Citizens of networked societies are almost incessantly accompanied by ecologies of images. These ecologies of still and moving images present a paradox of uncertainties emerging along with certainties. Images appear more certain as the technical capacities that render them visible increase. At the same time, images are touched by more uncertainty as their numbers, manipulabilities, and contingencies multiply. With the emergence of big data, the image is becoming a dominant vehicle for the construction and presentation of the truth of data. Images present themselves as so many promises of the certainty, predictability, and intelligibility offered by data. The focus of this book is twofold. It analyses the kinds of images appearing today, showing how they are marked by a return to modern photographic emphases on high resolution, clarity, and realistic representation. Secondly, it discusses the ways in which the uncertainty of images is increasingly underscored within such reiterated emphases on allegedly certain visual truths. This often involves renewed encounters with noise, grain, glitch, blur, vagueness, and indistinctness. This book provides the reader with an intriguing transdisciplinary investigation of the uncertainly certain relation between the cultural imagination and the techno-aesthetic regime of big data and ubiquitous computing. This book was originally published as a special issue of Digital Creativity.

Citizens of networked societies are almost incessantly accompanied by ecologies of images. These ecologies of still and moving images present a paradox of uncertainties emerging along with certainties. Images appear more certain as the technical capacities that render them visible increase. At the same time, images are touched by more uncertainty as their numbers, manipulabilities, and contingencies multiply. With the emergence of big data, the image is becoming a dominant vehicle for the construction and presentation of the truth of data. Images present themselves as so many promises of the certainty, predictability, and intelligibility offered by data. The focus of this book is twofold. It analyses the kinds of images appearing today, showing how they are marked by a return to modern photographic emphases on high resolution, clarity, and realistic representation. Secondly, it discusses the ways in which the uncertainty of images is increasingly underscored within such reiterated emphases on allegedly certain visual truths. This often involves renewed encounters with noise, grain, glitch, blur, vagueness, and indistinctness. This book provides the reader with an intriguing transdisciplinary investigation of the uncertainly certain relation between the cultural imagination and the techno-aesthetic regime of big data and ubiquitous computing. This book was originally published as a special issue of Digital Creativity.

'Panic' and 'mourning' are two pivotal constructs that often emerge and interplay under circumstances of conflict, violence, crisis, and catastrophe, both natural and man-made. Whereas panic tends to crop up during the experience of violent events, mourning, on the other hand, relates to the aftermath of a brutal disruption and to the way humans try to make sense of it retrospectively. Conversely, violent events can leave a thread of panic in their aftermath, while mourning can be unsettled, interrupted or even refuelled by another catastrophic incident. From an international and inter-disciplinary outlook, this volume wishes to address questions at the interface of panic and mourning and their impact on practices in literature, media, and the arts. Since violent events take place within cultures that will draw from their traditions, memories and systems of beliefs in order to process them, the authors of this book aim precisely at discussing the effects of calamity upon the cultural structure and the way literary, artistic and media practices not only reproduce individual and collective anxieties but also generate knowledge and reshape the cultural formation within which they emerge.

Scholars from a range of disciplines interrogate terms relevant to critical studies of big data, from abuse and aggregate to visualization and vulnerability. This pathbreaking work offers an interdisciplinary perspective on big data, interrogating key terms. Scholars from a range of disciplines interrogate concepts relevant to critical studies of big data--arranged glossary style, from from abuse and aggregate to visualization and vulnerability--both challenging conventional usage of such often-used terms as prediction and objectivity and introducing such unfamiliar ones as overfitting and copynorm. The contributors include both leading researchers, including N. Katherine Hayles, Johanna Drucker and Lisa Gitelman, and such emerging agenda-setting scholars as Safiya Noble, Sarah T. Roberts and Nicole Starosielski.