Embedded Merge & Split: Visual Adjustment of Data Grouping
| Autor: | Alex Endert, Nadir Weibel, Bahador Saket, Ali Sarvghad |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Bar chart 020207 software engineering 02 engineering and technology computer.software_genre Computer Graphics and Computer-Aided Design Personalization Visualization law.invention Data visualization law Histogram Signal Processing 0202 electrical engineering electronic engineering information engineering Computer Vision and Pattern Recognition Data mining business Merge (version control) computer Software |
| Zdroj: | IEEE Transactions on Visualization and Computer Graphics. 25:800-809 |
| ISSN: | 2160-9306 1077-2626 |
| DOI: | 10.1109/tvcg.2018.2865075 |
| Popis: | Data grouping is among the most frequently used operations in data visualization. It is the process through which relevant information is gathered, simplified, and expressed in summary form. Many popular visualization tools support automatic grouping of data (e.g., dividing up a numerical variable into bins). Although grouping plays a pivotal role in supporting data exploration, further adjustment and customization of auto-generated grouping criteria is non-trivial. Such adjustments are currently performed either programmatically or through menus and dialogues which require specific parameter adjustments over several steps. In response, we introduce Embedded Merge & Split (EMS), a new interaction technique for direct adjustment of data grouping criteria. We demonstrate how the EMS technique can be designed to directly manipulate width and position in bar charts and histograms, as a means for adjustment of data grouping criteria. We also offer a set of design guidelines for supporting EMS. Finally, we present the results of two user studies, providing initial evidence that EMS can significantly reduce interaction time compared to WIMP-based technique and was subjectively preferred by participants. |
| Databáze: | OpenAIRE |
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