Using visual representations for the searching and browsing of large, complex, multimedia data sets

Industry as a whole has become increasingly global and digitized in recent years, resulting in a huge increase in data generated by companies, projects and even individuals. This has led to great challenges in visualizing and searching for information. The speed and accuracy at which these large datasets can be effectively mined for information that is relevant and valuable can have a significant effect on company performance. Therefore, this research investigates the feasibility of using visual representations for the searching and browsing of large, complex, multimedia data sets. This paper introduces the SIZL (Searching for Information in a Zoom Landscape) system, which was developed to enable the authors to effectively test whether 2.5D environments can benefit effective data management. The usability of this visualization system was analyzed using experiments and a combination of quantitative and qualitative data collection methods. The paper presents these results and discusses potential industrial applications as well as future work that will improve the SIZL data visualization method.