Call for Papers

We invite contributions to BELIV 2026, the international forum to broadly discuss research methods in visualization. Our discussions span from novel and not-yet fully established design and evaluation methods for visualization tools and techniques, to methods that more generally establish the validity and scope of acquired visualization knowledge. BELIV supports contributions and discussions from the rich spectrum of visualization researchers.

This year: Complementary to the broad scope of BELIV and its general commitment to research methods, BELIV 2026 will include a timely focus topic: Learning What’s True, Doing What’s Right

Twenty years after the first BELIV in 2006, the BELIV workshop invites contributions on emerging and under-examined methodological challenges in visualization research, and fosters open discussions on how we establish the validity and scope of knowledge acquired in our domain, including all forms of systematic and empirical methods used to acquire this knowledge. The goal is to create space for members of the visualization research community to engage with a process of reflection and meta-discussion on empirical research practices in our domain, for example, on what level of rigor to require of our methods, how to choose methods and methodologies, and how to best communicate the results of empirical research. This year's focus will be on two pressing concerns in visualization research: 1) building towards truth in the midst of growing challenges to validity such as the pressures of the replication crisis and the ubiquitous presence of AI-augmented data and analytics as well as 2) building towards ethical research in a world in turmoil while maintaining our integrity as researchers and individuals.

Sample Topics:

  • Ethical implications and considerations of the use of generative AI in visualization in terms of labor, ecology, mis-/dis-information, or equity.
  • Perspectives on attribution and ownership of designs created with / by generative AI
  • Approaches to integrating generative AI into design processes and frameworks
  • Empirical characterizations of the benefits and challenges with leveraging generative AI to support design
  • Reflections on the varied roles of generative AI in visualization work as a function of modality (e.g., image vs. language models)
  • Perspectives on disclosing and characterizing the use of generative AI in research studies
  • Usages of generative AI in visualization evaluations
  • Position papers or other agenda-setting works for creating a vision of visualization research in an AI-driven world

BELIV 2026 also seeks papers on the broader topic of research methods in visualization, which include, but are not limited to:

Innovative Approaches to Visualization Evaluation

  • Novel evaluation methods
  • Revisiting or extending existing research methods
  • Data analysis techniques that are less used in the visualization community, such as Bayesian statistical analysis methods, multiverse analysis, and methods from vision science
  • Methodologies and theories of qualitative research
  • Synthetic or curated data sets and benchmarks

Reflective Practices and Insights on Visualization

  • How to turn empirical research into heuristics or guidelines
  • Reflections on evaluation practice in visualization in the past, present, and future
  • Meta-analysis of existing work in visualization from a methods and methodology perspective
  • Taxonomies / ontologies of evaluation methods, highlighting underexplored or underexplored methods for visualization
  • Methodological frameworks and theories

Foundations of Visualization

  • Rigor in the evaluation process
  • Theoretical and epistemological considerations for visualization research
  • Validity of studies and research results
  • Frontiers and limitations in visualization research
  • Grand challenges and open problems in visualization

Communicating and Reviewing Visualization Research

  • Evaluation criteria and methods for the paper reviewing process
  • How to best communicate the results of empirical research
  • Methods on documenting, archiving and replicating qualitative research

Visualization Evaluation & Design in Challenging Settings

  • Evaluation in the visualization development lifecycle
  • Longitudinal studies/long-term methodologies and challenges
  • Design and evaluation methods in virtual and hybrid settings

Paper Types

The workshop focuses on contributions from all areas of visualization, including VAST, InfoVis, and SciVis. We accept 3 types of submissions— research, position, and survey papers:

Research papers aim to make progress toward novel research methods in visualization and to discuss their benefits and limitations compared to traditional methodologies. As in past editions of BELIV, we will not accept papers that merely report on the use of a method or methodology unless the focus of the contribution is on lessons learned about applying a novel method and new insights on the method itself are presented. Research papers present new work and unpublished results on the topic areas of the workshop, including the focus topic. Research papers will be selected according to their novelty, quality, and relevance.

Position papers are problem discussions or statements describing the author's relevant experience and ideas in regards to methods and methodologies for visualization research, and in particular the focus topic of the workshop. Position papers will be selected according to their importance and relevance for the workshop topics, and how well they will fit the planned discussions.

Survey papers are intended to provide up-to-date and comprehensive surveys on topics relevant to methods and methodologies for visualization research. We welcome submissions that introduce emerging methodological approaches, as well as proposals on traditional research methods. We also welcome contributions from related disciplines and other application areas, including, but not limited to human-computer interaction, design, psychology, statistics, social science, computational sciences, etc. All survey papers, however, must make a clear case for their (potential) relevance to visualization.

Format

Papers can include up to eight pages of content with additional pages for references only. Both full-length and shorter papers are welcome. The length of the submission should be commensurate with the contribution.

All submissions should be formatted in the VGTC conference paper style. Suitable templates, in LaTeX and Word, can be downloaded from: https://tc.computer.org/vgtc/publications/conference/. The submission, however, must be made in PDF format. Authors can decide whether they want to reveal their names on the submission (single-blind) or submit it anonymously (double-blind).

Submission

To submit a paper, create an account and submit the paper to the submission system at: https://new.precisionconference.com/user/login. Please clarify whether you are submitting a position, research, or survey paper.

Publication

We plan to publish accepted papers in the IEEE digital library, including the assignment of DOIs to individual papers.