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If we want to support researchers, the data needs to tell a story

The sector's capacity to gather data on researchers is growing. Steve Goldenberg and Sofia Ropek ask what stories the data might tell
This article is more than 4 years old

Steve Goldenberg is President and Chief Product Officer at Interfolio.

Sofia was an Associate Editor at Wonkhe.

Though the sector runs on data, we’re not always good at collecting data in one place or making it tell a coherent story. Especially when there is no statutory or regulatory pressure to report it.

Many organisations have pledged to abide by the expectations of the updated Concordat to support the career development of researchers. But delivering on these aspirations will only be possible if they also commit to collecting the data that will allow them to understand, monitor and strengthen their practice across the Concordat’s themes of environment, employability, and professional development.

There are several ways of telling stories about research. Systematic collection of data on the outcomes and impact of research can contribute to our understanding of what unfolds from investment in particular areas. And capturing narratives can benefit researchers and help scholars to map out diverse career paths.

Put your eggs in one basket

An integrated approach to data collection is crucial, because it can capture both the person and their research. Steve Joy, head of researcher development at the University of Cambridge, is amalgamating a range of different datasets to get a rounded view of researcher development, incorporating both formal professional development training and statistics or language training offered by individual departments.

Rebecca Lambert, director of planning and performance insight at the University of Birmingham, is similarly interlaying different data sources to get a better sense of the range of professional development taking place across the researcher community.

Researcher development provision has proliferated, and become more specialised. Though a positive trend in the round, this can make it hard to offer a cohesive package of opportunities to researchers, and to collect data on who is engaged in what forms of professional development. A more holistic view gives better and deeper data to support researchers in mapping their development trajectories and measuring their impact, as well as avoiding department silos.

Making a wide range of training opportunities more accessible across departments also means that early-career researchers can respond to a more mobile and global research landscape.

Stories are important

But a more open and mobile research environment can make it harder for researchers to plan for a well-defined career trajectory, which is where stories about potential career paths can help. Steve Joy believes that “there isn’t always enough attention paid to a PhD as a piece of identity-work” and emphasises the power of stories to help people forge their identities as research professionals. Careers services often use stories to illustrate potential fields of work and opportunities, especially for undergraduate students, but postgraduate and postdoctoral researchers would similarly benefit from more narrative-based data.

Through reading other people’s stories, we develop our expectations and our sense of self in relation to other people. One fine example is the Think Ahead blog from the researcher development team at the University of Sheffield, which posts regular careers stories on where people with PhDs go.

As a member of Researchers14, Steve believes there is a widespread challenge with “delivering support to a diverse community at scale, while recognising that the best way to deliver support is to make it as personalised as possible”. Bringing stories into workshops shifts them from purely informational to researcher-led and personal.

Where’d you go, postdocs?

Increasingly, organisations are able to gather data on research outcomes as well as outputs, meaning that data can help us think about pathways to impact. It’s also now possible to record the range of academic work that contributes to the richness of the research environment, including speaking at conferences and working with the media.

Systematically capturing this data helps to inform organisations about researcher behaviour, and could highlight troubling patterns and help identify bias: who gets put forward as an expert? Who is overloaded with “service” activity at the expense of research and teaching?

There is, however, one key gap. In the UK there is a distinct lack of longitudinal data on where postdoctoral researchers progress to, unlike the US, Denmark and Germany where postdoctoral researcher destination data is collected at a national level. Combining qualitative data with destination data could help universities develop training and mentoring, and help researchers get a sense of their career options, making the research landscape more visibly open and porous.

Cambridge University’s alumni relations office has recently introduced a structured postdoc alumni community, and is keeping in touch with postdocs to make clear that they value them, and to track where they go. Researchers benefit from these lifelong communities, especially researchers moving around the country, or researchers between jobs – even more so if these communities come with access to journals or careers support.

Data-driven equality work

Data can support a more inclusive research environment and a more diverse body of researchers – if we have it.

Universities rarely have the same data on staff that they have on students, which can hinder equality and diversity initiatives. Rebecca at Birmingham finds that it’s far easier to draw conclusions from student data, which is often comprehensive, integrated, and easier to compare with other institutions. James Wilsdon, professor of research policy at the University of Sheffield regrets the lack of good data on research students in particular, and the abundance of “patchy” data.

Assuming that Office for Students data efforts will continue to focus on undergraduate students, James wonders whether UK Research and Innovation should take up the baton and collect data on postgraduate students, which would make it easier to target access programmes, and easier to understand postdoctoral researcher populations.

When we do have the data, we don’t always think about how one dataset might interact with another. Intersectional research acknowledges that people are shaped by multiple factors, perhaps not solely gender or ethnicity, for example, but the interaction of the two. James Wilsdon remarks that for equality and diversity programmes to be effective, universities need to deeply understand the people who live in their area and their broad socio-economic context: “there’s a huge amount that’s quite particular to each different mix of students admitted”.

Data fuels connections

Clearly, the more data that is available, the more support can be tailored to communities of researchers. But data can also give researchers agency in relation to their work and career path, and allow them to feel connected to a network. Alexandra Freeman, director of the Winton centre for risk and evidence communication, is developing Octopus, a new open-access, community-owned publishing platform which aims to connect researchers and smooth the process of publishing by breaking work into micro-publications from hypotheses to datasets. The data Octopus collects on research processes could eventually help develop learning tools for researchers, and the site data will all be freely available to download and analyse.

By making visible researchers and research processes, Octopus will help early-career researchers in particular. But the Octopus platform is also about stories: Alex objects to the belief that “to succeed in science, you need to think back from the headline”, as she heard one scientist say, and she wants to break up the neat narrative of inspiration-to-discovery.

Research processes and career trajectories can be messier and more complicated than they appear. The more this messiness is visible and digestible, the less researchers will feel that there is an archetype of a “star researcher” that they must mould themselves into.

This article is the second in a three-part series on the future academic research workforce, in association with Interfolio. Find out how Interfolio helps universities track research impact, improve academic diversity, and manage academic activity data. You can read the first in the series on research diversity here

Join us at Wonkfest on 4-5 November 2019 to hear from John Kingman, Chair of UK Research and Innovation and be part of the debate on how best to support the research workforce. 

One response to “If we want to support researchers, the data needs to tell a story

  1. The proposal here for a nationally co-ordinated and systematic collection of career data is well made. Without evidence of where researchers go it will be difficult, if not impossible, for the UK HE sector to articulate the contribution made by researchers to the ambitious 2.4% GDP target. This was reinforced by Chris Skidmore’s announcement of the increase in HEIF and expectations that PhD and postdocs will make a difference to Knowledge Exchange and the economy. If we can’t measure it, qualitatively or quantitatively, we open ourselves up to fail from the start. Each university signed up to the revised Researcher Development Concordat 2019 will do their best to implement it but the collection of an evidence base would be much better collated at national level.

    Dr Karen Clegg, Head of Research Excellence Training, University of York. Writing in a personal capacity.

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