Advancing Scholarship on Data: Theories, Methods, and Insights on Data-Intensive Technologies

Many popular topics in digital technology are intimately tied to data. Recent developments in generative AI, blockchain-based organizing, or digital twins rely extensively on new kinds of data produced, circulated, and brought together in the digital environment. Governing these and other similar technologies and understanding their various impacts on individuals, organizations, and society at large require new theorizing, methodological developments, and empirical insights that help account for the role of data in contemporary digital technology. In this professional development workshop, we explore the opportunities and challenges that the emerging data-intensive technologies pose for data scholars. We widen participation in the discussions by inviting emerging scholars to open the workshop by presenting their work on novel data-intensive phenomena. We particularly focus on five areas: 1) synthetic data, 2) digital twins, 3) personal data, 4) data and AI, and 5) data governance. First, five presenters provide an overview of their recent research in these areas, followed by breakout group discussions with participants working in these areas led by five expert discussants regarding theories, methods, and insights into the study of data in each area. Finally, the expert discussants convene into a panel to provide summative insights and suggestions for data scholars in these areas.