Visualization Process of Temporal Data

• Published in: Database and Expert Systems Applications pp. 914 - 924
• Main Authors: Daassi, Chaouki, Nigay, Laurence, Fauvet, Marie-Christine
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2004; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Computer science; control theory; systems; Exact sciences and technology; Information systems. Data bases; Memory organisation. Data processing; Software; Temporal Data; Visualization Process; Visualization Technique; Temporal databases; Data analysis; Information extraction; Data mining; Data visualization
• ISBN: 9783540229360; 3540229361
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-540-30075-5_88

Temporal data are abundantly present in many application domains such as banking, financial, clinical, geographical applications and so on. Temporal data have been extensively studied from data mining and database perspectives. Complementary to these studies, our work focuses on the visualization techniques of temporal data: a wide range of visualization techniques have been designed to assist the users to visually analyze and manipulate temporal data. All the techniques have been designed independently. In such a context it is therefore difficult to systematically explore the set of possibilities as well as to thoroughly envision visualization techniques of temporal data. Addressing this problem, we present a visualization process of temporal data. We adapt the Ed Chi’s visualization process to the case of temporal data. We illustrate the steps of our visualization process by considering the design of the Star Representation Technique that we have developed. By identifying and organizing the various aspects of design, our process serves as a basis for classifying existing visualization techniques and should also help the designer to address the right design questions and to envision future systems.