Data Visualization Pitfalls: A Systematic Review - Sinha, Agam (Digital Repository of Theses, 2024)
The purpose of this systematic review is to identify and analyze common pitfalls in data visualization techniques across various domains. By comprehensively synthesizing existing literature, this study aims to provide insights into the challenges and shortcomings encountered in the creation, interpretation, and communication of visual representations of data. A systematic approach is employed to gather and analyze relevant literature from peer-reviewed journals, conference proceedings, and scholarly books. The search strategy encompasses keywords related to data visualization, pitfalls, challenges, and best practices. Inclusion and exclusion criteria are established to ensure the selection of high-quality studies. Data extraction and synthesis are conducted to identify recurring themes, patterns, and critical insights regarding data visualization pitfalls. The findings reveal a plethora of pitfalls encountered in data visualization practices, including but not limited to misleading visualizations, ineffective use of color and design principles, misrepresentation of data, cognitive biases, and technological limitations. These pitfalls are observed across various stages of the visualization process, from data preparation and selection of visualization techniques to interpretation and communication of visualized information. This systematic review contributes to the understanding of the challenges inherent in data visualization and highlights the importance of addressing these pitfalls to enhance the effectiveness and reliability of visual data communication. The insights gained from this study can inform practitioners, researchers, and decision-makers about the potential pitfalls to avoid and best practices to adopt when creating and interpreting data visualizations. The systematic review underscores the complexity and multidimensionality of data visualization pitfalls, emphasizing the need for interdisciplinary approaches to address them effectively. Despite the advancements in data visualization technology and methodologies, the persistence of common pitfalls necessitates ongoing vigilance and critical evaluation in the design and implementation of visualizations. Furthermore, the study emphasizes the importance of education and training in data visualization to mitigate these pitfalls and promote data literacy among stakeholders. While efforts have been made to ensure the comprehensiveness and rigor of this systematic review, certain limitations exist. The scope of the review may not encompass all potential pitfalls in data visualization, and the findings may be influenced by publication bias or limitations inherent in the selected studies. Additionally, the evolving nature of data visualization techniques and technologies may render some findings outdated over time. Based on the findings of this systematic review, recommendations are provided for future research endeavors. These include the development of standardized guidelines and best practices for data visualization, the integration of interactive and immersive visualization technologies, and the exploration of novel approaches to mitigate cognitive biases and improve the accessibility of visualized information. Further research is warranted to investigate the efficacy of interventions aimed at addressing specific pitfalls and to assess the long-term impact of improved data visualization practices on decision-making and knowledge dissemination.