The Data-Intensive University

Magdalen College, University of Oxford

Previously I have argued that we now live within a horizon of interpretability determined in large part by the capture of data and its articulation in and through algorithms (Berry 2011, 2012, 2014, 2017; see also Golumbia 2009). Software and data shape and mediate our direct experience of political, economic and social systems through the automation of innumerable processes. This I call the data-intensive society, drawing on the notion of a fourth paradigm in science. This is informed by an understanding of the changing practices of scientific work understood as a set of scientific exemplar paradigms. These follow from the (1) experimental science paradigm, which is then replaced by (2) theoretical science, (3) computational science (models), and now (4) data-intensive science. Relatedly, the data intensive economy is an economic realisation of the projected gains and possibilities of the data-intensive scientific milieu. This will create new economic structures but also new social realities and, I would argue, data-intensive subjectivities and hence new problems for society to negotiate. Developing a set of practices around what we might call data-intensive critique and data-intensive ethics by thinking through the connected questions that are raised by the data-intensive society is a key element of this.

So I am keen to connect these questions to what I have started to think about as the data-intensive university and hence to the wider questions raised by a data-centric economy and polity (this post is one of a series where I want to explore and deepen a knowledge of this notion). These shifting social, political and economic forces demand a new distinctive role for the university and speaks to a situation in which universities also want to enhance their individual prestige and intellectual endeavours. It remains a question to the extent to which this new role will help to sustain and augment the existing institutional character of the university but also provide new orientations. I think these are important questions that give an impetus to a set of new long-range research commitments for the university. The concept of a data-intensive university is also, crucially, open for contestation. Therefore, I argue that if there is a need to create a special role for the university in relation to its data environment and new computational cultural milieu then it will need to provide a distinctive university in relation to others. This would have institutional implications in terms of the shape or pattern – the idea – of the university, and hence its organisational structures and its cultures. Indeed, there will undoubtably be a temptation for neoliberal management and corporate techniques being imported into the university: surveillance of staff, intensification of work routines facilitated through these new digital technologies. These will have to be contested continually by faculty and others inside and outside of the university. Now is the time for an alternative programme that needs to be articulated before the infrastructures of computation are solidified and normalised. 

Lincoln College, University of Oxford

John Henry Newman wrote perhaps the most famous idea of the university in 1859 when he argued, “a University…. is a place of teaching universal knowledge”. He maintained that the university had an essential function in the conservation of knowledge and ideas and their transmission to an elite body of largely undergraduates, a model he drew from Oxford. Similarly, Abraham Flexner writing in the 1930s with Johns Hopkins University in mind, argued that the university is “an institution consciously devoted to the pursuit of knowledge, the solution of problems, the critical appreciation of achievement, and the training of [students] at a very high level”. 

But as the varieties of universities began to grow and their internal complexity multiplied, it became seemingly more difficult to identify an essential idea of a university. By the late 1920s, for example, Robert Maynard Hutchins was remarking that the modern university was a set of schools and departments held together by a central heating system. Later in the 1960s, Clark Kerr described the modern university as “a series of individual faculty entrepreneurs held together by a common grievance” over car parking. And today it does sometimes seem like the 21st century university is similarly a set of schools and departments held together by a shared grievance over the e-learning system. But it is important to note that a university ideal has never been frozen in aspic, it has continually adapted over time. In fact the university's very success has been through a process of accretion. 

Arguably the last major change for the universities was the shift in the 1800s to what we now call the modern research university. I am interested in how the institutional pattern grew from the notion that research, as an experimental procedure conducted in a spirit of discovery, could form the basis of a new mission for the university. This emerged particularly in the German universities in the nineteenth century and later became more widely known as the Humboldtian university. The German universities developed the idea that integrating teaching and research within the same institution could be intensified to improve both teaching and the research process. Professors increasingly began to teach methodological skills, greater analytical and theoretical knowledge and tools as part of their courses. This included a growing reliance on field-work, maps and graphs, catalogues, and lists of specialised data to explain to students’ recent scientific advances and ongoing research work. However, it was the American universities that would take these ideas and develop them to a new level of intensity by combining and integrating the English collegial model of teaching and the German research traditions which resulted in the modern American research university. These new universities (particularly John Hopkins and Chicago) had a strong commitment to basic research, to contextualized and applied research and to training researchers. These pioneering universities had a great influence on others, such as Harvard, which soon embraced this new idea of a university. This created a distinctive American institutional structure for a research university which was extremely successful during the twentieth century. This modern research university subsequently became the reference standard for the idea of a university and there can be little doubt that American universities are in a class of their own in terms of their ability to produce world-class research. By continuing to undertake teaching, these universities have been able to develop an important role in contributing new knowledge to the economy and to various organizations and firms in the industrial sector. This connection between academia and the wider society has also created an expectation that teaching should be up-to-date and incorporate new knowledge. The institutional structures of the modern research university thus gave it the capacity to institutionalize and organize the proliferation of specialized knowledge into departments which were very successful over the course of the 20th century in undertaking high quality fundamental knowledge and practical research discoveries.  

Wolfson College, University of Cambridge

Research thus became arguably the foundational concept for the university which meant that the goal of the university was to create new knowledge (research) and transmit and preserve it (teaching). Research was articulated in terms of the project of the nation state, its economic development and the training of an educated citizenry (albeit often an elite). This implied that the state would be required to fund the basic research and the universities develop the capacity to undertake it. 

In my own work, I argue that we are on the verge of a new challenge for the university under the conditions of a society that is based increasingly upon digital knowledge and its economic valorisation. These post-industrial societies are structured around using knowledge and new knowledge production through computational technologies. The acquisition of new skills and these new knowledges are fundamental drivers of innovation in and around an economy based on data, information and digital techniques. As such the university continues to play a key role in undertaking basic research, a highly concentrated output of academia, but also in encouraging its use and innovation. There are two essential platforms for the university in this new economic environment, (1) the creation of new knowledge, and (2) the capacity for the transformation of knowledge into new forms of invention and transformation. I argue that a university’s growth will increasingly depend on its ability to integrate and transform new knowledge, compelling it to equip itself with new structures for research and teaching. This new formal structural capacity is fundamentally reliant on digital processes of creation, capture, experimentation and analysis in research through digital tools, methods, and techniques, combined with a critical capacity to assess theoretical and methodological foundations for such knowledge claims. As such these structures enable a data-intensive research university to flexibly adapt to the kinds of shifts in the core income streams necessary for university sustainability and growth.

At even the most basic level, access to the benefits of computation is still unequally distributed, and social, cultural and political disruptions persist. How can the university contribute to these social problems and thereby to notions of social justice more generally? What is the contribution of an institution that has been traditionally structured as an island of learning, even in the case of the civic universities, how do the boundaries operate and what is the permeability of knowledge?

Today, science and technology policy lacks even a rudimentary capacity to confront the complex implications of a computational society. The acquisition of new digital skills and these new knowledges are now fundamental drivers of innovation in and around an economy based on data, information and digital techniques. As such it is argued that the university has a key role to play in the undertaking of basic data-intensive research, a highly concentrated output of academia, but also in encouraging its use and innovation (now called “impact”). 

Original Design for the University College of Sussex (1960),
which later became the University of Sussex. This building
was designed by Basil Spence and was originally called
College House with a central quad (now called Falmer House).

In this new digital milieu, a university’s growth, and even its survival, will increasingly depend on its capacity to integrate and transform data-intensive knowledge and incorporate new methods for teaching and research. This would mean that a university is not only a research-intensive one but also a data-intensive one. The digital opens up new ways of seeing and enables new methods for undertaking research. As such, a data-intensive university supports efforts to ensure a new spirit of discovery and the promotion of research through the use of computational techniques and practices which will transform the culture of departments in a university. This I believe will have a fundamental transformatory effect on the idea of a mission for the university, and the way in which the institutional pattern and organisation structure of the university is currently constituted. For example, this includes new research into and investment in digital infrastructure (cyberinfrastructure) to support the digital transformation of research activities and to create a culture of digital-intensive research. 

This is also connected to the “turn” to "global challenges", interdisciplinarity, collaborative research, shared teams, and project-based research. It also problematises the notion of “open” as a legitimating concept for scholarly communications and knowledge dissemination, for example in the notion of open-access and open source. This would mean that such a university transforms its research-intensive identity into one that incorporates a data-intensive mission too. With the stress increasingly on the latter. Digital approaches for teaching and research also create the possibility of developing a digital data-intensive teaching environment which forms the base of the diversified pyramid of teaching programmes in the university from undergraduate to those at graduate level.

It remains a question as to whether a data-intensive research university needs a “centre” to the university. The chapel or the library no longer provide that function, and in a future post I want to explore what the status of the centre of a data-intensive university might be. 

These more general trends are both useful starting points for thinking about how the processes enabled by “data-intensive” as an ideal of a university is anchored in a set of norms related strongly to computational techniques and technologies. That is, how ideas, people, infrastructure, business environment, and places are transformed through “digital thinking” or "disruption". This means not only what the effects of expanding data-intensive research capacity of a university might be but also how transforming the digital skills of its students and thereby the wider labour workforce, changes the wider social milieu.


Berry, D. M. (2011) The Philosophy of Software: Code and Mediation in the Digital Age, London: Palgrave Macmillan.

Berry, D. M. (2012) Understanding Digital Humanities, Basingstoke: Palgrave.

Berry, D. M. (2014) Critical Theory and the Digital, New York: Bloomsbury

Berry, D. M. and Fagerjord, A. (2017) Digital Humanities: Knowledge and Critique in a Digital Age, Cambridge: Polity.

Golumbia, D. (2009) The Cultural Logic of Computation, Harvard University Press.


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