TACO : Visualizing Changes in Tables Over Time

Multivariate, tabular data is one of the most common data structures used in many different domains. Over time, tables can undergo changes in both structure and content, which results in multiple versions of the same table. A challenging task when working with such derived tables is to understand wh...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1998. - 24(2018), 1 vom: 15. Jan., Seite 677-686
1. Verfasser: Niederer, Christina (VerfasserIn)
Weitere Verfasser: Stitz, Holger, Hourieh, Reem, Grassinger, Florian, Aigner, Wolfgang, Streit, Marc
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2018
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
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520 |a Multivariate, tabular data is one of the most common data structures used in many different domains. Over time, tables can undergo changes in both structure and content, which results in multiple versions of the same table. A challenging task when working with such derived tables is to understand what exactly has changed between versions in terms of additions/deletions, reorder, merge/split, and content changes. For textual data, a variety of commonplace "diff" tools exist that support the task of investigating changes between revisions of a text. Although there are some comparison tools which assist users in inspecting differences between multiple table instances, the resulting visualizations are often difficult to interpret or do not scale to large tables with thousands of rows and columns. To address these challenges, we developed TACO, an interactive comparison tool that visualizes the differences between multiple tables at various levels of detail. With TACO we show (1) the aggregated differences between multiple table versions over time, (2) the aggregated changes between two selected table versions, and (3) detailed changes between the selected tables. To demonstrate the effectiveness of our approach, we show its application by means of two usage scenarios 
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700 1 |a Hourieh, Reem  |e verfasserin  |4 aut 
700 1 |a Grassinger, Florian  |e verfasserin  |4 aut 
700 1 |a Aigner, Wolfgang  |e verfasserin  |4 aut 
700 1 |a Streit, Marc  |e verfasserin  |4 aut 
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