The growing popularity of machine learning (ML) has attracted more software developers to
now want to adopt ML into their own practices, through tinkering with and learning from ML …

Prior research on communicating with visualization has focused on public presentation and
asynchronous individual consumption, such as in the domain of journalism. The …

Generating knowledge from data is an increasingly important activity. This process of data
exploration consists of multiple tasks: data ingestion, visualization, statistical analysis, and …

Data workers are people who perform data analysis activities as a part of their daily work but
do not formally identify as data scientists. They come from various domains and often need …

Prostate cancer is the most common cancer among men in the US, and yet most cases
represent localized cancer for which the optimal treatment is unclear. Accumulating …

Processes and practices used in data science projects have been reshaping especially over
the last decade. These are different from their software engineering counterparts. However …

The success of Big Data relies fundamentally on the ability of a person (the data scientist) to
make sense and generate insights from this wealth of data. The process of generating …

" Searching for Trust explores the intersection of trust, disinformation and blockchain
technology in an age of heightened institutional and epistemic mistrust. The book adopts a …

The machine learning (ML) life cycle involves a series of iterative steps, from the effective
gathering and preparation of the data—including complex feature engineering processes …

This study presents insights from interviews with nineteen Knowledge Graph (KG)
practitioners who work in both enterprise and academic settings on a wide variety of use …