Visualization of time-dependent semantics data

Time is an essential notion and common attribute in information science. Through the addition of the semantics structure on that information, it can turn out to be a powerful fundamental data in which the knowledge within in can be imparted. Nevertheless, this high potential capability is the contrary side that makes the development of adequate graphical interface even more arduously. Timeline is commonly used for addressing linear time-dependent data and applied as an excellent instrument to represent it. However, most timeline collide with the matter when they encounter a set of complex data, such as the semantics data. Following this further, this thesis proposes a new conceptual design to tackle the hindrances. It supports rich visualization by permitting dynamic hierarchy, cross concept relationships, meta-relationship, fast overview, scalability, and trend recognition. Moreover, the visualization concept is also geared with a set of interactions features which take the advantages of semantic technology to its fullest. It allows exploring the data through the time, distorting time, and generally brushes the data. Together, the major features in the proposed concept are realized through an implementation of prototype.