For an investigative journalist, a large collection of documents obtained from a Freedom of
Information Act request or a leak is both a blessing and a curse: such material may contain …

Dimensionality reduction methods, also known as projections, are frequently used in
multidimensional data exploration in machine learning, data science, and information …

Abstract Information visualization as a field is growing rapidly in popularity since the first
information visualization conference in 1995. However, as a consequence of its growth, it is …

Learn How to Design Effective Visualization SystemsVisualization Analysis and Design
provides a systematic, comprehensive framework for thinking about visualization in terms of …

Massive simulations and arrays of sensing devices, in combination with increasing
computing resources, have generated large, complex, high-dimensional datasets used to …

We introduce ImAxes immersive system for exploring multivariate data using fluid, modeless
interaction. The basic interface element is an embodied data axis. The user can manipulate …

Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data.
For DR techniques to be useful in exploratory data analysis, they need to be adapted to …

Traditional scatterplots fail to scale as the complexity and amount of data increases. In
response, there exist many design options that modify or expand the traditional scatterplot …

Labeling data instances is an important task in machine learning and visual analytics. Both
fields provide a broad set of labeling strategies, whereby machine learning (and in particular …

There is a need for solutions which assist users to understand long time-series data by
observing its changes over time, finding repeated patterns, detecting outliers, and effectively …