Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Oral health surveys largely facilitate the prevention and treatment of oral diseases as well as the awareness of population health status. As oral health is always surveyed from a variety of perspectives, it is quite a difficult and complicated task to gain insights from multidimensional oral health surveys. Objective: In this paper, we develop a visualization framework for the visual analytics and deep mining of multidimensional oral health surveys. Methods: First, diseases and groups are embedded into data portraits based on their multidimensional attributes. Based on group classification, correlation patterns are then built for diseases, behaviors, symptoms and cognition to reveal their correlation features. Given the extricated knowledge of diseases, groups, behaviors and their attributes, a knowledge graph is further constructed to reveal semantic information, integrate the graph query function, and describe the features of intrigue to users. Results: A set of meaningful user interactions are integrated, enabling users to intuitively understand the oral health situation and conduct in-depth data exploration and analysis. Case studies based on real-world datasets and interviews with domain experts have demonstrated the effectiveness of our system. Conclusions: In this paper, we propose a visualization framework for multidimensional oral health surveys. A series of user-friendly interactions are integrated to propose a visual analysis system that can help users further explore the regulations of oral health conditions. Case studies based on real-world datasets demonstrate the effectiveness of our system in the exploration of oral diseases.