It seems passé to talk about the ‘big data revolution’ in 2017. Much of the initial hype has subsided, leaving us in a different situation to the one in which big data was expected to sweep away all that had come before. Instead, we have the emergence of data science as well as the institutionalisation of computational methods, albeit unevenly, across the full range of the natural and social sciences. Furthermore, addressing the challenge posed by early waves of big data evangelicism to established methodologies, particularly those with a critical and/or hermeneutic focus, has generated a vast outpouring of creativity with the potential to generate significant reorientations within these disciplines. The ‘big data revolution’ has proceeded in a much more constructive way than those early prophets of epochal change were able to predict.
However, we are still far from harmony within the academy. While the intellectual changes driven by big data are well underway, institutional changes of potentially greater importance are still in their infancy. This is how Susan Halford describes the politics of discipline surrounding big data:
How we define Big Data matters because it shapes our understanding of the expertise that is required to engage with it – to extract the value and deliver the promise. Is this the job for mathematicians and statisticians? Computer scientists? Or ‘domain experts’ – economists, sociologists or geographers – as appropriate to the real-world problems at hand? As the Big Data field forms we see the processes of occupational closure at play: who does this field belong to, who has the expertise, the right to practice? This is of observational interest for those of us who research professions, knowledge and the labour market, as we see how claims to expert knowledge are made by competing disciplines. But it is also of broader interest for those of us concerned with the future of Big Data: the outcome will shape the epistemological foundations of the field. Whether or not it is acknowledged, the disciplinary carve-up of big data will have profound consequences for the questions that are asked, the claims that are made and – ultimately – the value that is derived from this ‘new oil’ in the global economy.
We can see rapid transformation at this level, with expertise in the social and natural sciences responding to the opportunities and incentives which big data has brought with it. The institutional landscape has begun to change, most notably around funding, with important consequences for how individual and collective agents plan their career-path through this environment. However, this is still unfolding within organisations that have not themselves undergone change as a result of big data. It is this which is likely to change in the coming years. As WonkHe reported earlier this week of the consultation on how the Office for Students will regulate providers of higher education in England:
The consultation will also be looking at the nuts and bolts of the OfS – how will it balance the demands of competition and autonomy while maintaining “proportionate” regulatory approaches? How will the remarkable new powers of entry (extreme audit?) be used? What sanctions will be available to the new regulator, and how will they be applied? Following strong ministerial direction, we can also expect measures on senior staff pay to feature prominently, but what form will they take, and will they have any real teeth? And how will approaches compare to other sectors?
Widely expected is an end to regular institutional visits – the “periodic review” is likely to be replaced by a new method for the OfS to use live data to monitor institutions. It may well be easier than the annual submission, but now is a good time to be a big data wonk, as new systems and process will need to be established in institutions to respond to a new approach.
This concern for real time metrics, institutionalising transactional data into the fabric of higher education itself, only seems likely to grow. What does this mean for the politics of discipline? My hunch is that the big data revolution within higher education has only just begun and that it’s eventual form will be different to that which most predicted.