The need for interpretable and accountable intelligent systems grows along with the
prevalence of artificial intelligence (AI) applications used in everyday life. Explainable AI …

We present a systematic literature review of the emerging field of visual learning analytics.
We review existing work in this field from two perspectives: First, we analyze existing …

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

Interpretation and diagnosis of machine learning models have gained renewed interest in
recent years with breakthroughs in new approaches. We present Manifold, a framework that …

The considerable previous work characterizing visualization usage has focused on low-level
tasks or interactions and high-level tasks, leaving a gap between them that is not addressed …

Design studies are an increasingly popular form of problem-driven visualization research,
yet there is little guidance available about how to do them effectively. In this paper we reflect …

Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

Visualizations are now widely used across disciplines to understand and communicate data.
The benefit of visualizations lies in leveraging our natural visual perception. However, the …

We present an overview of the last ten years of research on visualizations that support close
and distant reading of textual data in the digital humanities. We look at various works …

After decades of digitization, large cultural heritage collections have emerged on the web,
which contain massive stocks of content from galleries, libraries, archives, and museums …