DocumentCode
39738
Title
CoDe Modeling of Graph Composition for Data Warehouse Report Visualization
Author
Risi, Michael ; Sessa, Maria I. ; Tucci, Mauro ; Tortora, Giuseppe
Author_Institution
Dept. of Manage. & Inf. Technol., Univ. of Salerno, Salerno, Italy
Volume
26
Issue
3
fYear
2014
fDate
Mar-14
Firstpage
563
Lastpage
576
Abstract
The visualization of information contained in reports is an important aspect of human-computer interaction, for both the accuracy and the complexity of relationships between data must be preserved. A greater attention has been paid to individual report visualization through different types of standard graphs (Histograms, Pies, etc.). However, this kind of representation provides separate information items and gives no support to visualize their relationships which are extremely important for most decision processes. This paper presents a design methodology exploiting the visual language CoDe based on a logic paradigm. CoDe allows to organize the visualization through the CoDe model which graphically represents relationships between information items and can be considered a conceptual map of the view. The proposed design methodology is composed of four phases: the CoDe Modeling and OLAP Operation pattern definition phases define the CoDe model and underlying metadata information, the OLAP Operation phase physically extracts data from a data warehouse and the Report Visualization phase generates the final visualization. Moreover, a case study on real data is provided.
Keywords
data mining; data visualisation; data warehouses; human computer interaction; meta data; CoDe modeling; CoDe visual language; OLAP operation pattern definition; complexity design; data warehouse report visualization; design methodology; graph composition; human-computer interaction; information visualization; logic paradigm; meta data information; online analytical processing; Companies; Data mining; Data models; Data visualization; Standards; Visualization; Information visualization; OLAP reports; cognitive systems; data and knowledge visualization; user interfaces;
fLanguage
English
Journal_Title
Knowledge and Data Engineering, IEEE Transactions on
Publisher
ieee
ISSN
1041-4347
Type
jour
DOI
10.1109/TKDE.2013.24
Filename
6427742
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