Open research questions in Data Visualization and Analytics

What the literature leaves open

• Little is known about how individuals’ prior knowledge shapes their use of such information.

  Simpler is better for everyone: causal diagram complexity and the role of perceived knowledge in health decisions · 2026 · DOI

• Although a range of tools have been developed to support these decisions, including visual and causal representations, it remains unclear how the structure and complexity of such information affect decision quality.

  Simpler is better for everyone: causal diagram complexity and the role of perceived knowledge in health decisions · 2026 · DOI

• However, how supervised learning-based photometric stereo networks resolve these challenges remains to be elucidated.

  Revisiting Supervised Learning-Based Photometric Stereo Networks · 2025 · DOI

• Although being frequently employed in human daily reasoning, abduction is rarely explored in computer vision literature.

  Data-And Knowledge-Driven Visual Abductive Reasoning · 2025 · DOI

• Such an evaluation is insufficient to understand the effect of improvements on the fuzzer internals.

  Visualization Task Taxonomy to Understand the Fuzzing Internals · 2025 · DOI

• However, to what extent do these improvements affect the internal components or internals of a given fuzzer is not yet understood as the improvements are mostly evaluated using code coverage and bug finding capability.

  Visualization Task Taxonomy to Understand the Fuzzing Internals · 2025 · DOI

• The discussion highlights the current opportunities, open challenges, and anticipated future trends.

  A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperation · 2024 · DOI

• The split-attention effect adds extraneous cognitive load on readers. The lack of understanding of where, why, and how authors apply word-scale graphics. The rarity of word-scale graphics in scientific papers.

  Graphing Inline: Understanding Word-scale Graphics Use in Scientific Papers · 2026 · DOI

• Future research can explore the use of word-scale graphics in other types of documents. Future research can examine the effectiveness of word-scale graphics in enhancing scholarly communication.

  Graphing Inline: Understanding Word-scale Graphics Use in Scientific Papers · 2026 · DOI

• Existing image exploration tools prioritize relevance ranking and visual similarity, limiting exposure to alternative styles. There is a need for techniques that support transitions between diversity and similarity in image exploration.

  DiverXplorer: Stock Image Exploration via Diversity Adjustment for Graphic Design · 2026 · DOI

• This exploratory study focused on designers’ perceptions and ex- periences in controlled stock image selection tasks and does not capture downstream design activities such as layout composition or integration with text and branding. The participant pool was lim- ited in size and demographics, and the evaluation relied primarily on subjective and comparative measures rather than long-term or in-the-wild use. Future work should examine behavioral traces of exploration in greater depth, involve larger and more diverse popu- lations, and study how diversity control interacts with later stages of the design pipeline. In addition, given the computational cost of DPP algorithm’s sequential sampling, scaling diversity-aware exploration to larger image collections and incorporating alterna- tive feature representations remain important directions for further investigation.

  DiverXplorer: Stock Image Exploration via Diversity Adjustment for Graphic Design · 2026 · DOI

• The challenge of digital formalization of interpretive and discursive acts. The need for a careful and critical engagement with cultural materials. The uneven application of evaluation techniques.

  Chasing Meaning and/or Insight? A Survey on Evaluation Practices at the Intersection of Visualization and the Humanities · 2026 · DOI

• Viscursive approaches to VIS*H evaluation address the asymmetry that visualizations are labor-intensive to create and slow to adapt compared to text-based discourse, preventing rapid critical response and iterative debate. The field needs frameworks and technological infrastructure that enable continuous, responsive critical discourse around data visualizations.

  Chasing Meaning and/or Insight? A Survey on Evaluation Practices at the Intersection of Visualization and the Humanities · 2026 · DOI

• The challenge of transforming raw telecommunication datasets into meaningful, interactive visual insights. The need to integrate data extraction, preprocessing, graph analytics, geospatial intelligence, and interactive visualization.

  CrimeNet Intelligence Tool · 2026 · DOI

• The need for a tool that can transform raw telecommunication datasets into meaningful, interactive visual insights. The lack of a structured workflow for transforming heterogeneous telecom records into graph-based relational intelligence and geospatial mobility insights.

  CrimeNet Intelligence Tool · 2026 · DOI

• Current drug instructions often fail to meet patients' needs for practical and comprehensible information. There is a need for more effective visualization design for OTC drug instructions.

  Enhance comprehension of over-the-counter drug instructions for the general public and medical professionals through visualization design · 2026 · DOI

• The paper notes that it is difficult to know if the failures to find valid solutions in Lavaan and Psych R package indicate difficulties in model specification or reflect the limits of the estimation algorithms. The paper also notes that the analysis is limited to two data sets.

  Visualizations For Interpreting Latent Constructs · 2026 · DOI

• The paper suggests that future research should focus on developing more effective methods for estimating factor models. The paper also suggests that future research should explore the applications of the bifactor model in other domains.

  Visualizations For Interpreting Latent Constructs · 2026 · DOI

• further development of the proposed framework to support multivariate inspection of class-related distributions, - investigation of the applicability of the proposed method to other classification problems

  A Visual Analytics Workflow for Dashboard-Based Classification Support Using Information Gain and Histogram Segmentation · 2026 · DOI

• A central challenge in this context is how to translate attribute relevance into dashboard composition. In many practical settings, dashboards display multiple variables without a formal criterion for deciding which attributes should receive priority in the primary analytical view.

  A Visual Analytics Workflow for Dashboard-Based Classification Support Using Information Gain and Histogram Segmentation · 2026 · DOI

• The dataset scale and coverage could be enhanced in future work, - The curated dataset of 250 high-quality images per style may not capture broader design variations, - Potential overfitting risks may exist due to the limited dataset size

  AI for Garden Design Visualization: Development and Validation of the GardenDiff Model · 2026 · DOI

• Expanding the dataset to capture broader design variations, - Mitigating potential overfitting risks, - Exploring the application of the GardenDiff model in other design domains

  AI for Garden Design Visualization: Development and Validation of the GardenDiff Model · 2026 · DOI

• Little is known about how doctoral students acquire and retain the ability to design, interpret, and explain scientific figures over time. The study highlights the need for further research on the learning environments and experiences that shape long-term retention.

  Conceptual and procedural knowledge retention in data visualization: a longitudinal study of doctoral learning and instructional design implications · 2026 · DOI

• Several limitations should be acknowledged. An important limitation concerns the instruc- tional design of the intervention itself. The training examined in this study consisted of an intensive initial instructional phase, but it did not include structured reinforcement through 1 3F. J. Jiménez-Hornero, E. G. de Ravé Page 23 of 29 51 spaced retrieval, low-stakes testing, or repeated guided application after the course ended. From this perspective, the observed decline in performance, especially in procedural, tool- dependent skills, is not unexpected and should not be interpreted as evidence that visu- alization learning is inherently unstable. Rather, it suggests that a one-time instructional intervention is insufficient for long-term retention of complex data-visualization compe- tence. Research on retrieval practice and test-enhanced learning has shown that repeated recall opportunities, distributed over time and supported by feedback, can improve long- term retention and application of knowledge (Schwieren et al., 2017; Larsen et al., 2013). Future studies should therefore compare the present course-based model with evidence- informed alternatives that incorporate spaced practice, retrieval-based exercises, cumulative low-stakes quizzes, or follow-up graphing tasks embedded across the doctoral trajectory. Another important limitation is that the study did not directly document the learning experiences in which participants engaged between the three assessment points. Although the doctoral context is relevant for interpreting the transition from formal instruction to more independent research activity, the present design did not examine which features of the doctoral program, supervisory practices, research tasks, or informal learning opportuni- ties may have shaped retention outcomes. As a result, the study cannot determine which specific programmatic conditions supported or hindered the maintenance of data-visualiza- tion competence over time. Future research should therefore investigate these intervening experiences more directly, for example through longitudinal tracking of research activity, supervisory feedback, methodological use in ongoing projects, and students’ self-reported opportunities for continued practice. The study was conducted in a single institutional context with a modest sample size, which may limit the generalizability of results. Although linear mixed-effects modeling effectively addressed within-subject dependency and missing data, subsequent work should include larger, more diverse samples and possibly nonlinear modeling to explore alternative trajectories of change. The one-year observation period also captures only an initial phase of skill retention. Longitudinal studies extending over multiple years could determine whether procedural decline stabilizes, reverses, or continues as doctoral students advance toward dissertation work. Moreover, future research should investigate the mechanisms underlying retention and loss. Qualitative approaches, such as reflective journals, interviews, or think-aloud proto- cols, could complement quantitative models to illuminate how doctoral students perceive the relevance and use of data visualization in their ongoing research practice. Examining environmental factors such as access to visualization software, supervisory support, and par- ticipation in research communities of practice would help explain the contextual influences shaping skill maintenance. As Sinclair et al. (2013) note, doctoral learning environments are powerful mediators of skill development, and institutional culture often determines whether early gains are sustained or dissipated over time.

  Conceptual and procedural knowledge retention in data visualization: a longitudinal study of doctoral learning and instructional design implications · 2026 · DOI

• To explore the application of the proposed approach in various domains. To investigate the use of other datasets and techniques to improve cyber threat detection. To develop more advanced AI-Enhanced cybersecurity solutions.

  Data Fingerprinting and Visualization for AI Enhanced Cyber-Defence System · 2026 · DOI

Most-cited papers in Data Visualization and Analytics

• Risk‐of‐bias VISualization (robvis): An R package and Shiny web app for visualizing risk‐of‐bias assessments · Research Synthesis Methods · 2020 · 4,880 citations
• Variations of Box Plots · The American Statistician · 1978 · 3,159 citations
• Violin Plots: A Box Plot-Density Trace Synergism · The American Statistician · 1998 · 2,356 citations
• The Analysis of Proximities: Multidimensional Scaling with an Unknown Distance Function. I. · Psychometrika · 1962 · 1,666 citations
• Tree Visualization By One Table (tvBOT): a web application for visualizing, modifying and annotating phylogenetic trees · Nucleic Acids Research · 2023 · 1,299 citations
• Intercoder Reliability and Validity of WebPlotDigitizer in Extracting Graphed Data · Behavior Modification · 2016 · 924 citations
• Raincloud plots: a multi-platform tool for robust data visualization · Wellcome Open Research · 2019 · 896 citations
• ggplot2: Elegant Graphics for Data Analysis (2nd ed.) · Measurement Interdisciplinary Research and Perspectives · 2019 · 854 citations
• Some Implementations of the Boxplot · The American Statistician · 1989 · 799 citations
• Computing and Graphing Highest Density Regions · The American Statistician · 1996 · 690 citations

Most recent work

• AI-assisted assessment of higher education quality: A visual analytical approach · Visual Informatics · 2026
• Enhancing scientific argumentation with visual scaffolding in generative AI-supported environments · International Journal of Science Education · 2026
• Chasing Meaning and/or Insight? A Survey on Evaluation Practices at the Intersection of Visualization and the Humanities · 2026
• Enhance comprehension of over-the-counter drug instructions for the general public and medical professionals through visualization design · Computers & Graphics · 2026
• A Gentle Introduction to Bayesian Posterior Predictive Checking for Single-Case Researchers · Journal of Behavioral Education · 2026
• A novel approach for visualizing local consistency in network meta-analysis · Research Synthesis Methods · 2026
• Empirical mathematics in Australian Indigenous smoke telegraphy · The Mathematical Gazette · 2026
• People prefer novices for advice generated from direct experience and experts for advice generated from data synthesis and extrapolation · Organizational Behavior and Human Decision Processes · 2026
• D-MO: Depth from Motion and Occlusion as a Visual Channel for Information Visualization · SPIRE - Sciences Po Institutional REpository · 2026
• Graphing Inline: Understanding Word-scale Graphics Use in Scientific Papers · 2026

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