Navigating copyright in the Digital Age

Have you ever found a nice image on the great, wide web and decided to download and use it? Have you ever come across an array of Creative Commons licenses and their meaning was daunting or confusing? Hopefully the next few paragraphs will help you navigate copyright in the digital age.

So, what exactly is copyright? Copyright is defined as an exclusive economic right granted to the creator of original work to permit or prevent other people from using it. In plain language, copyright is a right given to a creator (human creator) to use the work created in any way shape or form they wish. They can sell it, bequeath it, or decide to give their copyright up and make it available for anyone to use without restriction. You might come across items that are licensed as Creative Commons Zero, those are free to be re-used without issues.

You can also find items that are in the public domain, not to be confused with publicly available. Public domain items are works, where copyright has come to an end, and they can now be used by the public without fear of copyright infringement. However, do be careful. Certain items can have trademarks attached to them, so they work differently.

How do you navigate this mishmash of reusable, free and all rights reserved works that you can find on the web? Well, there are some handy questions to ask yourself:

Be aware that anything that says “fair use” does not apply in the UK. In the UK we use the term “fair dealing”.

The ‘fair dealing’ principle in the UK, is much more restrictive than the US ‘fair use’ principle. In simple terms, the question to ask yourself when applying the ‘fair dealing’ principle is how would a fair-minded person use this material? The below infographic should help with ‘fair dealing’ use.

More information on ‘fair dealing’ can be found in the Fair Dealing: A quick guide on our repository.

Licenses are very useful when it comes to knowing what can or cannot be done with copyright materials. So here is a quick overview of the different licenses:

  • All Rights Reserved (ARR): The most restrictive license, granting the copyright holder exclusive control over all aspects of the work’s use.
  • Creative Commons (CC) Licenses: A family of open-content licenses that provide a flexible approach to copyright management. CC licenses offer different levels of permission, from non-commercial use to commercial exploitation with attribution.
  • Software licenses: Legal instruments governing the use and redistribution of software.

You can find more information on licenses in our Licenses section on the Copyright webpages.

Important to remember is the fact that materials found online have the same protection as physical materials, like books or paintings. Before you save and re-use, make sure you know what you can or cannot do with the material and most importantly of all, make sure to credit the author. If you still struggle with licensing and re-use of digital material, get in touch with Loughborough University’s Copyright and Licensing Manager.

AI and copyright

Post by Cristina Rusu, Copyright manager, Loughborough University

A humanoid robot pondering mathematical calculations on a blackboard
By Mike MacKenzie, CC-BY, via Flickr

As AI develops, an increasing number of news items are released regarding court cases of copyright infringement by ChatGPT, Stability AI and many, many more. Why is it that there are such issues regarding AI and copyright?

Copyright is an Intellectual Property (IP) right which grants the creator of a work the right to allow or prevent copying of said work. Although works are protected regardless of their artistic merit, the work does need to be created by a “natural person”. For example, software code is protected by copyright; what the code does is not.

Generative AI works, ChatGPT for example, because these algorithms have been fed an extensive amount of data. The outputs these AIs create are a combination of that data and the user’s input.  

AI is not limited to just written outputs; some AIs have been trained in creating the following media:

  • Image
  • Speech
  • Video
  • Music
  • Code.

So, what is the problem? In the beginning, companies have been open about where the data came from, and now they have become more and more secretive about it. While scrapping the internet and text and data mining (TDM) can be done for research purposes, under copyright exceptions, the access needs to be legal and the use non-commercial. Generative AI software is now mainly behind paywalls. It is also telling that something is not rosy, considering the number of court cases happening in the UK, EU and US. You can read more about some of the lawsuits below:

Artists Are Suing Artificial Intelligence Companies and the Lawsuit Could Upend Legal Precedents Around Art by Shanti Escalante-De Mattei

3 Lawsuits in 10 Days: Who Is Suing OpenAI, and Why? By Allison Burt

AI learned from their work. Now they want compensation. By Gerrit De Vynch

Authors file a lawsuit against OpenAI for unlawfully ‘ingesting’ their books by Ella Creamer

Let’s consider that the inputs (the data that the Generative AIs have been fed) are under copyright, and the use has potentially been unlawful. It also means that the outputs are plagiarized at the least and copyright infringement at worst.

However, there are other issues to be considered when using Generative AI. According to UNESCO’s quick start guide on ChatGPT, has highlighted the following issues:

Issues 
Academic integrityPlagiarism and cheating
Lack of regulationSecurity issues
Privacy concernsNo age-regulation
Cognitive biasBiased ideas and perpetuates bias
Gender and diversityStereotyping and discrimination
AccessibilityLack of access in certain countries
CommercializationExtracting data for commercial purposes
Table 1 Issues with using ChatGPT, UNESCO, 2023, p.11  

Alex Fenlon, Head of Copyright and Licensing in Library Services at the University of Birmingham, has also highlighted other risks associated with using Generative AIs.

Aleksandr Tiulkanov, AI and Data Policy Lawyer, created a useful flowchart to help assess when ChatGPT is safe. You could ask yourself: Does it matter if the outputs are true? Do you have the knowledge to verify the accuracy of the output? Are you willing and able to take full responsibility (legal, moral, etc.) for missed inaccuracies? If you answered yes to some or all of these questions, then you are free to use ChatGPT; if you answered no, you may want to re-think your use of the GenAI.

According to UNESCO’s ChatGPT quick guide, there are possible uses of ChatGPT in the research process:

It could be used in:

  1. Research Design: generate ideas for research questions or projects; suggest data sources.
  2. Data collection: search archives and datasets; translate sources into other languages.
  3. Data analysis: code data; suggest themes or topics for analysis.
  4. Writing up: improve writing quality; reformat citations and references; translate writing.

One point to make here is that everything that is inputted within these AIs will be used as training data. Make sure you own the data you input and are happy for it to be re-used to train the AIs. Always read the terms and conditions. If in doubt, get in touch with your copyright officer or library.

Disclaimer: The information presented here does not reflect the views of Loughborough University.

Further reading

Guadamuz, Andres, A Scanner Darkly: Copyright Liability and Exceptions in Artificial Intelligence Inputs and Outputs (February 26, 2023). Available at SSRN: https://ssrn.com/abstract=4371204 or http://dx.doi.org/10.2139/ssrn.4371204

Lee, Jyh-An, Computer-generated Works under the CDPA 1988 (November 5, 2021). Artificial Intelligence and Intellectual Property (Jyh-An Lee, Reto Hilty & Kung-Chung Liu eds, Oxford University Press, 2021) , The Chinese University of Hong Kong Faculty of Law Research Paper No. 2021-65, Available at SSRN: https://ssrn.com/abstract=3956911

Guadamuz, Andres, Do Androids Dream of Electric Copyright? Comparative Analysis of Originality in Artificial Intelligence Generated Works (June 5, 2020). Intellectual Property Quarterly, 2017 (2), Available at SSRN: https://ssrn.com/abstract=2981304

Yes, you can open commercially funded research (but probably not all of it)

Image description: Two LEGO figures, in white shirts and blue trousers, discussing a model of a LEGO shark. Image created with Bing’s AI Image Creator: https://www.bing.com/images/create/

“Mommy, how much do you think the Jaws LEGO set will cost?” asked my seven-year-old the other night as I was putting him to bed. His dad had told him earlier that day that the LEGO Review Board had officially announced that a build design, submitted by a LEGO fan, based on the 1974 novel by Peter Benchley, which was the source of the 1975 Steven Spielberg movie, was going to be in production. As my son is an ardent enthusiast of all things with big teeth, a LEGO Jaws set was the best news since he discovered that he could build a mosasaurus.

When companies like LEGO, IKEA, Unilever and NASA crowdsource design, innovations and problem-solving, it is termed open innovation. It is one example where a commercial venture works in synergy with open research practices. At Loughborough University, our researchers have worked with companies like Rolls Royce, Jaguar, Airbus, and Adidas. While some of the research outputs are embargoed due to commercial restrictions, there are parts of the research that can and is made openly available.

Negotiations of what can be made openly available should take place before the contract is signed. If you are a researcher who is working with commercial funding, be sure to check if your methods, data collection tools, and data (perhaps in an aggregated format) can be shared and under what conditions. In the discussions I’ve had, I have found commercial funders willing to work with researchers in opening as much of the research as is sensibly possible.

And thank goodness they are because, without open innovation, I wouldn’t be in the running for the best Christmas present award from my seven-year-old.

Tensions of Open Research in Creative Arts and Design fields

By Dr. Tincuta Heinzel, Senior Lecturer in Textiles and Open Research Lead, School of Design and Creative Arts

Mashup of vials and a blue swirly pattern
Image credit: Lara Skelly, CC-BY

Starting with the 1st of April 2022, all submitted for publication research that a public body has funded must comply with the Open Access policy. This rule applies to all UKRI research councils, Research England, and Innovate UK-funded projects. Open Research and Open Data compliance means that the researchers must make their research publications Open Access, make their research data as open as possible, follow good research data management practices, and acknowledge their funder in any outputs. (for more details, please check here). Still, many particulars are to be addressed regarding Open Science and research, like, for example, the right to privacy when it comes to Open Data or the way each discipline will implement this policy.

Given the previous research publication models, this new policy implies a paradigmatic change that aims to facilitate everyone’s access to the research results and enable them to re-use and build upon them. The Open Access Policy builds on ideas popularised by movements such as Free Software (Free Software Foundation) launched in 1983 or Open Source Software Initiative, both aiming to offer alternatives to commercial computer operating systems to facilitate experimentation and innovation in the digital arena. Both movements adhere to philosophies that place free access to the source code and collaboration at their core. As their manifestos state (here and here), it is about the freedom to use, study, distribute, create, and modify any operating system, with the difference that the free software focuses on the users’ freedom, while Open-Source software is focusing on collaboration and transparency of the source code to provide improvements to the operating systems; which translates in the fact that not all Open-Source software is free software, for example. The same principles also apply to free hardware, which refers to the freedom to build, modify, and distribute hardware designs. Arduino and Raspberry Pi boards are good examples in this sense. The educative role of most of these projects is at the core of all these cases.

The application of the Open Research and Open Science policy in creative arts and design has nothing of the obvious. At the crossroad between science and technologies, between humanities and natural sciences, the place of research in creative arts and design is a minefield. Concepts such as “tacit knowledge” (Polanyi, 1958) often address the complexity of research in creative arts and design, expressing the limits of translating certain aspects of the practice into generally accepted forms of research. The nature of the outputs makes things even less straightforward. An exhibition is already an open, public presentation of an artist’s work, but does it count as research? What exactly is research in creative arts and design? What is the role of design theory and design practice in design research? How to find harmony between “research for”, “research into”, and “research through” design (Savic et al., 2014; Zimmerman et al., 2010), for example, with Open Science and Open Data policy?

Moreover, not all artistic and design research results in texts; in many cases, it is about products, objects, swatch books, processes, and methodologies. In some cases, it is about industrious initiatives and not merely educational purposes. The research in creative arts and design might reflect and use different media, such as images, sound compositions, video recordings and films, codes, or, as in the case of interactive arts and design, it might be about all of them.

Let’s take a closer look at the case of textiles and textiles patterns. In general, when it comes to textile designs and patterns, these are defined as designs (see the difference between artistic copyright, designs, and trademarks). As an e-textiles designer, I came across situations where the status of Open Publication and Open Research has been challenged.

The Open Software movement inspired designers such as Hannah Perner-Wilson (aka plusea.at) to develop a series of textiles-based sensors and to release them into the public domain. Her “tilt sensor” developed during her master studies at MIT (Perner-Wilson, 2011) has been appropriated by a group of scientists (Hyung Sun Lee, Daejeon (KR); Hyung Cheol Shin, Daejeon (KR); Thad E. Starner, Atlanta, GA (US); Scott M. Gilliland, Atlanta, GA (US) and Clint Zeagler, Atlanta, GA (US)) from the Electronics and Telecommunications Research Institute, Daejeon, Korea and, respectively Georgia Tech Research Corporation, Atlanta, USA, and patented based on the argument that her work would be an artistic product and not scientific research. Still, it is to question how legitim such a patent is when it doesn’t recognise the scientific merit of an author and boycotts the designer’s ideological choices (Heinzel, 2018).

The same ambiguity can be seen when it comes to the cultural appropriation of traditional textiles’ patterns. Plenty of cases show the appropriation of the work of “collective authors” has been used for the financial gain of some brands. It is the case of the legal action of the Indigenous Mexican Community against Isabel Marant, who used their patterns for her collection, or the Maasai Association for Preserving and Celebrating Maasai Cultural Heritage legal action against companies like Louis Vuitton, Calvin Klein, or Jaguar Land Rover, who were using the image of Maasai warriors to sell their products (Pilling, 2018). In the same category could be included the media campaign “Bihor, not Dior” (Davies, 2018). Still, when it comes to woven structures, for example, we can easily argue that we deal with a certain form of ethnomathematics (logical structures that await to be discovered) and not really designs.

In some cases, the designs are about the notations of the steps to produce the pattern and not about the patterns themselves. This logic of notation approach brings us closer to the aspects related to programming and digital rights. We can notice a series of ambiguities when defining and applying a pattern’s legal status and a series of breaches into the legal system(s) (Heinzel, 2018).

Suppose there is justified to request that the public-funded research be publicly released. In that case, aspects still need to be pondered as they interfere with the existing legal, economic, or ethical orders. Moreover, as the cases of cultural appropriation are proving, there is also an aspect of legitimacy that should be considered. Certainly, there is still work to be done to address these issues.

Below are a series of useful links related to Open Research compliance guidance and links for information related to designs, patents, or trademarks.

Useful links:

Works cited:

Davies, K. M. (2018). Bihor, not Dior: check out the new campaign reclaiming Romanian folk style, The Calvert Journal, URL:  https://www.calvertjournal.com/articles/show/10465/bihor-not-dior-watch-the-new-campaign-reclaiming-romanian-folk-style. (Retrieved on line on 29th of April 2023)

Heinzel, T. (2018). Patented Patterns: On the art and science of patterns. A critical inquiry, Proceedings of the Politics of the Machines – Art and After (EVA Copenhagen) Conference, May 2018, DOI: 10.14236/ewic/EVAC18.8.   

The Open Source Definition (2007), URL: https://opensource.org/osd/. (Retrieved 1st of May 2023.)

Pilling, D. (2018). Warrior tribe enlists lawyers in battle for Maasai “brand”, in The Financial Times, URL:

Perner-Wilson, H. et.al. (2011). Handcrafting Textile Interfaces from A Kit-of-No-Parts, TEI’11 Conference Proceedings, Funchal, Portugal, p. 61-68, DOI: 10.1145/1935701.1935715.

https://www.ft.com/content/999ad344-fcff-11e7-9b32-d7d59aace167 . (Retrieved the 15th of June 2018).

Polanyi, M. (1958). Personal Knowledge: Towards a Post-Critical Philosophy. Chicago: University of Chicago Press. ISBN 0-226-67288-3.

Savic, S., Huang, J. (2014). Research Through Design: What Does it Mean for a Design Artifact to be Developed in the Scientific Context?, Proceedings of the 5th STS Italia Conference : A Matter of Design. Making Society through Science and Technology, Milan, Italy, DOI: 10.13140/RG.2.1.4306.6729.

US Patent 9316481 (2016). Sensor for measuring tilt angle based on electronic textile and method thereof. URL: https://patents.justia.com/patent/9316481.  (Retrieved the 15th of June 2018).

Zimmerman, J.; Stolterman, E.; Forlizzi, J. (2010). An Analysis and Critique of Research through Design: Towards a Formalisation of a Research Approach; ACM: New York, NY, USA, 2010; pp. 310–319.

What is Free Software? (2001), URL: https://www.gnu.org/philosophy/free-sw.html. (Retrieved 1st of May 2023.)

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.

AHRC Technical Plans – training event

On Wednesday 23rd  September I will be leading a training session on “Writing a Successful Technical Plan for the AHRC”. Prof. Richard Bibb, an AHRC Technical Plan reviewer, will also be in attendance to give a reviewer’s perspective. The session will be held in the Stewart Mason Building (room SMB .02) between 1200 and 1300. Lunch will be provided for attendees. Please book through the Online Store so we have an idea of numbers.

If you are currently working on an AHRC application or think that you may do so in the future please do come along and find out what to include in your Technical Plan. We will be working through a couple of examples of existing plans so that you can see what a successful plan looks like.

For further information please contact Kate Clift in the Research Office, Gareth Cole in the Library or see our poster for the AHRC Technical Plan session.

“Projects” functionality in the data repository

Loughborough’s data repository has recently been upgraded with additional functionality. You can still deposit data as an individual (please contact rdm@lboro.ac.uk for more information or if you wish to deposit data) but you can now also set up “Projects”.

Currently limited to Loughborough University members, Projects allows you to set up a collaborative space where data can be shared and checked amongst a research group. How Projects is used is up to you and your group.

If you think that this functionality would be useful for your research group or research project please do get in contact. Data associated with Projects can be kept private or published in the same manner as data on your individual accounts.

Each Project will have an initial storage allocation of 10GBs although this could be increased on application to the Research Data Manager on rdm@lboro.ac.uk.