Paper Info
Title
Measuring Insight into Multi-dimensional Data from a Combination of a Scatterplot Matrix and a HyperSlice Visualization.
Abstract
Understanding multi-dimensional data and in particular multi-dimensional dependencies is hard. Information visualization can help to understand this type of data. Still, the problem of how users gain insights from such visualizations is not well understood. Both the visualizations and the users play a role in understanding the data. In a case study, using both, a scatterplot matrix and a HyperSlice with six-dimensional data, we asked 16 participants to think aloud and measured insights during the process of analyzing the data. The amount of insights was strongly correlated with spatial abilities. Interestingly, all users were able to complete an optimization task independently of self-reported understanding of the data.
Year
Venue
Field
2017
HCI
Data science,Multi dimensional data,Public records,Information visualization,Computer science,Matrix (mathematics),Visualization,Human–computer interaction,Think aloud protocol
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
5
4
Name
Order
Citations
PageRank
André Calero Valdez113425.44
Sascha Gebhardt211.76
Torsten Kuhlen344469.40
Martina Ziefle41176135.05