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 …

Scientific workflow systems have become a necessary tool for many applications, enabling
the composition and execution of complex analysis on distributed resources. Today there …

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 …

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 …

Scientists are now faced with an incredible volume of data to analyze. To successfully
analyze and validate various hypothesis, it is necessary to pose several queries, correlate …

Interactive history tools, ranging from basic undo and redo to branching timelines of user
actions, facilitate iterative forms of interaction. In this paper, we investigate the design of …

Geoscientists now live in a world rich with digital data and methods, and their computational
research cannot be fully captured in traditional publications. The Geoscience Paper of the …

In many data-driven applications, analysis needs to be performed on scientific information
obtained from several sources and generated by computations on distributed resources …

Modern scientific collaborations have opened up the opportunity to solve complex problems
that require both multidisciplinary expertise and large-scale computational experiments …

We describe Chronicle, a new system that allows users to explore document workflow
histories. Chronicle captures the entire video history of a graphical document, and provides …