The Big Data Agenda
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 www.knowledgeunlatched.org.
This book is included in DOAB.
Why read this book? Have your say.
You must be logged in to comment.
Rights InformationAre you the author or publisher of this work? If so, you can claim it as yours by registering as an Unglue.it rights holder.
- 48 - pdf (CC BY-NC-ND) at Unglue.it.
- 52 - epub (CC BY-NC-ND) at Unglue.it.
- 35 - pdf (CC BY-NC-ND) at OAPEN Library.
- 34 - pdf (CC BY-NC-ND) at OAPEN Library.
- 71 - pdf (CC BY-NC-ND) at OAPEN Library.
- 72 - pdf (CC BY-NC-ND) at OAPEN Library.
- 132 - mobi (CC BY-NC-ND) at Unglue.it.
- 122 - pdf (CC BY-NC-ND) at Unglue.it.
- 118 - epub (CC BY-NC-ND) at Unglue.it.
- !bisac SOC052000
- big data
- Biomedical Sciences
- Critical Data Studies
- Data Ethics
- Digital humanities
- Discourse Ethics
- Health Research
- Health Surveillance
- Media & Communications
- Predictive analytics
- Public Health