Rigel: Transforming Tabular Data by Declarative Mapping

We present Rigel, an interactive system for rapid transformation of tabular data. Rigel implements a new declarative mapping approach that formulates the data transformation procedure as direct mappings from data to the row, column, and cell channels of the target table. To construct such mappings,...

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Vydáno v:IEEE transactions on visualization and computer graphics Ročník 29; číslo 1; s. 1 - 11
Hlavní autoři: Chen, Ran, Weng, Di, Huang, Yanwei, Shu, Xinhuan, Zhou, Jiayi, Sun, Guodao, Wu, Yingcai
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Channels
Data models
Data transformation
Data visualization
declarative specification
Drag
Economic indicators
Interactive systems
Mapping
programming by example
self-service data transformation
Tables (data)
Task analysis
Transformations
Transforms
Usability
Writing
ISSN:1077-2626, 1941-0506, 1941-0506
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Popis
Shrnutí:We present Rigel, an interactive system for rapid transformation of tabular data. Rigel implements a new declarative mapping approach that formulates the data transformation procedure as direct mappings from data to the row, column, and cell channels of the target table. To construct such mappings, Rigel allows users to directly drag data attributes from input data to these three channels and indirectly drag or type data values in a spreadsheet, and possible mappings that do not contradict these interactions are recommended to achieve efficient and straightforward data transformation. The recommended mappings are generated by enumerating and composing data variables based on the row, column, and cell channels, thereby revealing the possibility of alternative tabular forms and facilitating open-ended exploration in many data transformation scenarios, such as designing tables for presentation. In contrast to existing systems that transform data by composing operations (like transposing and pivoting), Rigel requires less prior knowledge on these operations, and constructing tables from the channels is more efficient and results in less ambiguity than generating operation sequences as done by the traditional by-example approaches. User study results demonstrated that Rigel is significantly less demanding in terms of time and interactions and suits more scenarios compared to the state-of-the-art by-example approach. A gallery of diverse transformation cases is also presented to show the potential of Rigel's expressiveness.
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ISSN:1077-2626
1941-0506
1941-0506
DOI:10.1109/TVCG.2022.3209385