Uncertain Archives: Unknowns, Errors, and Vulnerabilities in Big Data Why: Data production, capture, and dissemination constitute key global themes and challenges today. We are surrounded by immense data archives that constantly accumulate from a wide array of activities organized on all levels of society: from global search engines to local smart cities; from public health monitoring to personal self-tracking. While borne out of a desire to innovate, securitize, and escape human error, it is becoming increasingly clear that big data archives also bring with them new uncertainties in the form of new bias dynamics, new forms of systemic errors, and new ethical dilemmas. The aim of this project is to develop a theoretical framework for understanding the pertinent ethical and epistemological questions that have arisen with the prevalence of big data analytics. How: Grounded in the humanities, but part of the emerging field of Critical Data Studies, it is the contention of this project that there are significant insights to be gained from the application of cultural theories of the archive. By operationalizing aesthetics as a methodology and developing a theoretical framework, the research group offers an innovative and productive environment for theorizing the uncertainties that other disciplines seem to agree govern these large and dynamic archives, thereby facilitating the necessary interdisciplinary dialogue concerning the nature of big data environments. With this approach, based on cultural and aesthetic theory and focused on case studies on smart city and quality of life technologies, the aim is to make the research group a key international hub for a growing international and interdisciplinary research environment. What: The object of study for this project – the uncertainties embedded in big data environments – is of central relevance to society in so far as more and more public institutions and private organizations are increasingly reliant of data aggregation and big data analytics in their response to the key challenges that face us in the twenty-first century. Population growth, distribution of resources and the global cost of health are all acute challenges that will increasingly be addressed by way of big data analytics. The case studies on the unknowns, errors and vulnerabilities of smart city and quality of life technologies offered here will generate new insights that can inform and make for more sustainable responses to these grand challenges.