-centered approach, emphasizing not just the creation of visualizations but also their usability, interpretability, and emotional impact. This shift aligns with contemporary design thinking, which values empathy, storytelling, and user engagement—concepts that are more explicitly recognized in the 2019 list.

Lastly, the proliferation of multidisciplinary teams working on data visualization projects demands clearer role definitions. These roles now overlap across technical, design, and communication disciplines, requiring a more detailed and nuanced list of responsibilities.

Suggestions for the Next Revision

Looking forward, the next revision could incorporate more explicit roles related to emerging technologies such as Artificial Intelligence (AI) and Augmented Reality (AR), which are increasingly integrated into data visualization workflows. For instance, roles could include "AI Integrator" or "AR Experience Designer" to address these technological frontiers.

Moreover, it would be beneficial to emphasize ongoing roles related to data literacy and education, recognizing the importance of empowering users and stakeholders to interpret visualizations critically. As data literacy becomes a core skill, visualizers might also take on roles as educators or facilitators.

Additionally, given the importance of sustainability and environmental considerations, future roles could focus on ethical sustainability practices, ensuring visualizations promote responsible data use and foster informed decision-making without environmental harm.

Finally, expanding the list to explicitly include roles related to cross-cultural communication and multilingual accessibility will reflect the globalized nature of data visualization. This would ensure visualizations serve diverse audiences effectively and ethically.

Conclusion

The progression from the 2012 to the 2019 list of roles or "hats" in data visualization reflects the field’s maturation and broadening scope. The increased granularity and inclusion of ethical, user-centered, and technological considerations demonstrate a holistic understanding of what it takes to produce impactful visualizations today. Future revisions should continue to adapt to technological innovations, societal changes, and the need for responsible, inclusive, and accessible data storytelling. By doing so, the roles will better prepare practitioners to meet the challenges of an increasingly data-driven and interconnected world.

References

• Kirk, A. (2012). Data Visualization: A Handbook for Data Driven Design. SAGE Publications.
• Kirk, A. (2019). Data Visualisation: A Handbook for Data Driven Design (2nd ed.). SAGE Publications.
• Cairo, A. (2016). The Truthful Art: Data, Charts, and Maps for Communication. New Riders.