Abstract

This paper treats a 3D visualization tool called Time-tunnel, especially describes its aspects as 3D Parallel Coordinates by showing its actual visualization examples. Originally, Time-tunnel is a multidimensional data visualization tool and it was extended to support Parallel Coordinates called PCTT(Parallel Coordinates version of Time-tunnel). Furthermore, as its aspects of 3D Parallel Coordinates, 2Dto2D visualization functionality was added. Although PCTT can visualize network data because IP packets consist of many attributes and such multiple-attributes data can be visualized using Parallel Coordinates, 2Dto2D visualization functionality can more effectively visualize patterns of IP packets that seem network attacks. The authors have already proposed the combinatorial use of PCTT and 2Dto2D visualization for the intrusion detection of the Internet. This paper also introduces Spline Parallel Coordinates representation as one of the new features of PCTT. The authors also proposed the use of PCTT for learning analytics by visualizing leaners' learning activity data and introduced 3D mode into PCTT to visualize each learner's learning pattern more efficiently. This 3D mode is regarded as 3D Parallel Coordinates. However, because such 3D mode was not enough to distinguish each learner's leaning pattern, the authors implemented more effective 3D mode, and clarify the usefulness of the new 3D mode by showing visualization results.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call