<p>This dissertation details one of the first lines of inquiry into the rhetorical strategies used in scientific data analysis. The study primarily concerns the relationships between data work and knowledge making in the analysis of so-called “big data,” and how rhetoric and technical communication theories might inform those relationships. Hinging on five months embedded at a national science laboratory, this study uses ethnographic methods to detail the ways in which data analysis is neither purely data-driven and objective, nor purely situated in a local context or problem. Rather, data work requires both analytical processes and artful <i>techne</i> embedded in ongoing reflective praxis. As purely analytic, data work focuses on mathematical treatments, step by step procedures and rote formulas. As <i>techne</i>, data work requires interpretation. Rhetorical data analysis is not the opposite of data-driven work. Instead, rhetorical <i>techne</i> stands as the midpoint between the extremes of purely data-driven and purely context-driven analysis. Based on three cases that compare the practices of data novices, seasoned experts, and interdisciplinary teams, I argue that the ways in which scientists go about their data cleaning, collaboration, and analysis change based on their levels of expertise and the problem at hand. A number of principles that outline how data analysis is a form of rhetorical inscription are also defined, including the ways data dictionaries, model building and the construction of proxies intimately link scientific insights with language. The set of principles detailed in this dissertation are key areas that should be considered in both data science education and professional and technical writing curricula. Therefore, the project should be of particular interest to instructors and administrators in both Technical Writing and Data Science programs, as well as well as critical data studies scholars.</p>

In this thesis I examine current and future uses of Big Data in archaeology. New technologies have enabled a range of data capture, data storage, and analyses. Digitization in our society has brought new ways of working for archaeologists and the increased amount of data affects how we can understand the world. Big Data reshapes the research process and creates new risks and opportunities for digital archaeology. Several sources have been examined in order to understand what this looks like in archaeology, such as articles published in the journal Internet Archaeology, a questionnaire answered by archaeologists and digital humanists, interviews by two representatives of archaeology, one representative of digital humanities and a chatbot.  The archaeological material has become more accessible. Big Data contributes to data-driven science which enforces a paradigm shift. As data is created faster in various ways and to a voluminous extent archaeologists are forced to work with issues related to the management and storage of data. Digital humanists and archaeologists emphasize that Big Data brings efficient working methods and analyses that can contribute with new questions and reliable knowledge. This can increase the relevance of humanities subjects in the research community. That being said, the nature of Big Data often includes quantitative structured data and its result can be characterized as objective and trustworthy. Perceptions of data as bias-free and that Big Data affects theory to become obsolete may jeopardize the use of source criticism. There is a lack of standardization in how to measure and store data in archaeology which contributes to decontextualization of data. I urge that archaeologists should reflect on how cutting edge data-modeling and AI-modeling can assist in the research process as well as how ethical aspects of data should be considered in order not to risk interpretations overlooking people, places and practices.

This dissertation is a theoretical study of the relationship between digitality, knowledge, and power in the age of Big Data. My argument is that human medical research on psychedelic substances supports a critique of what I call "the data episteme." I use "episteme" in the sense developed by philosopher Michel Foucault, where the term describes an apparatus for determining the properties associated with the epistemic condition of scientificity. I write that the data episteme suppresses bodies of knowledge which do not bear the epistemic virtues associated with digital data. These include but are not limited to the capacities for positivistic representation and translation into discrete digital media. Drawing from scientific reports, I demonstrate that certain forms of knowledge regarding the therapeutic mechanisms of psychedelics cannot withstand positivistic representation and digitization. Henceforth, psychedelic research demands frameworks for epistemic legitimation which differ from those predicated on the criteria associated with the data episteme. I additionally claim that psychedelic inebriation promotes a form of thinking which has been called, by various theorists, "negative," "abstract," or "idiosyncratic" thought. Whereas the data episteme denies the existence of negative thought, psychedelic research suggests that this mental function is essential to the successful deposition of psychedelic substances as adjuncts to psychotherapy. For the reasons listed above, psychedelic science provides a uniquely salient lens on the normative operations of the data episteme. In the course of suppressing non-digitizable knowledge, the data episteme implements what Foucault conceptualizes "knowledge-power," a term which affirms the fact that there is no meaningful difference between knowledge and power. Here, "power" may be defined as the power to promote but also to retract conditions on which phenomena may exist across all sites of social, intellectual, and political construction. I write that the data episteme seeks to both nullify the preconditions for negative thought and to naturalize the possibility of an infinite expansion of human mental activity, which in turn figures mentality as an inexhaustible resource for the commodity of digital data. The data episteme therefore reifies the logic of ceaseless economic proliferation, and as such, abets technologized capitalism. In the event that the data episteme fulfills its teleological goal to become total, virtually all that is thinkable would yield to economic subordination. I present psychedelic science as a site where knowledge which challenges the data episteme is empirically necessary, and which, by extension, attests to the existence of that which cannot be economically subsumed. / Doctor of Philosophy / In the age of Big Data, scientists draw upon the ever-expanding quantities of data which are produced, circulated, and analyzed by digital devices every day. As data grow in number, digital tools gain in their ability to yield precise and faithful information about the objects they represent. It would appear that all forms of knowledge may one day be perfectly replicated in the form of digital data. This dissertation claims that certain forms of knowledge cannot be digitized, and that the existence of non-digitizable knowledge has important implications for both science and politics. I begin by considering the fact that digital tools can only produce knowledge about phenomena which permit digitization. I claim that this limitation necessarily restricts the sorts of information which digital devices are capable of generating. I also observe that the digital turn has inaugurated a novel mode of capitalist economic production based on the commodity of digital information. Thus, the increasing dependence of scientific authority on digital methods is also a concern for political economy. I argue that the reliance of scientific authority on digital data restricts the scope of scientific inquiry and makes ceaseless economic expansion appear both necessary and inevitable. It is therefore critical to indicate sites of research and practice where non-digitizable knowledge plays an essential role in informing scientific processes. Such an indication is not only pertinent to scientific research, but points up the ways in which data facilitate unregulated economic growth. Psychedelic drug research serves as my lens on digitality and political economy. Specifically, I explore the ways in which quantitative and computational methodologies have been used and critiqued by scientists who study the psychiatric benefit of psychedelics on human consciousness. Taking a historical approach, I demonstrate that psychedelic scientists have always faced the paradoxical task of translating the unusual and ineffable effects of psychedelics into discrete, measurable variables. This quandary has become more pronounced in the age of digital tool use, as such tools rest on the logic of metrical and discrete analysis. I suggest that the therapeutic mechanisms of psychedelics can only be fully revealed by methodological techniques which explicitly address the epistemic limitations of digital data. Noting that the ascendance of Big Data is contemporaneous with a rise of interest in psychedelics as adjuncts to psychotherapy, I assert that psychedelic science provides abundant materials for a critique of the ostensive epistemic authority of digital data, which operates as an alibi for technologized capitalism.