In search of missing princes: what drives repository views?

By Lara Skelly, Open Research Manager for Data and Methods, Loughborough University Library

Sleeping Beauty slumbers for decades in her tower until she is woken by a prince, whom she marries, and they live happily ever after. We all know the story, but what if the prince was gone when she awoke? Where would she find her happily ever after? 

The case of the missing prince is not a tale that everyone knows, but it might be familiar to those reporting on the impact of their research. Sleeping Beauties in research are articles1 that lie largely undiscovered for a period until they are cited, mentioned in the media or otherwise woken up [source]. If the prince did the proper thing and cited the article, then happily ever after could be a sure ending, but many princes do not conform to these standard practices and slip away before they are discovered. 

Take, for example, Karen Blay’s thesis on resilience in projects. First uploaded in 2017, it received a few hundred views each year, when suddenly, in July 2022, there were over 2000. Karen was on leave for much of the year and is at a loss as to what might have sparked this level of interest, particularly from Cardiff, London, Helsinki and Amsterdam which all reflected over 300 views that month. 

Korbinian Moeller is similarly unsure what caused the bump in the views of his paper, Potential and limits of game-based learning. Since its upload to Loughborough University’s Research Repository, it’s never had more than a hundred views in a month. Until, inexplicably, it was viewed almost 500 times in August 2022, most of them from Seychelles and Australia. Presumably, the prince resides out there. 

Princes are easier to track if you create your own. Lise Jaillant tweeted about her article, which had just been published in Open Access. The tweet was seen over 13 000 times, easily marking itself the prince that led to 600+ views in January 2023, whereas previous months never saw more than twenty-five views. 

Knowing your prince is a good first step in tracking impact. After all, views are necessary precursors to the change that any research project could make. But the happily-ever-after of impact takes more than just finding the prince. Anyone with a messy life knows that happily can happen in small moments just as easily as in the big moments; that happily can happen instantaneously or after years of a long slog. Happily is not quantifiable, even though one could count the happy moments. So too, with impact, which can happen on a large scale or small, immediately or delayed. As our Responsible use of research metrics policy puts out, quantitative measures do not tell the full story. 

Not all impact depends on a prince. Some research projects are not Sleeping Beauties at all. Ian Taylor, whose research was the focus of Experts in sports podcast, Episode 35, has seen steadily increasing interest in his work from some unusual places, including a book on feminist creativity.

So, in searching for the ever-elusive impact stories, keep a watchful eye out for princes or be your own prince. If the Sleeping Beauty analogy doesn’t work for you (or your research), drop it like a golden ball down a well. And if anyone has any information on the missing princes, please get in touch with rdm@lboro.ac.uk.  

The author is grateful for the assistance from David Campling in identifying stories with missing princes.

The views and opinions of this article are the author’s and do not reflect those of the University…although hopefully, they do reflect Loughborough University values. 

Endnotes:

[1] I use the word articles because that has traditionally been the only item of interest, but with the rise of Open Research practices, Sleeping Beauties can be any file related to research that is somehow discoverable.

Data management – from a section in the grant proposal to a day-to-day reference manual 

By Krzysztof Cipora, Lecturer in Mathematical Cognition, Open Research Lead of the School of Science, Centre for Mathematical Cognition, Loughborough University, k.cipora@lboro.ac.uk, @krzysztofcipora

Most funding agencies require grant proposals to contain a data management plan. It may seem an extra burden to prepare yet another document, as all applicants have been handling research data and know how to do it, so why mandate such a technicality in the proposal? At the same time, many researchers have not been formally trained in data management. Open Research practices becoming more and more widely adopted (and more and more often mandated by funders) include Open Data, that is sharing research data, either in the public domain or granting access to other researchers. No matter whether shared publicly or with some restrictions, the data need to be understandable and usable. This requires the data to be thoroughly curated, documented, and at best to go along with the programming code used for its processing and analysis. Researchers also benefit from good data curation and documentation if they come back to their own data after a few months or years. Data management is even more critical in large-scale projects including many researchers, research assistants etc. However, the document typically supplied to the funder is relatively short (space restrictions!) and therefore quite generic, so it cannot fully satisfy the day-to-day data management needs. 

In June 2022 at Loughborough University, we launched £ 9 989 000 Centre for Early Mathematics Learning (CEML; ceml.ac.uk) funded within ESRC Research Centre scheme. Funding covers a period of five years and over twenty-five researchers from several institutions are involved within five CEML challenges. They are supported by several research assistants and PhD students. Various types of data are being gathered. One of the crucial issues at the CEML onset was to ensure we are on the same page with data management. It has been necessary for several reasons both within CEML and for future data sharing. The same variables should be named and coded consistently across studies to streamline the readability of the data, facilitate the re-use of analysis code, and collapse datasets if needed. In case a researcher is reallocated from one study to another, they can catch up easily. Keeping our data curated and consistent for ourselves also makes it more accessible to other researchers when we share it with the community. 

Together with other colleagues, I took on preparing a detailed Data Management Policy for the CEML. In the following, I briefly describe what we did and how this might be used as an example for other projects (including much smaller ones). 

We started from the Data Management Policy from the CEML proposal and elaborated on the details (see CEML Data Management Policy https://doi.org/10.17028/rd.lboro.21820752). The document first outlines the responsibilities of Challenge Leads and Leads of specific studies being run (this is particularly important given the number of researchers involved in CEML). It specifies where the data are stored, who should have access to the data (working together with researchers from outside Loughborough University required some thinking of how to set this up efficiently), and when the data can be shared publicly. The document also specifies how to document the data entry process and how to document data analysis to ensure analytical reproducibility. We also specify the process of creating backups and data sharing. 

The Data Management Policy refers to Variable Dictionary (see CEML Variable Dictionary https://doi.org/10.17028/rd.lboro.21820824) – a document providing detailed information on how to name and organise data files and how to name variables. We also provide a template for the meta-data file to be created for each study (see CEML Variable Dictionary Template https://doi.org/10.17028/rd.lboro.21820947).  

To make these materials more accessible to CEML colleagues, we prepared a short video highlighting the most important aspects of the CEML data management and justifying why such detailed guidelines have been prepared (see CEML Data Management Training Video https://doi.org/10.17028/rd.lboro.21820713). 

All these look quite elaborate and may not seem very useful for smaller projects. However, at least some of these points may be worth considering. It is worth remembering that “there will be at least two people working with your data, you and future you”. Thus, ensuring a consistent way of naming data files, their structure, variable names, the analysis code, and documenting the progress of data processing is a big favour to future you and, most likely, other researchers who may work with your data. Hopefully, the CEML documents linked may serve as a useful template on how to prepare a day-to-day data management reference for other projects.

The views and opinions of this article are the author’s and do not reflect those of the University…although hopefully they do reflect Loughborough University values.

Open Research across disciplines

By Camilla Gilmore, Chair of Loughborough University’s Open Research Group and Professor of Mathematical Cognition

One of the challenges of institutional change around open research practices is the diversity of disciplines involved. Open research covers a range of activities that promote the openness, transparency, rigour, and reproducibility of research. These values are relevant to all disciplines, but the way these activities are applied and the (perceived) barriers to using them can look very different in different disciplines. 

The challenges of promoting open data provide a clear example of this. In behavioural sciences, where quantitative and qualitative research data comes from human participants, one of the major challenges is how to share data ethically and anonymously. In contrast, in STEM subjects, particularly where industrial partnerships are common, the challenges are around confidentiality, commercial sensitivity and IP protection instead. Consequently, promoting open data at an institutional level must be informed by these different concerns and challenges and provide appropriate disciplinary-specific training and support.

This was a problem that I became immediately aware of when I took over the role of chair of Loughborough’s Open Research Working Group (ORWG) in early 2020. As individual researchers, our perceptions of the “state of the art” of open research are informed by our own disciplinary experience. But to make institutional change, we need to ensure that the systems supporting open research and the opportunities and incentives we promote apply to researchers in all disciplines. I felt that I didn’t know enough about what open research looks like in other disciplines.

Fortunately, I was not alone in feeling like this. Professor Emily Farran (Academic Lead, Research Culture and Integrity, University of Surrey) had similar concerns, and so we decided that it would be beneficial to draw together examples of open research practices and resources across as wide a range of disciplines as possible. This project quickly became a substantial task and benefitted from many authors and contributors. The resulting document, Open Research: Examples of good practice, and resources across disciplines (osf.io/3r8hb) was initially launched in December 2020. The document is updated annually in response to suggestions and feedback from readers (if you think good practice in your discipline is missing, why not suggest it here?).

This work has now been incorporated into the UKRN (UK Reproducibility Network) webpages, where 28 separate disciplinary pages provide case studies, examples of open research practices and disciplinary-specific resources. These highlight that, while open research practices may look different in different disciplines, there is much to learn by looking beyond our own discipline and seeing commonalities in approaches.

At Loughborough, we are ensuring that our institutional activities are sensitive to disciplinary differences by creating Open Research Leads in each school who sit on the ORWG. But we are building on the commonality of challenges by working across schools to provide training and opportunities. Look out for more opportunities in the coming academic year.

The views and opinions of this article are the author’s and do not reflect those of the University…although hopefully they do reflect Loughborough University values.

A different kind of diversity

By Lara Skelly, Open Research Manager for Data and Methods

A few years ago, I submitted a methodological paper to a discipline-specific journal. The reviewers were not kind, one of them saying “There is no narrative of the findings.” Well naturally not, as the findings were the methodology I was describing. While entirely likely that I presented the purpose of the paper poorly, being a freshly minted PhD with limited publication experience, I remember the confusion I felt around the limited expectation of the reviewers.

Methodological papers are still a rarity, despite the slightly increased popularity that I saw during the COVID lockdowns. Most researchers that I encounter still see the typical paper of introduction-literature review-methods-results-discussion as the only format worth putting out into the world. And as is the case in any one-size-fits-all approach, much is lost by this homogeneity.

Research and the people who work in research are anything but homogenous. I have seen all manner of opinions of what counts for science, what data are, and ways of engaging with their craft. I’ve known researchers who are interested in the broad and the narrow, the individual and the collective, the future and the past. Boxing this variety into a homogenous communication is in this day-and-age, down-right daft.

We are in a wonderful age that strives to see diversity as a celebration. The time has come to celebrate the diversity in our research as well. To recognise that the typical paper format is perfectly fine, but researchers are not restricted to it. Sharing code, protocols, data, any of the ingredients of our research is one way that we can live our diversity, upholding a value that has become global.

Thanks to Katie Appleton and Gareth Cole for insightful comments on early drafts.

The views and opinions of this article are my own and do not reflect those of the University…although hopefully they do reflect Loughborough University values.

ARMA2015

Last week we attended the Association of Research Managers and Administrators‘ (ARMA) annual conference in Brighton. We were presenting on our Research Data Repository which was launched at the end of April.

Although our session part of the last panel of the conference it was still well attended with representatives from both universities and funders. As part of our talk we had decided to hold c30-45 minute breakout/discussion sessions. Not only were these sessions an opportunity for attendees to ask us additional questions about our repository but it was also an opportunity for us to discover the lay of the land at other institutions.

As someone with a research background but who has worked in libraries for the past 10 years it was interesting to hear some of the comments from the research managers and administrators. It is a view I have heard before but until the growth of open access and research data management at universities many research office staff were not aware that the ‘Library did research’.

One of the many advantages of the current “open landscape” at universities is that many departments that previously had limited or even no contact with each other (or contact only in very specific areas) e.g. Research Office, IT, Library, now have regular and meaningful contact across a number of areas. (For example, within a week of starting at Loughborough I had met colleagues from IT and the Research Office as part of my induction and work with them on a weekly (if not daily) basis.) Not only does this regular contact help to reduce any duplication of effort but it also means that staff working in those departments now have the opportunity to have a more holistic view of how research is conducted and supported at their organisation. As such, they are able to do their jobs with an understanding of how their decisions and work may affect others at the institution. Most importantly, it means that we are better placed to provide the support that researchers and academics may require.

This holistic view is particularly important at the moment when one considers the demands on academic staff in both research and teaching.

Updated ESRC policy on Research Data

The Economic and Social Research Council (ESRC) has recently released an updated version of its research data policy. This can be found at: http://www.esrc.ac.uk/about-esrc/information/data-policy.aspx (link to the PDF of the policy at the bottom of the page).

The ESRC policy now maps more clearly to the RCUK Common Principles on Data Policy. In addition, the updated ESRC policy explains in far greater detail than before the responsibilities of: ESRC grant applicants, ESRC grant holders, grant holders’ institutions, the ESRC itself, and ESRC data service providers.

If you are ESRC funded, based at Loughborough University, and wondering how this policy may affect you please do contact me (Gareth Cole – Research Data Manager) on g.j.cole(at)lboro.ac.uk.

 

Over 1,000 research data repositories available in re3data.org

In August 2012 re3data.org – the Registry of Research Data Repositories went online with 23 entries. Two years later the registry provides researchers, funding organisations, libraries and publishers with over 1,000 listed research data repositories from all over the world making it the largest and most comprehensive online catalog of research data repositories on the web. re3data.org provides detailed information about the research data repositories, and its distinctive icons help researchers easily identify relevant repositories for accessing and depositing data sets.

To more than 5,000 unique visitors per month re3data.org offers reliable orientation in the heterogeneous landscape of research data repositories. An average of 10 repositories are added to the registry every week. The latest indexed data infrastructure is the new CERN Open Data Portal: http://service.re3data.org/repository/r3d100011381

[Taken from a Re3data update in November 2014]

RDM case study

Dr Erika Whiteford has kindly written a research data management case study for the Lakes and the Artic Carbon cycle project. Erika’s case study highlights the value historic research data brings to our understanding of the future. It also illustrates the importance of managing research data and sharing it for possible future studies.

Erika’s case study is available via the university Library’s Research Support web pages.

RCUK Data Policies

Research Councils UK have devised Common Principles on Data Policy. This establishes their position on the management of research data produced by projects they fund, as well as taking steps to making data publically available.

Each Council has slightly different requirements in relation to proposals for funding and the research data arising from the projects they fund. The Digital Curation Centre have pulled together a useful summary table together with information on funders’ data policies. See their Overview of funders’ data policies web page for further details.

UK HEI RDM survey and the DCC

This post makes an interesting addition to earlier posts regarding our UK HEI Research Data Management survey and the benefits of being part of the JISCMRD programme.

We looked at the survey results and DCC engagement institutions to see whether there was any evidence to suggest that institutions with RDM services in place received DCC support.

An initial mapping of data from the survey against data on institutions receiving DCC support revealed similar numbers had a research data management policy. Thirty-eight percent (9 out of 15) receiving DCC support had a research data policy compared with 39% (15 out of 38) of all respondents. However, un-supported institutions, those not supported by the DCC s or not part of the JISCMRD programme were less likely to have a research data management policy (20% [3 out of 15]).

Research Data Policy

Research Data Policy

Similarly, 15% (2 out of 13) of those receiving DCC support had a research data service in place, but this proportion falls to 7% (1 out 15) for un-supported institutions.

Research Data Service

Research Data Service

Thus support, whether through funded projects, DCC support or a mixture of both has a significant impact in policy development. This applies even when such development is not a condition of funding; only MRD-funded projects had such a requirement.

It’s worth noting some overlaps between JISCMRD and DCC support. A few of the institutions in our survey had a bit of both. More generally DCC helped facilitate JISCMRD workshops and have a continuing brief to promote its lessons across other institutions.