ABSTRACT
This chapter discusses the ethical implications of research with large datasets with particular reference to issues of consent and re-identification. These issues are important not only for researchers who undertake secondary data analysis, but also for those involved in primary data collections who intend to make their data available for reuse. A rapid rise in the application of big-data methods and secondary analysis, particularly in health geography, has brought with it a new series of ethical dilemmas. Consent is a central pillar of ethical research. Datasets are said to have been de-identified if "elements that might immediately identify a person or organization have been removed or masked". For health geographers combining big health data – such as medical data or ambulance-dispatch records – with geospatial technologies, the ethical issues are more complex. A number of masking methods – applied either before or after analysis – have been developed to protect locational privacy while allowing valid spatial analysis to be performed.
