Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …

Utilizing Visualization-oriented Natural Language Interfaces (V-NLI) as a complementary
input modality to direct manipulation for visual analytics can provide an engaging user …

Data collection is a major bottleneck in machine learning and an active research topic in
multiple communities. There are largely two reasons data collection has recently become a …

Data quality issues trace back their origin to the early days of computing. A wide range of
domainspecific techniques to assess and improve the quality of data exist in the literature …

Data visualization is crucial in today's data-driven business world, which has been widely
used for helping decision making that is closely related to major revenues of many industrial …

General visualization tools typically require manual specification of views: analysts must
select data variables and then choose which transformations and visual encodings to apply …

Visualizations themselves have become a data format. Akin to other data formats such as
text and images, visualizations are increasingly created, stored, shared, and (re-) used with …

Profiling data to determine metadata about a given dataset is an important and frequent
activity of any IT professional and researcher and is necessary for various use-cases. It …

Data visualization is invaluable for explaining the significance of data to people who are
visually oriented. The central task of automatic data visualization is, given a dataset, to …

To support effective exploration, it is often stated that interactive visualizations should
provide rapid response times. However, the effects of interactive latency on the process and …