Towards Visualizing Primary Sjogren'S Syndrome Data From Heterogeneous Cohorts

Visual analytics establish a comprehensive approach to handling the exponential growth of healthcare data and promise to offer innovative approaches to the understanding of health parameters and their important interrelations. Primary Sjogren's Syndrome (pSS) is an autoimmune disease with unknown causes and various symptoms, for which visual analytics can prove useful in understanding its characteristics, utilizing the abundance of currently available data. A large number of medical organizations currently possess databases of patients with pSS, recording demographic, geographical, clinical, genetic and activity data. However, these databases are usually diverse in their schemas, focusing on different characteristics and having different naming conventions for their concepts. Visual analytics for such data require that they are represented in a common schema. This paper presents the Visual analytics methods utilized within the HarmonicSS EU project, which aim at providing visualization and interaction techniques to the operator, based on a semantic-based harmonization of data from multiple cohorts. Visualization of large data from multiple sources is important in order to understand the causes of the disease and facilitate diagnosis.