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 …

Supporting exploratory visual analysis (EVA) is a central goal of visualization research, and
yet our understanding of the process is arguably vague and piecemeal. We contribute a …

Visualization recommender systems aim to lower the barrier to exploring basic visualizations
by automatically generating results for analysts to search and select, rather than manually …

High-quality visualization collections are beneficial for a variety of applications including
visualization reference and data-driven visualization design. The visualization community …

Charts are very popular for analyzing data, visualizing key insights and answering complex
reasoning questions about data. To facilitate chart-based data analysis using natural …

Inspired by the great success of machine learning (ML), researchers have applied ML
techniques to visualizations to achieve a better design, development, and evaluation of …

The majority of visualizations on the web are still stored as raster images, making them
inaccessible to visually impaired users. We propose a deep‐neural‐network‐based …

Automatic infographics generators employ machine learning algorithms/user-defined rules
and visual embellishments into the creation of infographics. It is an emerging topic in the …

People often use charts to analyze data, answer questions and explain their answers to
others. In a formative study, we find that such human-generated questions and explanations …

The use of natural language interfaces (NLIs) to create charts is becoming increasingly
popular due to the intuitiveness of natural language interactions. One key challenge in this …