Towards Systematic Design Considerations for Visualizing Cross-View Data Relationships

Knowledge maps as a complementary tool to learn and teach surgical anatomy in virtual reality: A case study in dental implantology

A thorough understanding of surgical anatomy is essential for preparing and training medical students to become competent and skilled surgeons. While Virtual Reality (VR) has shown to be a suitable interaction paradigm for surgical training, traditional anatomical VR models often rely on simple labels and arrows pointing to relevant landmarks. Yet, studies have indicated that such visual settings could benefit from knowledge maps as such representations explicitly illustrate the conceptual connections between anatomical landmarks. In this article, a VR educational tool is presented designed to explore the potential of knowledge maps as a complementary visual encoding for labeled 3D anatomy models. Focusing on surgical anatomy for implantology, it was investigated whether integrating knowledge maps within a VR environment could improve students' understanding and retention of complex anatomical relationships. The study involved 30 master's students in dentistry and 3 anatomy teachers, who used the tool and were subsequently assessed through surgical anatomy quizzes (measuring both completion times and scores) and subjective feedback (assessing user satisfaction, preferences, system usability, and task workload). The results showed that using knowledge maps in an immersive environment facilitates learning and teaching surgical anatomy applied to implantology, serving as a complementary tool to conventional VR educational methods.

A Survey of Designs for Combined 2D+3D Visual Representations

We examine visual representations of data that make use of combinations of both 2D and 3D data mappings. Combining 2D and 3D representations is a common technique that allows viewers to understand multiple facets of the data with which they are interacting. While 3D representations focus on the spatial character of the data or the dedicated 3D data mapping, 2D representations often show abstract data properties and take advantage of the unique benefits of mapping to a plane. Many systems have used unique combinations of both types of data mappings effectively. Yet there are no systematic reviews of the methods in linking 2D and 3D representations. We systematically survey the relationships between 2D and 3D visual representations in major visualization publications-IEEE VIS, IEEE TVCG, and EuroVis-from 2012 to 2022. We closely examined 105 articles where 2D and 3D representations are connected visually, interactively, or through animation. These approaches are designed based on their visual environment, the relationships between their visual representations, and their possible layouts. Through our analysis, we introduce a design space as well as provide design guidelines for effectively linking 2D and 3D visual representations.

YouTube and science: models for research impact

Video communication has been rapidly increasing over the past decade, with YouTube providing a medium where users can post, discover, share, and react to videos. There has also been an increase in the number of videos citing research articles, especially since it has become relatively commonplace for academic conferences to require video submissions. However, the relationship between research articles and YouTube videos is not clear, and the purpose of the present paper is to address this issue. We created new datasets using YouTube videos and mentions of research articles on various online platforms. We found that most of the articles cited in the videos are related to medicine and biochemistry. We analyzed these datasets through statistical techniques and visualization, and built machine learning models to predict (1) whether a research article is cited in videos, (2) whether a research article cited in a video achieves a level of popularity, and (3) whether a video citing a research article becomes popular. The best models achieved F1 scores between 80% and 94%. According to our results, research articles mentioned in more tweets and news coverage have a higher chance of receiving video citations. We also found that video views are important for predicting citations and increasing research articles' popularity and public engagement with science.