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.

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.