The Big Data Agenda

The Big Data Agenda

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This book highlights that the capacity for gathering, analysing, and utilising vast amounts of digital (user) data raises significant ethical issues. Annika Richterich provides a systematic contemporary overview of the field of critical data studies that reflects on practices of digital data collection and analysis. The book assesses in detail one big data research area: biomedical studies, focused on epidemiological surveillance. Specific case studies explore how big data have been used in academic work.

The Big Data Agenda concludes that the use of big data in research urgently needs to be considered from the vantage point of ethics and social justice. Drawing upon discourse ethics and critical data studies, Richterich argues that entanglements between big data research and technology/ internet corporations have emerged. In consequence, more opportunities for discussing and negotiating emerging research practices and their implications for societal values are needed.

An electronic version of this book is freely available, thanks to the support of libraries working with Knowledge Unlatched. KU is a collaborative initiative designed to make high quality books Open Access for the public good. More information about the initiative and details about KU's Open Access programme can be found at

This book is included in DOAB.

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  • big data
  • Bio-ethics
  • Biology, Life Sciences
  • Biomedical Sciences
  • Computing & information technology
  • Critical Data Studies
  • Data Ethics
  • Datafication
  • Digital humanities
  • Discourse Ethics
  • Epidemiology & medical statistics
  • Ethical & social aspects of IT
  • Ethical issues & debates
  • Facebook
  • Health Research
  • Health Surveillance
  • Information technology: general issues
  • Informed Consent
  • KUnlatched
  • Life sciences: general issues
  • Mathematics & science
  • Media & Communications
  • Media and Communications
  • Media Studies
  • Medical bioinformatics
  • medicine
  • Medicine: General Issues
  • Predictive analytics
  • Public Health
  • Public health & preventive medicine
  • Social Science / Media Studies
  • Society & culture: general
  • Society & Social Sciences


DOI: 10.16997/book14


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