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Data science requires time-consuming iterative manual activities. In particular, activities such as data selection, preprocessing, transformation, and mining, highly depend on iterative trial-and-error processes that could be sped-up…

The data revolution continues to transform every sector of science, industry and government. Due to the incredible impact of data-driven technology on society, we are becoming increasingly aware of the imperative to use data and algorithms…

For a variety of inter-related cultural, organizational, and political reasons, progress in climate science and the actual solution of scientific problems in this field have moved at a much slower rate than would normally be possible. Not…

From a computer science perspective, addressing on-line hate speech is a challenging task that is attracting the attention of both industry (mainly social media platform owners) and academia. In this chapter, we provide an overview of…

Data science has become increasingly essential for the production of official statistics, as it enables the automated collection, processing, and analysis of large amounts of data. With such data science practices in place, it enables more…

The data science revolution has led to an increased interest in the practice of data analysis. While much has been written about statistical thinking, a complementary form of thinking that appears in the practice of data analysis is design…

Artificial Intelligence has the potential to exacerbate societal bias and set back decades of advances in equal rights and civil liberty. Data used to train machine learning algorithms may capture social injustices, inequality or…

Several high-profile events, such as the mass testing of emotion recognition systems on vulnerable sub-populations and using question answering systems to make moral judgments, have highlighted how technology will often lead to more adverse…

Although data science builds on knowledge from computer science, mathematics, statistics, and other disciplines, data science is a unique field with many mysteries to unlock: challenging scientific questions and pressing questions of…

Data have power. As such, most discussions of data presume that records should mirror some idealized ground truth. Deviations are viewed as failure. Drawing on two ethnographic studies of state data-making in a Chinese street-level…

We present a programmatic approach to incorporating ethics into an undergraduate major in statistical and data sciences. We discuss departmental-level initiatives designed to meet the National Academy of Sciences recommendation for…

Managers regularly face a complex ethical dilemma over how to best govern online communities by evaluating the effectiveness of different social or technical strategies. What ethical considerations should guide researchers and managers when…

Data Science is a multidisciplinary field that plays a crucial role in extracting valuable insights and knowledge from large and intricate datasets. Within the realm of Data Science, two fundamental components are Information Theory (IT)…

Emerging research frontiers and computational advances have gradually transformed cognitive science into a multidisciplinary and data-driven field. As a result, there is a proliferation of cognitive theories investigated and interpreted…

Computational Politics is the study of computational methods to analyze and moderate users' behaviors related to political activities such as election campaign persuasion, political affiliation, and opinion mining. With the rapid…

Consensus on the definition of data science remains low despite the widespread establishment of academic programs in the field and continued demand for data scientists in industry. Definitions range from rebranded statistics to data-driven…

Justice-centered approaches to equitable computer science (CS) education frame CS learning as a means for advancing peace, antiracism, and social justice rather than war, empire, and corporations. However, most research in justice-centered…

Across academia, government, and industry, data stewards are facing increasing pressure to make datasets more openly accessible for researchers while also protecting the privacy of data subjects. Differential privacy (DP) is one promising…

The presence of data science has been profound in the scientific community in almost every discipline. An important part of the data science education expansion has been at the undergraduate level. We conducted a systematic literature…

Healthcare stands at a critical crossroads. Artificial Intelligence and modern computing are unlocking opportunities, yet their value lies in the data that fuels them. The value of healthcare data is no longer limited to individual…