Situated analytics (SA), a novel visualization approach that combines real-time interaction and visualization techniques drawn from visual analytics and augmented reality (AR), is presented in this paper. It provides features for exploring and analyzing objects in its environment.

Two interaction methods are considered: analytical (AI) and AR interactions (ARI). AIs enable filtering, sorting, and comparing information associated with physical objects. ARIs enable physical objects to select/deselect instead of interacting with input devices. SA visual representation consists of abstract and situated information. According to the paper, “abstract information represents the overall information” and situated information is “the information associated with physical objects.”

To evaluate SA, a shopping scenario using analytical interaction is designed. It includes tree nutrition algorithms, such as “point system algorithms for food and targets, star guidance program for general foods and beverages, and the healthy eating plate.” A user study to enhance user understanding of information was performed. It evaluates aspects of SA, error rates, and shopping completion time and compares them with those completed using a manual approach. Situated and abstract information is used to virtualize the results of user interaction. The results show that tasks performed using the proposed approach are faster and accurate (lower error rates) than those performed using a manual approach. A questionnaire-based survey reveals that users rather prefer the SA approach for completing shopping tasks.

The SA approach has great potential to enhance decision-making processes in several fields. However, the authors only compare their approach with the manual approach, omitting traditional AR approaches, which presents limitations. A comparison with such systems could best point out their novelty.

I can recommend this paper for readers with a strong AR background.