Enhancing usability of the similarity map for more accessible politics

Our project builds on an established internet service that facilitates understanding complex political agendas and helps to choose the best candidates in local or governmental elections. The service, widely adopted by the great public in Finland, is text based, and according to our claim, does not perform optimally with respect to cognitive ergonomy and visualization. The present paper describes a design iteration loop to improve the visualization of high dimensional political data. Our earlier prototype already proposed a visual similarity map interface with basic visualization and data access functionalities. According to our claim, the effective use of similarity maps improves cognitive ergonomy of the service. It takes advantage of the parallel processing of visual perception and compresses the semantic core of the multidimensional input. Yet, it has been claimed that the representation requires the user to conceptualize information in unfamiliar way. The difficulty can be alleviated by usability measures and our explorative study suggests that simplicity should be taken as a guideline for the design.