@conference{476,
  author = {Andreas Peterschofsky and Theresia Gschwandtner},
  title = {VoD - Understanding Structure, Content, and Quality of a Dataset},
  abstract = {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. },
  year = {2018},
  journal = {IEEE VIS Workshop on Visual Summarization and Report Generation: Beyond Scatter-Plots and Bar-Charts (VISREG 2018)},
  publisher = {IEEE Xplore Digital Library},
  address = {Berlin, Germany},
}