2018 IEEE Evaluation and Beyond - Methodological Approaches for Visualization BELIV

活动简介

* Evaluation in the visualization development lifecycle * Novel evaluation methods * Revisiting or extending existing research methods * Synthetic data sets and benchmarks * Taxonomy of tasks * Benchmark development and repositories * How to turn empirical research into heuristics or guidelines * Reflections on evaluation practice in visualization in the past, present, and future * Validity of studies and research results * Evaluation criteria and methods for the paper reviewing process * Design methods and methodologies * Methodological frameworks and theories * Rigor in the evaluation process * How to best communicate the results of empirical research

征稿信息

重要日期

2018-06-30

初稿截稿日期

We invite contributions to BELIV 2018, the international forum to broadly discuss research methods in visualization. Our discussions span from novel and not-yet fully established evaluation methods for visualization tools and techniques to methods that more generally establish the validity and scope of acquired visualization knowledge. The 2018 call for papers includes an expanded scope from years past to reflect this newly broadened purview.

New this year: Complementary to the broader scope on research methods more generally, 2018 will also include a focus topic—replication practices in visualization—which will shape half of the workshop. This call for papers thus also includes specific issues related to both the replication of quantitative and qualitative work, as well as opportunities for reflective assessment of unsuccessful replication efforts.

征稿范围

Based on the definition of replication above, specific focus topics of interest include, but are not limited to:

Best practices for supporting replication
How do we, or how should we build on other’s work
The value of replication in VIS
Alternatives when replication is not possible
Discussion of methods that support replicability in VIS, e.g. pre-registration
Reflection on replication attempts, successes, and failures
Dangers of replication
Reviewing replicated work
Meta-analysis of replication in visualization