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Introducing data

In the 21st century, data makes the world go round. It powers enterprise and connectivity, as oil and steam did in the last two centuries. It comes in many varieties and flavours – ‘raw’ data, ‘processed’ data, ‘big’ data, ‘meta’ data, ‘personal’ data, ‘open’ data, ‘unstructured’ data, to name only a handful that are currently significant... | As the sector begins to get its collective head around data, Graeme Wise sets the scene and introduces Wonkhe’s new data blog – a new initiative dedicated to higher education and its relationship with data.
This article is more than 9 years old

Graeme Wise is a Contributing Editor to Wonkhe.

In the 21st century, data makes the world go round. It powers enterprise and connectivity, as oil and steam did in the last two centuries. It comes in many varieties and flavours – ‘raw’ data, ‘processed’ data, ‘big’ data, ‘meta’ data, ‘personal’ data, ‘open’ data, ‘unstructured’ data, to name only a handful that are currently significant. And all of these categories are loaded with issues of politics and ethics – about governance, ownership, privacy, education, monetisation, and on and on. Governments and corporations measure their largesse in petabytes. Judges deliberate on the ‘right to be forgotten’. Everyday life – entertainment, shopping, and just getting around – is shaped by algorithms. Contemporary society is marinated in the stuff.

The opportunities for higher education are immense. Would-be students can use data more than ever before (to a more limited extent they have always used it) to inform choices of subject and destination. Centres of learning can use data to analyse student habits and behaviours and the factors of strong (and poor) performance – and use the conclusions to shape teaching, learning and the student experience.

Researchers, of all the people in the world the most familiar with the possibilities of data, can use increasingly sophisticated techniques to become more effective and open new ground for discovery. Governments can use data to make judgements about the effectiveness of higher education systems, and employers can use it to make judgements about institutions and their graduates. With more and more ‘open’ data, anyone can be involved in every part of this transformation.

But there are real problems and challenges. We should not allow any room for a hagiography of this agenda, or misplaced utopianism. The vast majority of data is closed, some of it locked up very securely indeed, and not always for good reasons. On the other hand, enormous amounts of data are collected in an ad-hoc fashion and stored inadequately; most of us probably know where we can find a ‘crumbling nuclear stockpile’ of data if we went looking.

In the UK we have a very strong systems and policy infrastructure in place – in the figures of Jisc, HESA, UCAS, and others – but most of the world’s HE sectors are not so fortunate and we may become more interdependent with other systems. Even with that core strength, there are residual problems of the costs of data collection, inconsistent data language and definitions, inadequate connections between both agencies and datasets, all to be addressed.

New policy pressures on higher education institutions to compete more intensively in an evolving market may frustrate potential collaboration, where a delicate balance of competition and collaboration is required to get good results. There are significant issues of capability amongst people in the sector at all levels to handle all this data to good effect – our analytical skills base, our training for innovation, our ethical grounding, all need work. There are problems of sustainable investment – any senior management team in the sector who are not planning for their IT costs and costs of analytical staff to begin rise exponentially in the near future probably needs to think again.

The leadership role for ‘wonks’ in taking this agenda forward and making sense of it through real-world applications is clear. Some members of the community that follow this site work at sector level mainly on wide reaching policy analysis and development, others work within centres of education on policy and practice, and some colleagues straddle these domains. Whatever the perspective, our engagement now with both the opportunities and challenges of this new world of data will be strongly influential on how far the agenda makes a positive difference. Without doubt, it is going to be a major factor shaping the future of higher education, and we can shape how that plays out. So this post represents only an introduction to a new regular strand at Wonkhe on the theme of data. There is a lot of ground to cover.

In the UK context alone, we need to look at the emerging work to redesign the HE ‘data landscape’ being conducted under the auspices of the Higher Education Data and Information Improvement Programme (HEDIIP). This programme has already been looking at the volume of data collections, data language and definitions, the way we categorise subjects of study in our data, and the potential of the Unique Learner Number (ULN) to bring benefits to the sector. It will go on to consider how the overall landscape could operate better, in terms of governance and the relationship between co-ordinating organisations, data collectors, institutions and others.

No small task – but potentially extremely important to ensuring the sector can take full advantage of data in the future. To support this, HESA has recently obtained funding from HEFCE to develop a business case for infrastructure change to implement any recommendations from HEDIIP that the sector agrees to take forward. Elsewhere, exploration of innovative ways for using data is underway. Universities UK is working with the Open Data Institute on a joint project to highlight the potential of ‘open data’ in higher education, while numerous institutions have been progressing their own work on data analytics.

We also need to make our attention run more widely than specific UK based policy initiatives. For example, we need to consider the constantly evolving issues of data ethics that come with greater focus on and deployment of data resources. We should look at comparative cases, illustrating what is happening in this area in other countries and getting a sense of where the UK sector stands. We should look at what has been achieved through the novel use of analytical techniques in other sectors – for instance at the way that media, politics, professional sport, transport have all been significantly affected by a sudden increase in data availability and capability.

Data is a rich seam, and we want to mine it. Higher education has huge advantages in relation to data, and there is every chance that those advantages can be built on and applied to the benefit of all. We want to create a place to think and talk about how that can be made to happen.

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