IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics topics, including modeling, rendering, animation, (data) visualization, HCI/user interfaces, novel applications, hardware architectures, haptics, and virtual- and augmented-reality systems.

From specific algorithms to full system implementations, CG&A offers a unique combination of peer-reviewed feature articles and informal departments. Theme issues guest edited by leading researchers in their fields track the latest developments and trends in computer-generated graphical content, while tutorials and surveys provide a broad overview of interesting and timely topics. Regular departments further explore the core areas of graphics as well as extend into topics such as usability, education, history, and opinion. Each issue, the story of our cover focuses on creative applications of the technology by an artist or designer. Published six times a year, CG&A is indispensable reading for people working at the leading edge of computer-generated graphics technology and its applications in everything from business to the arts.

CG&A is the oldest and still the only publication with such a breath of topics and its mix of opinion pieces and peer-reviewed research articles. We pride ourselves on both our high impact factor and fast turnaround time for submitted content.

Special Issue on Critical Data Visualization
Día de Entrega: 2024-10-31

Critical data visualization generally refers to the practice of examining and representing data with an awareness of the cultural, social, and ethical implications. These methods support consideration of the power structures embedded into visualization designs, inspection of the politics latent to research methods, and reflection on visualization content and context more broadly. Coming to prominence in information visualization from Dörk et al. (2013), the term critical visualization originally described principles for authoring visualizations that expose embedded values and support empowerment for readers. This field has since grown to encompass a range of topics—for instance, integrating considerations of how data and graphical practices might embrace feminist methods. Works in this area strive to challenge existing visualization dogmas and identify overlooked assumptions as a way to push conventional visualization practice toward more inclusive and reflective practices.

Despite growing usage, however, there is a lack of a shared definition of what ‘criticality’ refers to for visualization and how those ideas can be applied in a rigorous and useful manner. While this plural understanding of criticality has afforded a vast array of creative applications, it has precluded critical methods and goals from being broadly understood or adopted. Through this special issue, we aim to both complicate and coalesce the visualization research community’s understanding and definition of critical visualizations, as well as the challenges associated with it. For instance, answering questions like: How to design ‘critical’ visualizations? What are the goals of critical visualization? Or even, what is critical visualization? To address these concerns we invite essays, explorations, and empirical work on topics including:
- Examinations of how critical theory intersects with data visualization (theoretical or empirical)
- Critical methods that have led to new visualization methods, theories, or designs
- Investigations of the relationship between criticality and feminism in visualization
- Reflections on the ethical implications of visualization research
- Challenges to appropriateness of critical theory for visualization research
- Case studies of critical methods applied to visualization (for example, speculative design/auto-ethnography/diffraction)
- New means of critically evaluating visualizations
- Grand challenges for critical visualization. 

Special Issue on Inclusive Data Experiences
Día de Entrega: 2024-12-30

While the visualization community has made great strides over the last few decades, visualization research has traditionally centered on certain user groups, notably individuals without disabilities, overlooking the diverse capabilities and needs of a broader range of people. The disparities in sensory, cognitive, and motor abilities lead to unequal access to data visualization and the underlying data.

Data has become an integral part of our lives and holds immense potential to influence how we work, live, and engage with the world. Data visualization has proven a powerful tool for gaining and communicating insights, as well as supporting informed decision-making across various domains and contexts. The inequitable access to data and data visualization significantly affects education and employment, as well as health and lifestyle. Recognizing the urgent need to address this significant equity issue, research communities have put increasing efforts towards making data visualization accessible to people with disabilities. We aspire not only to amplify this trend but also to more broadly consider inclusive data experiences. This goes beyond data visualization to understand broader interactions between data and people so that everyone can equitably access and benefit from data.

This special issue aims to foster novel insights and advancements for inclusive data experiences. We invite submissions that examine various needs and challenges, introduce innovative approaches and solutions, present robust methodologies and evaluations, and offer visions and viewpoints, among other things.

Topics of interest include, but not limited to:
- Accessible visualization authoring tools and production methods
- Novel devices for accessible data interaction
- Technologies for inclusive data experiences
- Data physicalization for inclusive data experiences
- Challenges and opportunities of AI for inclusive data experiences
- Accessible multimodal data representations
- Evidence-based guidelines for inclusive data representations
- Data and visualization education for inclusive data representations
- Real-world data needs of people with disabilities and marginalized users
- Accessible personal informatics for people with disabilities and marginalized 

Special Issue on Breakthroughs, Challenges, and Opportunities in Biological Data Visualization
Día de Entrega: 2025-02-21

The rapidly expanding data generated by advanced methods in biology is creating enormous  challenges at the interface between humans and biological data that can be represented and  analyzed visually. To meet these challenges, a blend of methodology from the visualization,  bioinformatics and biology domains is required. This methodology encompasses perception and  design knowledge, algorithm design, techniques for analyzing and visualizing big data,  statistics, and specific domain knowledge for different application problems. Powerful and  integrative visualization methods are necessary, as well as methods for visually communicating  the outcome of computational analytical methods and findings. 

This special issue aims to highlight new challenges in biological data visualization (BioVis), and  state-of-the-art solutions created by the vibrant BioVis community. We invite contributions on all  aspects of data visualization in biology, from molecular to cell, tissue, organism and population  biology. Topics of interest include, but are not limited to: 

    Genome and sequence data visualization, including genomic variation data, 3D and 4D genome visualization, and chromosome interaction maps
    Multivariate omics data visualization (transcriptomics, proteomics, metabolomics, etc.)
    Phylogenetic data visualization, as well as biological networks and pathways
    Neurobiology and developmental biology visualization, biological atlases and metadata 
    Macromolecular structures (e.g., protein or RNA structures) visualization
    Biological image data, such as microscopy data visualization 
    Visualization for the modeling and simulation of biological systems 
    Biovis systems and software frameworks, and integrating visualization and machine learning for biological analysis 
    Biological workflows or collaborative processes, processes for interdisciplinary collaboration between biology and visualization, and usability of visualization by biologists, including communicating uncertainty 
    New challenges, breakthroughs, and opportunities in biological data visualization