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 …

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 …

The remarkable progress in algorithms for machine and deep learning have opened the
doors to new opportunities, and some dark possibilities. However, a bright future awaits …

This article attempts to bridge the gap between widely discussed ethical principles of Human-
centered AI (HCAI) and practical steps for effective governance. Since HCAI systems are …

The explosive growth in the number of devices connected to the Internet of Things (IoT) and
the exponential increase in data consumption only reflect how the growth of big data …

Provenance refers to any information describing the production process of an end product,
which can be anything from a piece of digital data to a physical object. While this survey …

Designing a data physicalization requires a myriad of different considerations. Despite the
cross-disciplinary nature of these considerations, research currently lacks a synthesis across …

In this paper, we begin to outline how feminist theory may be productively applied to
information visualization research and practice. Other technology-and design-oriented fields …

There is fast‐growing literature on provenance‐related research, covering aspects such as
its theoretical framework, use cases, and techniques for capturing, visualizing, and …

Geospatial big data present a new set of challenges and opportunities for cartographic
researchers in technical, methodological and artistic realms. New computational and …