<i>‘This book puts digital data at the center of scholarly inquiry, and the result is a refreshing array of perspectives and approaches for dealing with the topic. A must-read for organizational researchers looking to go beyond the surface in exploring domains such as artificial intelligence, evidence-based decision making, digital platforms & infrastructures, and contemporary business models.’</i>
- Nick Berente, University of Notre Dame, USA,
<i>‘The </i>Research Handbook on Digital Data<i> offers a comprehensive account of how digital data both shape and are shaped by emerging infrastructures. 24 chapters by leading scholars explore the multifaceted character and implications of digital data, the practices through which it acquires meaning and is used and how it is governed.’</i>
- Robin Williams, The University of Edinburgh, UK,
<i>‘Turn data into value with contemporary information infrastructure like machine learning, neural networks, and digital twins. Balance privacy, governance, regulation, and organization in traditional or circular economies. A heady mix of insight and practical guidance.’</i>
- John Leslie King, University of Michigan, USA,
By situating its chapters within the layers of a digital data stack, this unique Research Handbook not only offers a variety of diverse perspectives and approaches, but it also provides a structure for cumulative insight. Leading scholars analyse and interpret the creation, governance, and utilization of data, covering key topics such as machine learning, data heterogeneity, temporal fragilities in data sharing, and blockchain finance. Ultimately, this Research Handbook highlights how the kaleidoscopic nature of digital data gives rise to multiple competing realities, making it a reference point for future scholarship.
The Research Handbook on Digital Data is an essential read for scholars and students of information systems, management, science and technology studies, sociology of technology, public policy, and data governance. It is also of benefit to practitioners in data-intensive fields seeking conceptual clarity and practical insight into the complexities of working with digital data.