Although true in some aspects, the suggested characterization of today’s science as a dichotomy between traditional science and data-driven science misses some of the nuance, complexity, and possibility that exists between the two positions. Part of the problem is the claim that Data Science works without theories. There are many theories behind the data that are used in science. However, for data science, the only theories that matter are those in mathematics, statistics, and computer science. In this conceptual paper, we (...) add two other philosophy of science tenets, experiments and data, to the discussion to create a more nuanced view of how data science uses theories. Following Ihde’s concept of technoscience and the incessant quest for more precision, magnification, and resolution, we argue that technology-driven science created a need for more technology-driven science, culminating in data science. Further, we adapt Hacking and Galison’s views on physics to argue that data science is also an experimental science, which uses data objects in experiments. Drawing from Heelan, we called these objects “data-objects-for-knowing”. Finally, we conclude that data science is a science to study artificially created phenomena—a science to study the data manipulated by the equations and operations of AI. It disregards the connections between data and the real world that were carefully built by the theories from other sciences. In the experiments of data science, data are the world itself. The knowledge created by data science is purposely disconnected from any theory from other sciences; it is a knowledge for the sake of itself. (shrink)

The modern abundance and prominence of data have led to the development of “data science” as a new field of enquiry, along with a body of epistemological reflections upon its foundations, methods, and consequences. This article provides a systematic analysis and critical review of significant open problems and debates in the epistemology of data science. We propose a partition of the epistemology of data science into the following five domains: (i) the constitution of data science; (ii) the kind of enquiry (...) that it identifies; (iii) the kinds of knowledge that data science generates; (iv) the nature and epistemological significance of “black box” problems; and (v) the relationship between data science and the philosophy of science more generally. (shrink)

Before the EU General Data Protection Regulation entered into force in May 2018, we witnessed an intense struggle of actors associated with data-dependent fields of science, in particular health-related academia and biobanks striving for legal derogations for data reuse in research. These actors engaged in a similar line of argument and formed issue alliances to pool their collective power. Using descriptive coding followed by an interpretive analysis, this article investigates the argumentative repertoire of these actors and embeds the analysis in (...) ethical debates on data sharing and biobank-related data governance. We observe efforts to perform a paradigmatic shift of the discourse around the General Data Protection Regulation-implementation away from ‘protecting data’ as key concern to ‘protecting health’ of individuals and societies at large. Instead of data protection, the key risks stressed by health researchers became potential obstacles to research. In line, exchange of information with data subjects is not a key concern in the arguments of biobank-related actors and it is assumed that patients want ‘their’ data to be used. We interpret these narratives as a ‘reaction’ to potential restrictions for data reuse and in line with a broader trend towards Big Data science, as the very idea of biobanking is conceptualized around long-term use of readily prepared data. We conclude that a sustainable implementation of biobanks needs not only to comply with the General Data Protection Regulation, but must proactively re-imagine its relation to citizens and data subjects in order to account for the various ways that science gets entangled with society. (shrink)

Over the past two decades urban social life has undergone a rapid and pervasive geocoding, becoming mediated, augmented and anticipated by location-sensitive technologies and services that generate and utilise big, personal, locative data. The production of these data has prompted the development of exploratory data-driven computing experiments that seek to find ways to extract value and insight from them. These projects often start from the data, rather than from a question or theory, and try to imagine and identify their potential (...) utility. In this paper, we explore the desires and mechanics of data-driven computing experiments. We demonstrate how both locative media data and computing experiments are ‘staged’ to create new values and computing techniques, which in turn are used to try and derive possible futures that are ridden with unintended consequences. We argue that using computing experiments to imagine potential urban futures produces effects that often have little to do with creating new urban practices. Instead, these experiments promote Big Data science and the prospect that data produced for one purpose can be recast for another and act as alternative mechanisms of envisioning urban futures. (shrink)

The debate on the right to be forgotten on Google involves the relationship between human information processing and digital processing by algorithms. The specificity of digital memory is not so much its often discussed inability to forget. What distinguishes digital memory is, instead, its ability to process information without understanding. Algorithms only work with data without remembering or forgetting. Merely calculating, algorithms manage to produce significant results not because they operate in an intelligent way, but because they “parasitically” exploit the (...) intelligence, the memory, and the attribution of meaning by human actors. The specificity of algorithmic processing makes it possible to bypass the paradox of remembering to forget, which up to now blocked any human-based forgetting technique. If you decide to forget some memory, the most immediate effect is drawing attention to it, thereby activating remembering. Working differently from human intelligence, however, algorithms can implement, for the first time, the classical insight that it might be possible to reinforce forgetting not by erasing memories but by multiplying them. After discussing several projects on the web which implicitly adopt this approach, the article concludes by raising some deeper problems posed when algorithms use data and metadata to produce information that cannot be attributed to any human being. (shrink)

Epidemiology is a field torn between practices of surveillance and methods of analysis. Since the onset of COVID-19, epidemiological expertise has been mostly identified with the first, as dashboards of case and mortality rates took centre stage. However, since its establishment as an academic field in the early 20th century, epidemiology’s methods have always impacted on how diseases are classified, how knowledge is collected, and what kind of knowledge was considered worth keeping and analysing. Recent advances in digital epidemiology, this (...) article argues, are not just a quantitative expansion of epidemiology’s scope, but a qualitative extension of its analytical traditions. Digital epidemiology is enabled by deep and digital phenotyping, the large-scale re-purposing of any data scraped from the digital exhaust of human behaviour and social interaction. This technological innovation is in need of critical examination, as it poses a significant epistemic shift to the production of pathological knowledge. This article offers a critical revision of the key literature in this budding field to underline the extent to which digital epidemiology is envisioned to redefine the classification and understanding of disease from the ground up. Utilising analytical tools from science and technology studies, the article demonstrates the disruptive expectations built into this expansion of epidemiological surveillance. Given the sweeping claims and the radical visions articulated in the field, the article develops a tentative critique of what I call a fantasy of pathological omniscience; a vision of how data-driven engineering seeks to capture and resolve illness in the world, past, present and future. (shrink)

Web-based platforms play an increasingly important role in managing and sharing research data of all types and sizes. This article presents a case study of the data storage, sharing, and management platform Figshare. We argue that such platforms are displacing and reconfiguring the infrastructure of norms, technologies, and institutions that underlies traditional scholarly communication. Using a theoretical framework that combines infrastructure studies with platform studies, we show that Figshare leverages the platform logic of core and complementary components to re-integrate a (...) presently splintered scholarly infrastructure. By means of this logic, platforms may provide the path to bring data inside a scholarly communication system still optimized mainly for text publications. Yet the platform strategy also risks turning over critical scientific functions to private firms whose longevity, openness, and corporate goals remain uncertain. It may amplify the existing trend of splintering infrastructures, with attendant effects on equity of service. (shrink)

This article introduces the Culturally Meaningful Networks (CMN) approach. Following a pragmatist perspective of social mechanisms more broadly, it develops and demonstrates an approach to understanding networks that incorporates both structure and meaning and that leverages time to understand how these aspects influence each other. I apply this approach to investigate a longstanding puzzle about why some of those who leave military service for civilian life fare well, and others badly. In a mixed-methods analysis, I follow a sample of individuals (...) moving through the transition from military to civilian life in the contemporary United Kingdom. I find that the higher the proportion of alters (i.e., “contacts”) with a military background in the networks of leavers before discharge, the worse they fare after discharge. The CMN approach helps me locate a specific structural embedding that explains the presence or absence of durable cultural frames that set the context for the actual experience of the transition and cause problems during it. Attention to the temporal unfolding of network structure and social meaning is essential to bringing out this finding. By re-embedding networks within people’s experiences over time, the CMN approach helps grasp the distinctions by which leavers understand their interactions. I conclude by arguing that the CMN approach has implications for network sociology and cultural sociology that go beyond this substantive case. (shrink)

Recent works have suggested an analytical complementarity in mixing big and thick data sources. These works have, however, remained as programmatic suggestions, leaving us with limited methodological inputs on how to archive such complementary integration. This article responds to this limitation by proposing a method for ‘blending’ big and thick analytical insights. The paper first develops a methodological framework based on the cognitivist linguistics terminology of ‘blending’. Two cases are then explored in which blended spaces are crafted from engaging big (...) and thick analytical insights with each other. Through these examples, we learn how blending processes should be conducted as a rapid, iterative and collaborative effort with respect for individual expertise. Further, we demonstrate how the unique, but often overlooked, granularity of big data plays a key role in affording the blending with thick data. We conclude by suggesting four commonly appearing blending strategies that can be applied when relying upon big and thick data sources. (shrink)

This article adapts the ethnographic medium of the diary to develop a method for studying data and related data practices. The article focuses on the creation of one data diary, developed iteratively over three years in the context of a national centre for monitoring disasters and natural hazards in Brazil. We describe four points of focus involved in the creation of a data diary – spaces, interfaces, types and situations – before reflecting on the value of this method. We suggest (...) data diaries are able to capture the informal dimension of data-intensive organisations; enable empirical analysis of the specific ways that data intervene in the unfolding of situations; and as a document, data diaries can foster interdisciplinary and inter-expert dialogue by bridging different ways of knowing data. (shrink)

As researchers we often find ourselves grappling with social media platforms and data ‘at close quarters’. Although social media platforms were created for purposes other than academic research – which are apparent in their architecture and temporalities – they offer opportunities for researchers to repurpose them for the collection, generation and analysis of rich datasets. At the same time, this repurposing raises an evolving range of practical and methodological challenges at the small and large scale. We draw on our experiences (...) and empirical data from two research projects, one using Facebook Community Pages and the other repurposing Facebook Activity Logs. This article reflects critically on the specific challenges we faced using these platform features, on their common roots, and the tactics we adopted in response. De Certeau’s distinction between strategy and tactics provides a useful framework for exploring these struggles as located in the practice of doing social research – which often ends up being tactical. This article argues that we have to collectively discuss, demystify and devise tactics to mitigate the strategies and temporalities deeply embedded in platforms, corresponding as far as possible to the temporalities and the aims of our research. Although combat at close quarters is inevitable in social media research, dialogue between researchers is more than ever needed to tip the scales in our favour. (shrink)

This paper is a critical assessment of the epistemological impact of the systematic quantification of nature with the accumulation of big datasets on the practice and orientation of ecological science. We examine the contents of big databases and argue that it is not just accumulated information; records are translated into digital data in a process that changes their meanings. In order to better understand what is at stake in the ‘datafication’ process, we explore the context for the emergence and quantification (...) of biodiversity in the 1980s, along with the concept of the global environment. In tracing the origin and development of the global biodiversity information facility we describe big data biodiversity projects as a techno-political construction dedicated to monitoring a new object: the global diversity. We argue that, biodiversity big data became a powerful driver behind the invention of the concept of the global environment, and a way to embed ecological science in the political agenda. (shrink)

The experimental practice in contemporary molecular biology oscillates between the creativity of the researcher in tinkering with the experimental system, and the necessity of standardization of methods of inquiry. Experimental procedures, when standardized in lab protocols, might definitely be seen as actual recipes. Considering these protocols as recipes can help us understand some epistemological characteristics of current practice in molecular biology. On the one hand, protocols represent a common ground, i.e. the possibility of reproducibility, which constitutes one of the essential (...) properties for contemporary science to define an actual discovery. At the same time, however, protocols are flexible enough to be adapted by the individual researcher (within a space of maneuver given by the experimental system and by the practices that each individual discipline gives to itself) to his/her specific needs. These variations, just like the recipes, remind us that the legitimacy of an experimental practice, involves both objective and subjective constraints and it is articulated on a fuzzy background rather than a rigid and clear context. Moreover, looking at experiments according to this perspective can provide a key to understanding how different forms of science (which adopt different methodologies but which investigate the same phenomena), such as computational biology, are precisely different in the use of a different “cookbook”.Indeed, given the procedural/operational realism of biologists towards phenomena, the clash of different procedures has opened a discussion also about the nature and the meaning of the obtained results. Thus, according to the recipe-perspective that, the methodological struggle over the nature of biological phenomena (and their ways of discovery) among scientists, might be seen as a not always explicit, epistemological debate, however coming from the practice of science itself. (shrink)

The modern abundance and prominence of data has led to the development of “data science” as a new field of enquiry, along with a body of epistemological reflections upon its foundations, methods, and consequences. This article provides a systematic analysis and critical review of significant open problems and debates in the epistemology of data science. We propose a partition of the epistemology of data science into the following five domains: (i) the constitution of data science; (ii) the kind of enquiry (...) that it identifies; (iii) the kinds of knowledge that data science generates; (iv) the nature and epistemological significance of “black box” problems; and (v) the relationship between data science and the philosophy of science more generally. (shrink)

The article presents a conceptual framework for distinguishing different sorts of heterogeneous digital materials. The hypothesis is that a wide range of heterogeneous data resources can be characterized and classified due to their particular configurations of hypertext features such as scripts, links, interactive processes, and time scalings, and that the hypertext configuration is a major but not sole source of the messiness of big data. The notion of hypertext will be revalidated, placed at the center of the interpretation of networked (...) digital media, and used in the analysis of the fast-growing amounts of heterogeneous digital collections, assemblages, and corpora. The introduction summarizes the wider background of a fast-changing data landscape. (shrink)

The objective of this work is to analyse the phenomena and the implications of hyperglobalization on current companies. To introduce this purpose, we are going to review the different processes of global economic cohesion produced throughout history. We will focus on the hyperglobalization stage and on the effect that hyperconnectivity has had for companies and their operation. We will analyze the phenomenon of big data, his new technological innovations and how they have affected the companies act and the global society. (...) Finally, we will present an ethical analysis of these new technological phenomena and their implications for society. (shrink)

The growing importance of the computational turn deeply affected the landscape of the social sciences and humanities. One of the most profound transformations caused by the development of digital technologies is the changes of the practice conditions and the production of knowledge. In recent years, French academics working in the humanities and social sciences have been devoting attention to the practices of "Digital Humanities", a new territory that fosters collaboration, openness, and enhancement of knowledge. The scope of this work is (...) bounded to ten special thematic issues in nine French academic journals. The aim is to map main themes and emerging practices, in terms of research, knowledge production and dissemination, and also the modalities that allow Digital Humanities to develop new social and editorial assignments. The corpus is composed of seventy-three articles in nine academic journals, dedicated to various and differentiated topics of "Digital Humanities". (shrink)