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

Recent years have seen a huge increase in the digital data generated by companies, projects and individuals. This has led to significant challenges in visualizing and using large, diverse collections of digital information. Indeed the speed and accuracy with which these large datasets can be effectively mined for information that is relevant and valuable can have a significant effect on company performance. 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 a 2.5D graphical representation of a multimedia data landscape produces quantifiable improvements in a user's ability to assess its contents. 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.