Talks and Poster Presentations (with Proceedings-Entry):
A. Peterschofsky, T. Gschwandtner:
"VoD - Understanding Structure, Content, and Quality of a Dataset";
Talk: IEEE VIS Workshop on Visual Summarization and Report Generation: Beyond Scatter-Plots and Bar-Charts (VISREG 2018),
2018-10-22; in: "Proceedings of the IEEE VIS Workshop on Visual Summarization and Report Generation: Beyond Scatter-Plots and Bar-Charts (VISREG 2018)",
IEEE Xplore Digital Library,
In the age of data science analysts need to handle new data sets on a daily basis. In a first step they need to understand structure, content, and if the dataset is fit-for-use for further processing. However, getting familiar with a dataset by simply scrolling through the data in tabular form is just not feasible for these usually very large sets of data. Thus, we have designed and evaluated a Visual Analytics prototype that provides interactive visual summaries of a dataset on three different levels: the dataset level, the data attribute level, and the data value level. Our results demonstrate the usefulness of our approach and point to further research challenges.
Visual Analytics, Data Summary, Data Profiling
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.