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 …

Provenance in the context of workflows, both for the data they derive and for their
specification, is an essential component to allow for result reproducibility, sharing, and …

In the past few years, 3D electron microscopy (3DEM) has undergone a revolution in
instrumentation and methodology. One of the central players in this wide-reaching change is …

Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can
make database more intelligent (AI4DB). For example, traditional empirical database …

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 …

Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can
make database more intelligent (AI4DB). For example, traditional empirical database …

This system paper presents the Topology ToolKit (TTK), a software platform designed for the
topological analysis of scalar data in scientific visualization. While topological data analysis …

Building a machine learning model is an iterative process. A data scientist will build many
tens to hundreds of models before arriving at one that meets some acceptance criteria (eg …

While the primary goal of visual analytics research is to improve the quality of insights and
findings, a substantial amount of research in provenance has focused on the history of …

Today's computational, experimental, and observational sciences rely on computations that
involve many related tasks. The success of a scientific mission often hinges on the computer …