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Data Diversity Podcast #3 – Dr Nick H. Wise (1/4)

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In our third instalment of the Data Diversity Podcast, we are joined by Dr Nick H. Wise, Research Associate in Architectural Fluid Mechanics at the Department of Engineering, University of Cambridge. As is the theme of the podcast, we spoke to Nick about his experience as a researcher, but this is a special edition of the podcast. Besides being a scientist and an engineer, Nick has made his name as a scientific sleuth who, based on an article on the blog Retraction Watch which was written in 2022, is responsible for more than 850 retractions, leading Times Higher Education to dub him as a research fraudbuster. Since then, through his X account @Nickwizzo, he has continued his investigations, tracking cases of fraud and in some cases, naming and shaming the charlatans. Nick was kind to share with us many great insights over a 90-minute conversation, and as such we have decided to release a four part-series dedicated to the topic of research integrity. 

In this four-part series, we will learn from Nick about some of the shady activities that taint the scientific publishing industry today. In part one, we learn how Nick was introduced into the world of publication fraud and how that led him to investigate the industry behind it. Below are some excerpts from the conversation, which can be listened to in full here. 

I have found evidence of a papermill bribing some editors and there have been many, at least tens, if not hundreds, of editors that have been let go or told to stop being editors by journals in the last year because they have been found to be compromised. This could be because of bribery or some other way of being compromised. This is what I try to uncover. – Dr Nick H. Wise

Tortured Phrases and PubPeer: Nick’s beginnings as a Scientific Sleuth  

My background is in fluid dynamics where I mostly think about fluid dynamics within buildings. For instance, I think about the air flows generated by different heating systems and things like pollutant transport such as smells or COVID which can travel with the air and interact with other each other. That was my PhD and the post-doc in the Engineering department.

About three years ago whilst trying to avoid writing my thesis, I saw a tweet from the great Elizabeth Bik, who is possibly the most famous research fraud investigator. She mostly looks at biomedical images and her great skill is she would be able to look through a paper and see photos of Western blots of microscopy slides and see if parts of an image are identical to other parts, or if the image overlaps with images from different papers. She has an incredible memory and ability to spot these images. She’s been doing this for over 10 years and has caused many retractions. I was aware of her work but there was no way for me to assist with that because it is not my area of research. I don’t have an appreciation of what these images should look like.

But about three years ago she shared a preprint written by three computer scientists on her Twitter account about a phenomenon they called ‘tortured phrases’. In doing their research and reading the literature, these computer scientists noticed that there were papers with very weird language in them. What they surmised was that to overcome plagiarism checks by software like Turnitin, people would run text through paraphrasing software. These software were very crude in that they would go word by word. For instance, it would look at a word and replace it with the first synonym it found in a thesaurus. It would do this word for word, which makes the text barely readable. However, it is novel and so it will not flag any plagiarism checking software. Eventually, if you as a publisher have outsourced the plagiarism checks to some software, and neither your editor or peer reviewer reads the text to check if it makes sense, then this will get through peer review process without any problem and the paper would get published.  

For an example of tortured phrases: sometimes there’s not only one way to say something. Particularly if English is not someone’s first language, you don’t want to be too harsh on anyone who’s just chosen a word which just isn’t what a native speaker would pick. But there are some phrases where there’s only one right way to say it. For instance, artificial intelligence is the phrase for the phenomenon you want to talk about, and if instead you use “man-made consciousness”, that’s not the phrase you need to use, particularly if the original text said artificial intelligence brackets AI, and your text says “man-made consciousness” brackets AI. It’s going to be very clear what has happened.  

The three computer scientists highlighted this phenomenon of ‘tortured phrases’, but entirely from within the computer science field. I wondered if a similar phenomenon was happening in my own field in fluid dynamics. Samples of these paraphrasing software are freely available online as little widgets so I took some standard phrases from fluid dynamics, which were the kind that would not make sense if you swapped the words around and generated a few of these tortured phrases, I googled them and up popped hundreds of papers featuring these phrases. That was the beginning for me. 

I started reporting papers with these phrases on a website called PubPeer, which is a website for post-publication peer review. I commented on these papers and started being in conversation with the computer scientists who wrote the paper on ‘tortured phrases’ because they built a tool to scrape the literature and automatically tabulate these papers featuring these phrases. They basically had a dictionary of phrases which they knew would be spat out by the software because some of this paraphrasing software are so crude, such that if you put in “artificial intelligence”, you are always going to get out “man-made consciousness” or a handful of variants. It didn’t come up with a lot of different things. If you could just search for “man-made consciousness” and it brings up many papers, you knew what has been going on. I contributed a lot of new ‘fingerprints’, which is what they call their dictionary that they would search the literature for. That is my origin story. 

On Paper Mills and the Sale of Authorships 

There is also the issue of meta-science, which has nothing to do with the text of the paper or with the data itself, but more to do with how someone may add a load of references through the paper which are not relevant, or they are all references to one person or a colleague. In that way you would be gaming the system to boost profiles, careers, and things like H-index. Because having more publications and more citations is so desirable, there is a market for this. It is easy to find online advertisements for authorship of scientific papers ranging from $100 to over $1000, depending on the impact factor of the journal, and the position of authorship you want: first authorship, seventh authorship, or whether you want to be the corresponding author, these sorts of factors. Likewise, you can buy citations.  

There are also organizations known as paper mills. For example, as an author I might have written the paper and want, or need, to make some money and so I go to this broker and say: I want to sell authorships, I’ll be author number six, but I can sell the first five authorships. Can you put me in touch with someone selling authorships? At the same time, there are people who go to them saying I want to buy an authorship, and they put two and two together acting as a middleman. Also, some of these paper mills do not want to wait for someone to come to them with a paper – they will write papers to order. They have an in-house team of scientific writers who produce papers. This does not necessarily mean that the paper is bad. Depending on where they want the paper to publish, the paper might have to be good if it has to get published. So, they will employ people with degrees, qualified people or PhD students who need to earn some money, and then they will sell the authorships and get the papers published. This is a big business. 

There is a whole industry behind it, and something I have moved onto investigating quite a lot is where these papers are going. When I identify these papers, I try to find out where they are being published, how they’re being published, who is behind them, who is running these paper mills, who is collaborating with them. Something I found out which resulted in an article in Science was that paper mills want to guarantee acceptance as much as they can. If a paper is not accepted, it creates a lot of work for them and it means a longer time before their customers get what they paid for. For example, if a paper that they wrote and sold authorships for gets rejected, they’re going to have to resubmit it to another journal. So something paper mills will do is they will submit a paper to 10 journals at once and publish with whichever journal gave them the easiest time. But still, they want to try and guarantee acceptance and one way to do that is to simply bribe the editor. I have found evidence of a papermill bribing some editors and there have been many, at least tens, if not hundreds, of editors that have been let go or told to stop being editors by journals in the last year because they have been found to be compromised. This could be because of bribery or some other way of being compromised. This is what I try to uncover.

Although I’m not fighting this alone, it can feel like that. Publishers are doing things to some extent and they’re doing things that they can’t tell you about as well. And then there’s other people like me investigating this in their free time or as a side project. Not enough of us are doing it because it is a multi-million-dollar industry that is generating these papers. More papers are being published than ever before so it is a big fight.

Stay tuned as we release the rest of the conversation with Nick over the next month. In the next post, we get Nick’s take on the peer review process and fake research data, and I ask his opinion on where the fault lies in the publication of fraudulent research. 

Data Diversity Podcast #2 – Dr Alfredo Cortell-Nicolau

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In our second instalment of the Data Diversity Podcast, we are joined by archaeologist Dr Alfredo Cortell-Nicolau, a Senior Teaching Associate in Quantitative and Computational Methods in Archaeology and Biological Anthropology at the McDonald Institute for Archaeological Research and Data Champion.

As is the theme of the podcast, we spoke to Alfredo about his relationship with data and learned from his experiences as a researcher. The conversation also touched on the different interpersonal, and even diplomatic, skills that an archaeologist must possess to carry out their research, and how one’s relationship with individuals such as landowners and government agents might impact their access to data. Alfredo also sheds light on some of the considerations that archaeologists must go through when storing physical data and discussed some ways that artificial intelligence is impacting the field. Below are some excerpts from the conversation, which can be listened to in full here.

I see data in a twofold way. This implies that there are different ways to liaise with the data. When you’re talking about the actual arrowhead or the actual pot, then you would need to liaise with all the different regional and national laws regarding heritage and how they want you to treat the data because it’s going to be different for every country and even for every region. Then, of course, when you’re using all these morphometric information, all the CSV files, the way to liaise with the data becomes different. You have to think of data in this twofold way.

Dr Alfredo Cortell-Nicolau
Lutfi Othman (LO): What is data to you?

Alfredo Cortell-Nicolau (ACN): In archaeology in general, there are two ways to see the data. In my case for example, one way to see it is that the data is as the arrowhead and that’s the primary data. But then when I conduct my studies, I extract lots of morphometric measures and I produce a second level of data, which are CSV files with all of these measurements and different information about the arrowheads. So, what is the data? Is it the arrowhead or is it the file with information about the arrowhead? This raises some issues in terms of who owns the data and how you are going to treat the data because it’s not the same. In my case, I always share my data and make everything reproducible. But when I share my data, I’m sharing the data that I collected from the arrowheads. I’m not sharing the arrowheads because they are not mine to share.

This is kind of a second layer of thought when you’re working with Archaeology. When you’re studying, for example, pottery residues, then you’re sharing the information of the residues and not the pot that you used to obtain those residues. There are two levels of data. Which is the actual data itself? The data which can be reanalyzed in different ways by different people, or the data that you extracted only for your specific analysis? I see data in this twofold way. This implies that there are different ways to liaise with the data. When you’re talking about the actual arrowhead or the actual pot, then you would need to liaise with all the different regional and national laws regarding heritage and how they want you to treat the data because it’s going to be different for every country and even for every region. Then, of course, when you’re using all these morphometric information, all the CSV files, the way to liaise with the data becomes different. You have to think of data in this twofold way.

On some of the barriers to sharing of archaeological data

ACN: There are some issues in how you would acknowledge that the field archaeologist is the one who got the data. Say that you might have excavated a site in the 1970s and some other researcher comes later, and they may be doing many publications after that excavation, but you are not always giving the proper attribution to the field archaeologist because you cited the first excavation in the first publication, and you’re done. Sometimes, that makes field archaeologists reluctant to share the data because they don’t feel that their work is acknowledged enough. This is one issue which we need to try to solve. Take for example a huge radiocarbon database of 5000 dates: if I use that database, I will cite whoever produced that database, but I will not be citing everyone who actually contributed indirectly to that database. How do I include all of these citations? Maybe we can discuss something like meta-citations, but there must be some way in which everyone feels they are getting something out of sharing the data. Otherwise, there might be a reaction where they think “well, I just won’t share. There’s nothing in for me to share it so why should I share my data”, which would be understandable.

On dealing with local communities, archaeological site owners and government officials

ACN: When we have had to deal with private owners, local politicians and different heritage caretakers, not everyone feels the same way. Not everyone feels the same way about everything, and you do need a lot of diplomatic skills to navigate through this because to excavate the site you need all kinds of permits. You need the permit of the owner of the site, the municipality, the regional authorities, the museum where you’re going to store the material. You need all of these to work and you need the money, of course. Different levels of discussion with indigenous communities is another layer of complexity which you have to deal with. In some cases, like in the site where we’re excavating now, the owner is the sweetest person in the world, and we are so lucky to have him. I called him two days ago because we were going to go to the site, and I was just joking with him, saying I’ll try not to break anything in your cave, and he was like, “this is not my cave. This is heritage for everyone. This is not mine. This is for everyone to know and to share”. It is so nice to find people like that. That may happen also with some kinds of indigenous communities. The levels of politics and negotiation are probably different in every case.

On how archaeologists are perceived

LO: When you approach a field or people, how do they view the archaeologists and the work?

ACN: It really depends on the owner. The one that we’re working with now, he’s super happy because he didn’t know that he had archaeology in his cave. When we told him, he was happy because he’s able to bring something to the community and he wants his local community to be aware that there is something valuable in terms of heritage. This is one good example. But we have also had other examples, for instance, where the owner of the cave was a lawyer and the first thing he thought was “are there going to be legal problems for me? If something happens in the cave, who’s the legal responsibility.” In another case there was there was another person that just didn’t care, she said “you want to come? Fine. The field is there, just do whatever you want.” So, there are different sensibilities to this. Some people are really happy about the heritage and don’t see it as a nuisance that they have to deal with. 

LO: How about yourself as a researcher, archaeologist: do you see yourself as the custodian of sorts, or someone who’s trying to contribute to this or local heritage for the place? Or is it almost scientific and you’re there to dig.

ACN: When I approach the different owners, I think the most important thing is to let them know that they have something valuable to the local community and they can be a part of that. They can be a part of being valuable to the local community. Also, you must make it clear that it’s not going to be a nuisance for them and they don’t have to do anything. I think the most important part is letting them know how it can be valuable for the community. I usually like them to be involved, and they can come and see the cave and see what we are doing. In the end it’s their land and if they see that we are producing something that is valuable to the community then it is good for them. In this case, the type of data that we produce is the primary type of data, that is, the actual different pottery sherds, the different arrowheads, etcetera. In this current excavation, we got an arrowhead that is probably some 4- or 5000 years old and you get (the land owners) to touch this arrowhead that no one in 5000 years has seen. If you can get the owners to think of it in this way, that they’re doing something valuable for your community, then they will be happier to participate in this whole thing and to just let us do whatever we want to do, which is science.

LO: How do you store physical data? Or do you let the landowner store it?

ACN: That depends on the national and regional laws and different countries have different laws about this. The cave where I’m working right now is in Spain, so I’m going to talk about the Spanish law, which is the one that I that I follow and it’s going to be different depending on every country. In our case, with the different assemblages that you find, you have a period of up to 10 years where you can store them yourself in your university and that period is for you to do your research with them. After that period, it goes to whichever museum they are supposed to be going, which depends on the law that says that it has to be the museum that is the closest to the cave or site where they were excavated. Here, the objects can then be displayed and the museum is the ones responsible for managing them, and storing them long term.

There is one additional thing: If you are excavating a site that has already been excavated, then there is a principle of keeping the objects and assemblages together. For example, there is this cave that was excavated in the 1950s and they store all the assemblages in the Museum of Prehistory of Valencia, which was the only museum in the whole region. Now, they excavated it again a few years ago and now there are museums that are closer to the cave but because the bulk of the assemblages are in Valencia and they don’t want to have it separated in two museums, they still have to go to Valencia. This is the principle of not having the assemblages separated and it is the most important one.

As always, we learn so much by engaging with our researchers about their relationship with data, and we thank Alfredo for joining us for this conversation. Please let us know how you think the podcast is going and if there are any question relation to research data that you would like us to ask!

Thomas Roulet on sustainable publishing models

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Knowledge Rights 21 recently published a short video by Thomas Roulet, Professor of Organisational Sociology and Leadership at the Judge Business School at the University of Cambridge. In it, Prof. Roulet discusses the operations of M@n@gement, the no-fee open access journal published by L’Association Internationale de Management Stratégique (AIMS). The journal is a good example of the turn to community-led forms of open access publishing and how publishing can be organised by communities and sustained by professional associations.

This video is reproduced under a CC BY licence and with the permission of Prof. Roulet. The original video was shared on the Knowledge Rights 21 blog here: https://www.knowledgerights21.org/video/sustainable-publishing-models-thomas-roulet/

Thoth Archiving Network goes live at Cambridge 

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Dr Agustina Martínez-García, Head of Open Research Systems, Digital Initiatives

Cambridge University Library (CUL) is piloting participation in the Thoth Archiving Network, which allows small presses to use a simple deposit option to archive their publications in multiple repository locations, creating the opportunity to safeguard against the complete loss of their open books catalogue, should they cease to operate. 

Participation in the pilot has allowed us to explore the implementation of suitable infrastructure, built on interoperable, open, and widely adopted platforms to support discovery, access, and long-term availability of open scholarly works. 

Work done so far 

We are pleased to share that the Cambridge repository platform participating in the Thoth network is now live at https://thoth-arch.lib.cam.ac.uk/home, and now includes a full back catalogue of two open monograph publishers. This repository is based on the open-source DSpace software. 

Through the implementation phase, we have worked very closely with the Thoth technical team to support the implementation and testing of standard and automated deposit mechanisms into DSpace-based repositories. This work has allowed us to further our knowledge and expertise on scholarly and research platforms by using well adopted repository platforms (DSpace) in a new area: open access books and monographs. It has also provided us with the opportunity to test the implementation of additional infrastructure to support discovery, access, and dissemination of such open access content, and potentially experiment with other types of scholarly work. 

What’s next 

Now that the repository platform is live, we would like to gather insights about volume of content, required storage and staff resources (both infrastructure and user support). This will help us estimating associated costs for provision of such a service as well as preservation costs for the longer term, during the 3-year pilot.  

In terms of long-term preservation, we will explore several preservation options, including preserving the content in-house as part of the Libraries’ wider Digital Preservation Programme. The types of material hosted in this platform can provide an exemplary use case of scholarly content that is “preservation ready”, uses open and standard file formats (i.e., PDF and epub) and is accompanied by rich, high quality descriptive metadata. 

See this post by the Open Book Futures Team for more details about the pilot:  

https://copim.pubpub.org/pub/thoth-archiving-network-goes-live-at-university-of-cambridge/release/1

Formatting the Future: Why Researchers Should Consider File Formats

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Dr Kim Clugston, Research Data Coordinator, OSC
Dr Leontien Talboom, Technical Analyst, Digital Initiatives

Many funders and publishers now require data to be made openly available for reuse, supporting the open data movement and value for publicly funded research. But are all researchers aware of why they are being asked to share their data and how to do this appropriately? When researchers deposit their research data into Apollo (the University of Cambridge open access repository) they generally understand the benefits of sharing data and want to be a part of this. These researchers provide their data in open file formats accompanied by rich metadata so the data has the best chance of being discovered and reused most effectively. 

There are other researchers who deposit their data in a repository during the publication process; this often takes place within tight deadlines set by the publisher. For this reason, researchers often rush to upload their data, and thoughts about how this data will remain preserved and accessible for long-term use are not considered. The challenges around preserving open research data were highlighted in this article. The authors addressed the concerns that open research data can include a wide variety of different types of data files, some of which may only be accessible with proprietary software or software that is outdated or at risk of being outdated soon. How can we ensure that research data that is open now stays accessible and open for use for many years to come? 

In this blog, we will discuss the importance of making data open, ensuring this is maintained for future use (digital preservation). We will use some examples from datasets in Apollo and suggest recommendations for researchers that go beyond the normal FAIR principles to include considerations for the long term. 

Why is it important for the future?

The move to open data, following the FAIR principles, has the potential to boost knowledge, research, collaboration, transparency and decision making. In Apollo alone, there are now thousands of datasets which are available openly worldwide to be used for reference or reused as secondary data. Apollo, however, is just one of thousands of data repositories. It is easy to see how this vast amount of archived data comes with great responsibility for long term maintenance. A report outlined the pressing matter that FAIR data, whilst addressing metadata aspects well, doesn’t really address data preservation and the challenges that this brings such as the risk of software and/or hardware becoming obsolete, and therefore data reliant on these becoming inaccessible.

Tracking the reuse of datasets could provide essential information on how different file formats are holding up, but there is an ongoing challenge to track dataset reuse. Datasets are not yet routinely cited in the established way that is seen for journal articles or other publication types. This is an area that is actively being developed through initiatives such as Make Data Count and it is hoped that at some point soon, data citation will become part of the routine practice of research to further enhance visibility on how data is being credited and reused. 

In Apollo, we see great interest in the available datasets as they are viewed and downloaded frequently. The most downloaded dataset in Apollo has been downloaded over 300,000 times since it was first deposited in 2015 and, interestingly, consists of open file formats. Other highly downloaded datasets in Apollo, such as the CBR Leximetric dataset, have been used by lawyers and social scientists and successfully cited as a data source to answer new research questions. The Mammographic Image Analysis Society database was deposited in Apollo in 2015 and has been frequently downloaded and reused by researchers working in the field of medical image analysis as discussed in a previous blog. To date, Google Scholar reports it has been cited 78 times. These datasets show the value of sharing and reusing data and all are in file formats that are accessible to everyone which will help to preserve them for as long as possible. 

Digital preservation is a discipline focused on providing and maintaining long-term access to digital materials. Obsolete software is a big problem in maintaining access to files in the future. PRONOM, a file format registry, keeps track of a large amount of known file formats and provides additional information on these formats. Last year, a file format analysis of datasets in Apollo was conducted to highlight what file formats are represented in the repository. The results revealed the diverse array of different file formats which is a testament to the breadth of research conducted and the adoption of open data across many disciplines. Most of the file formats are common and can still be opened, but a large percentage of the material has not been identified or are in formats that are not immediately accessible without migrating to a different format or emulating the current file formats. Table 1 shows a few complex examples of file formats held in Apollo. 

File FormatExample in ApolloFuture Use
.dx (Spectroscopic Data Exchange Format)LinkThis is not an open-source format, meaning that opening the file is dependent on the software being available
.mnova (Mestrelab file format)LinkProprietary file format, licence for the programme is expensive
.pzfx (Prism file format)LinkOlder format for a file software program called Prism. This is now considered legacy software.

The Bit List, a list maintained by the Digital Preservation Coalition that includes contributions from members of the digital preservation community, outlines the “health” of different file formats and content types,  including research data. In fact, unpublished research data (which is another issue outside the scope of this blog!) is classified as critically endangered and uncovers the problem that the majority of researchers generally only make data open at the point of publication. But even research data published in repositories has its difficulties and is classified as vulnerable, mainly due to the dependency on many file formats having the availability of the appropriate software to open and use them. There are potential solutions on the horizon to address this problem, such as the open-source ReproZip which packages research data with the necessary files, libraries and environments so they can be run by anybody. However, this still doesn’t address the issue of obsolete software. The gold standard would be to deposit research data in open formats, so viewing and using the files is not dependent on a particular software; the files will be open and accessible as long as they are held available within a repository.  

What researchers can do

What can researchers do to make sure that when they deposit data into a repository, it will be available for them and others in 10 or even 20 years time? Awareness is the first step. Researchers should consider submitting their data to a repository, one that is suitable for their files. Choose a trusted data repository. A recent blog highlighted the potential problem of disappearing data repositories, with approximately 6% of repositories listed on the repository search registry, re3data being shut down (most reasons are unknown but some were listed as organisation or economic failure, obsolete software/hardware or external attacks). Approximately 47% of the repositories that had shut down did not provide an alternative solution to rescue the data and it is assumed that this data is lost. It may be that your funder or publisher decides the repository for you, but we have some guidance on what to look for in a trusted repository. If you are at Cambridge, you can deposit your data in Apollo which has CoreTrustSeal certification.

The data itself is arguably the most important factor, we need to make sure the data files can be found and used by anyone at any time, forever. Ideally, this means using open file formats where possible as these don’t have any restrictions. The Library of Congress and the UK National Archives both maintain registries of file formats. There is some Cambridge University guidance on choosing file formats as well as some by the UKDS. Have a look at the file formats you have on the PRONOM database, is this seen as a sustainable format? If the data you are generating is from proprietary software, it is good practice to deposit this version as well as an open format that does not require any specialist software to open them. This ensures that both options are available in case of any loss of formatting from converting to open formats. An example are the statistical software packages SPSS and NVivo which are proprietary but have the option to convert to open formats such as a CSV file. 

There may be information on how to convert your file types to open formats within your discipline. In the Chemistry department here at Cambridge, an initiative was started together with the Data Champion programme to provide a platform to allow researchers to add instructions for converting experimental derived files into open formats. Open Babel is an open-source, collaborative project aimed at providing a “chemistry toolbox” with information on how to convert chemical file formats into other formats where needed. There is also some guidance on how to export from R to open formats such as txt and csv.

In some cases, it might not be possible to provide an open file format alternative. The files you use may be subject to discipline-specific standards or you are restricted by the hardware and software you use in your research. For these, it is important to provide good documentation or a detailed README file alongside the file format so researchers know how to access and use your files. In fact good file organisation, documentation and metadata is just as important as the files themselves, as data without any documentation is considered virtually meaningless. The more information you can provide the better and might possibly save you time in the long run from potential questions from other researchers in the future. 

The future use of past research hinges on the thoughtful selection of file formats. By prioritising openness and longevity, we lay the foundation for collaboration and innovation. Choices that researchers make today shape the accessibility and integrity of data for generations to come.

The (exponential) thirst for data – The March 2024 Data Champions forum

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The Data Champions were treated to a big data themed session for the March Data Champion forum, hosted at (and sponsored by) the Cambridge University Press and Assessment in their amazing Triangle building. First up was Dr James Fergusson, course director for the MPhil in Data Intensive Science, who described how the exponential growth in data accumulation, computing and artificial intelligence (A.I.) capabilities has led to a paradigm shift in the world of cosmological theorisation and research, potentially changing with it scientific research as a whole.  

Dr James Fergusson presenting to the Data Champions at the March forum

As he explained, over the last two decades cosmologists have seen a rapid increase of data points on which to base their theorisation – from merely 14 data points in 2000 to 800 million data points in 2013! Through the availability of these data points, the paradigm for research in cosmology started to shift completely – from being theory based to being based on data.  With several projects beginning soon that will see vast amounts of data generated daily for decades to come, this trend is showing no signs of slowing down. The only way to cope with this exponential increase in data generation is with computing power, which has also been growing exponentially. In tandem with these sectors of growth is the growth of machine learning (ML) capabilities as the copious amount of data not only necessitates immense amounts of computing power but also ML capabilities to process and analyse all of the data. Together, these elements are fundamentally changing the story of scientific discovery. What was once a story of an individual researcher having an intellectual breakthrough is becoming the story of machine led, automated discovery. While it used to be the case that an idea, put through the rigour of the scientific method, would lead to the generation of data, now the reverse is not only possible but become increasingly likely. Data is now generated first before a theory is discovered, and the discovery may come from AI and not a scientist. This, for James, can be considered the new scientific method. 

Dr Anne Alexander has been familiarising herself with AI, especially in her capacity as Director of Learning at Cambridge Digital Humanities (CDH) where she has been incorporating critique of AI into a methodology of research in the digital humanities, particularly in the area of Critical Pedagogy. In her work, Anne addresses how structural inequalities can be reinforced, rather than challenged by AI systems. She demonstrated this through two projects that she was involved with at CDH. One was called Ghost Fictions, a series of workshops with the aim of encouraging critical thinking about automated text generation using AI methods both in scholarly work and in social life. The project resulted in a (free to download) book titled Ghost, Robots, Automatic Writing: an AI level study guide, which was intended as a provocation of a future where books, study guides and examinations are created by Large Language Models (LLM) (perhaps a not so distant future). Another project involved using AI to create characters for a new novel, which revealed the racial biases of ChatGPT when prompted with certain names. Yet, perhaps the most worrying aspect about the transformative forms of AI is the immediate and consequential impact it has on the environment. The computational power needed to quench the thirst for the exponential amounts of data needed to train and progress AI chat bots, LLMs and image generation systems, requires vast computing power which in turn generates a lot of heat and requires large amounts of water to operate. As Anne demonstrated, this could be increasingly problematic for many places as the global climate crisis continues. Locally, we have the case of West Cambridge, which is already water stressed, but also home to the University’s data centre and where the new DAWN AI supercomputer is located. Through these examples, she posed the questions: does AI perpetuate further harm and inequality? Are the environmental costs of AI too high?    

Dr James Fergusson and Dr Anne Alexander answering questions from the Data Champions at the March forum

The themes that Anne concluded her presentation with formed the basis of the Q&A between the Data Champions and the speakers. The topic of the potential biases of AI and ML was put forward to James who agreed that his field of study could not escape it. That said, unlike the humanities, biases in physics can potentially be helpful as it may help make the scientific process as objective as possible. However, this could clearly be problematic for humanities research, which tends to deal with social systems and relations, and views of the world. The topic of the environmental cost of AI was also touched on, with which James commented that energy insufficiency is a problem and getting harder to justify, and solutions might only create new problems as the demand for this technology is not slowing down. Anne expressed her concerned and suggests that society at large should be consulted on this as the environment is a social problem thus society should have a say on what risk they are willing to be a part of. The question of the automation of science was also raised to James who admitted that preparing early career physicists for research now involves developing their software skills rather than subject knowledge expertise in physics or mathematics. 

Dear Data,…

Uncategorized

Valentine’s day week for the international data community is not only a time for expressing your love to the significant others in your life. As it is also Love Data Week, it is also a time to reflect on your love for all things data! That was the goal for the Research Data team this year! The theme of this year’s Love Data Week was “My Kind of Data”, suggesting that data workers – researchers and analysts alike – have a relationship to data that is personal, often idiosyncratic, and almost always heartfelt. The Research Data team, as supporters of the University’s researchers, are interested in such relationships and are always eager to discover the distinctive needs that the disciplinary differences between the University’s departments create. This year, the Research Data team decided that they wanted to find out from students and researchers from the Arts, Humanities and Social Sciences (AHSS) what was their kind of data.

To do so, the Research Data team positioned themselves at the Foyer of the Alison Richard Building on the University’s Sidgwick Site, which is home to several AHSS departments, for two mornings on Monday the 12th and Thursday the 15th of February. Across the city, Data Champion Lizzie Sparrow was leading the charge with science, technology, engineering, mathematics (STEMM) students and researchers by holding her own pop-up at the West Hub. Like the Research Data team, and as a Research Support Librarian (Engineering) herself, Lizzie is also interested in the relationships that researchers have with data. Her approach, however, would likely be different. Unlike researchers in the STEMM subjects, the term data for AHSS students and researchers can sometimes feel exclusionary as they may not consider what they generate through research as data. From our perspective on the other hand, any material that goes on to form any part of their research is one’s data. To bring attention to this, the team tried to engage passers-by with the provocation “you have research data, change our minds!” The provocation was successful and many conversations were had on the different ways that members of the Sidgwick community understood data in their research.

The Research Data Team from the Office of Scholarly Communication (Cambridge University Library), from left to right: Clair Castle, Lutfi Othman, Kim Clugston.

The team was pleased to find that there was a general interest in the services of the Research Data team among the Sidgwick community, and we were happy to be able to share with others how we can help them with their data management and planning.

Some treats for those who stop by.
Our Open Research poster, designed by Clair Castle.

The team tried to capture the sentiments of the conversations had by asking the Sidgwick community to partake in 2 short activities as they departed our pop-up to better understand  their relationship with data (in exchange for Love Hearts sweets!). Firstly, we asked them to describe to us what data was to them, a question that we are extremely fond of asking! As usual, the answers were informative and they helped us to gain a sense of the varying data types that the Sidgwick community worked with – from political tracts and archival materials to balance sheets and land deeds from the early modern era.

Activity 1: Lots of different data types in the AHSS community!

For the second activity, we asked them what term best captured the materials that formed the basis of their scholarly work: data, research materials, or other? To our surprise, the majority of people we spoke to over both days saw themselves as working with data, more than double the number that saw themselves working with research materials, with a small number seeing themselves as working with both, interchangeably. This finding illustrated something that has been increasingly discussed in the Research Data team office: that finding alternatives to the term data may make our services and initiatives more appealing to members of the AHSS community. This is something we will take into account when targeting our outreach in the future. Yet, one thing is certain – our Research Data services are needed by the AHSS community just as much as it is by the STEMM community.

Activity 2: More generators of ‘data’ than we expected!

The pop-ups at the Alison Richard building were encouraging and it is hoped that fruitful relationships will transpire from these events. This is something that we may hold again soon. It was a good way to communicate our message and make others aware of the services of the Research Data team. Over at the West Hub Lizzie was not as encouraged, having only managed to have in depth chats with a couple of people. She reported that lots of people were very determinedly on their way somewhere and not up for stopping to talk. The time and/or location did not seem right for the intended audience. I suppose, we shouldn’t stand in between a student and their food. In any case, there were lots to take away from this Love Data Week pop-ups, and lots to reflect when we plan for our next pop-up, be it for Love Data Week 2025 or just as a periodic service to the research community here at Cambridge. Perhaps when the weather is nicer in the summer, we will do a pop-up outdoors in the middle of the Sidgwick site, or at research events throughout the University. If you have any ideas on where it would be good for us to hold such a pop-up, do let us know!

Mapping the world through data – The November 2023 Data Champion Forum 

Uncategorized,

The November Data Champion forum was a geography/geospatial data themed edition of the bi-monthly gathering, this time hosted by the Physiology department. As usual, the Data Champions in attendance were treated to two presentations. Up first was Martin Lucas-Smith from the Department of Geography who introduced the audience to the OpenStreetMap (OSM) project, a global community mapping project using crowdsourcing. Just as Wikipedia is for textual information, OSM results in a worldwide map created by everyday people who map the world themselves. The resulting maps can vary in terms of its focus such as the transport map, which is a map which shows public transport lanes like railways, buses and trams worldwide, and the humanitarian map, which is an initiative dedicated to humanitarian action through open mapping. Martin is personally involved in a project called CycleStreets which, as the name implies, uses open mapping of bicycle infrastructure. The Department of Geography uses OSM as a background for its Cambridge Air Photos websites. Projects like these, Martin highlighted, demonstrate how community gets generated around open data. 

CycleStreets: Martin at the November 2023 Data Champion Forum

In his presentation, Martin explained the mechanics of OSM such as its data structure, how the maps are edited, and how data can be used in systems like routing engines. Editing the maps and the decision-making processes that go behind how a path is represented visually on the map is the point where the OSM community comes to action. While the data in OSM consists primarily of geometric points (called ‘Nodes’) and lines (called ‘Ways’) coupled with tags which denotes metadata values, the norms about how to define this information can only come about by consensus from the OSM community. This is perhaps different to more formal database structures that might be employed within corporate efforts such as Google. Because of its widespread crowdsourced nature, OSM tends to be more detailed than other maps for less well-served communities such as people cycling or walking, and its metadata is richer, as they are created by people who are intimately familiar with the areas that they are mapping. A map by users for users. 

Next up was Dr Rachel Sippy, a Research Associate with the Department of Genetics who presented how geospatial data factored into epidemiological research. In her work, the questions of ‘who’, ‘when’, and ‘where’ a disease outbreak occurred are important, at it is the where that gives her research a geographical focus. Maps, however, are often not detailed enough to provide information about an outbreak of disease among a population or community as maps can only mark out the incident site, the place, whereas the spatial context of that place, which she denotes as space, is equally as important in understanding disease outbreaks.  

Of ‘Space’ and ‘Place’: Rachel at the November 2023 Data Champion forum

It can be difficult, however, to understand what a researcher is measuring and what types of data can be used to measure space and/or place. Spatial data, as Rachel pointed out, can be difficult to work with and the researcher has to decide if spatial data is a burden or fundamental to the understanding of a disease outbreak in a particular setting. Rachel discussed several aspects of spatial data which she has considered in her research such as visualisation techniques, data sources and methods of analysis. They all come with their own sets of challenges and researchers have to navigate them to decide how best to tell the fundamental story that answers the research question. This essentially comes down to an act of curation of spatial data, as Rachel pointed out, quoting Mark Monmoneir, that “not only is it easy to lie with maps, it’s essential”. In doing so, researchers working with spatial data would have to navigate the political and cultural hierarchies that are explicitly and implicitly inherent to places, and any ethical considerations relating to both the human and non-human (animal) inhabitants of those geographical locations. Ultimately, how data owners choose to model the spatial data will affect the analysis of the research, and with it, its utility for public health. 

After lunch, both Martin and Rachel sat together to hold a combined Q&A session and a discussion emerged around the topic of subjectivity. A question was raised to Rachel regarding mapping and subjectivity, as it was noticed that how she described place, which included socio-cultural meanings and personal preferences of the inhabitants of the place, can be considered to be subjective in manner. Rachel agreed and alluded back to her presentation, where she mentioned that these aspects of mapping can get fuzzy as researchers would have to deal with matters relating to identity, political affiliations and personal opinions, such as how safe an individual may feel in a particular place. Martin added that with the OSM project the data must be objective as possible, yet the maps themselves are subjective views of objective data.  

Rachel and Martin answering questions from the Data Champions at the November 2023 forum

Martin also brought to attention that maps are contested spaces because spaces can be political in nature. Rachel added that sometimes, maps do not appropriately represent the contested nature of her field sites, which she only learned through time on the field. In this way, context is very important for “real mapping”. As an example, Martin discussed his “UK collision data” map, created outside the University, which states where collisions have happened, giving the example of one of central Cambridge’s busiest streets, Mill Road: without contextual information such as what time these collisions occurred, what vehicles were involved, and the environmental conditions at the time of the accident, a collision map may not be that valuable. To this end, it was asked whether ethnographic research could provide useful data in the act of mapping and the speakers agreed. 

The Data Picture

Library and training matters, Uncategorized

I was recently named one of “the next generation of [library] leaders” as part of the CILIP 125, having been recognised as an individual who contributes energy and knowledge to improving and impacting their organisation. My area of expertise, and thus recognition, lies with the use of data within libraries. As a data analyst for the Office of Scholarly Communications at Cambridge University Library, my role focuses on empowering decisions with data driven understanding – such as supporting the Springer Nature negotiations. To develop my understanding of data, and its role within a wider organisation, further, I engage with data beyond the library – such as the Big Data London conference and the Carruthers and Jackson Data Leaders’ Summer School. Reflecting on the use of data in the wider world, what can be expected of the library and data?

The summer school provided practical advice, proven methodologies, and guidance that could apply across a variety of businesses. The course is designed to provide insight on the workflow of data officers, and their role within an organisation – no matter its stage of data maturity and literacy. Over the course of the ten weeks, leading experts discussed the role of a chief data officer (CDO), both as a business development opportunity, and as a career path for individuals. It explored the risk and governance of data within an organisation, and the final weeks focused strongly on the role of people and teams associated with data.

Peter Jackson and Caroline Carruthers addressed the differing types of CDO and described a pendulum between ‘risk aversion’ and ‘value added’. Understanding the balance between secure and proper data governance (GDPR for example) and providing value through data (such as setting up automation). The pendulum of risk to reward is relevant to many roles, including those within the library. Understanding the need to divide time and energy between creating policies and getting decision making results, is just as relevant to my role as a chief data officer. In my role I have supported decision making staff through data production, but equally, to instil a culture of data, time and energy must be dedicated to risk aversion, through tasks of researching data management, preparing training sessions for data storage, and supporting staff in data preparation.

Another important concept introduced was the DIKW pyramid – Data, Information, Knowledge, Wisdom – for understanding the value created from data. The base of the pyramid is (raw) Data, which can be processed into (useful) Information. This Information is data with meaning and a purpose and can be organised into (insightful) knowledge. Knowledge combines experiences, values, insights, and contextual information, which can then transcend to (integral) Wisdom. Wisdom is considered a deeper understanding with ethical implications and the ability to define ‘why’. The DIKW pyramid provided a frame of thought for presenting and approaching future data projects. Understanding the requirement to provide, data, information or knowledge, to better support a decision-making team.

To develop communication skills, expert Scott Taylor, known as The Data Whisperer, spoke about the three V’s for data storytelling: Vocabulary, Voice and Vision. Combining an accessible vocabulary, with a common voice will illuminate the business vision, and why that is important. This overarching concept for an organisations data approach can be scaled down to support individual data workers, to provide value – which should either grow, improve or protect the business case. Understanding how to communicate the data is a key skill as “Hardware comes and goes, software comes and goes, but data remains”. And that data that remains should be used to either grow, improve or protect the business, such that data gathered should be usable data!

At Big Data London, the organisation Women in Data hosted conversations about nurturing a culture of learning within data teams. Pulling from their experiences from minority backgrounds, the speakers highlighted the power in upskilling, sharing skills across teams and being an advocate on oneself and skills. As for what to upskill, data literacy was a hot topic across the conference. Data literacy, also called data fluency and data confidence, is the combination of ability, skills and confidence surround data and its uses. Data literacy enables more efficient work, and begs the question, what is the base level of data literacy / confidence across the library? Librarians use data daily; checking in/out material, answering students’ queries, or tracking the use of space, but are all librarians confident to use that data? This is an area I hope to explore further at the CUL, to ensure staff can use the data they have to support decisions.

Engaging with the world of data provides a big picture of the possibilities within the library. Conversations of AI (Artificial Intelligence), data policies and maturity, and shiny-new databases, software, and services, demonstrate the growing adoption of data, and therefore, libraries should follow suit. Actively taking snippets of larger conversations, developing ideas within the library space, and exploring the possibilities with data will help libraries thrive in this world of technological growth.

Should the UK make a deal with Springer Nature?

Uncategorized

This is a guest post by Prof. Stephen J. Eglen on the concurrent negotiations between the UK academic sector and the publisher Springer Nature. Prof. Eglen is a Fellow of Magdalene College and Professor of Computational Neuroscience in the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge. This post does not necessarily reflect the view of Cambridge University Libraries.

The UK academic sector is currently in discussion with Springer Nature around a renewed ‘read and publish’ deal for journal content. I understand that most institutions are likely to reject the current deal, but wish to continue negotiations. My position is that further discussions with Springer Nature are futile; we should stop accepting ‘transformative deals’. The likely effect of this deal would be that more of Springer Nature’s content may be openly available to read, but with the ‘paywall’ shifted to the publish side. Here I list my key objections:

  1. There is still no justification for the high APCs (9500 EUR + taxes) for Nature tier journals. Accepting a deal, regardless of the level of discounts that could be achieved, is implicitly accepting their business model. Springer Nature declined to engage with the Journal Comparison Service run by cOAlition S that aims to help understand how costs are determined.
  2. Springer Nature’s view is that ‘gold OA’ is the only viable way to open access. Other models for open access are available, and show promise, including diamond OA journals and Subscribe to Open. However, Springer Nature assert that “they haven’t found a way of making them financially sustainable”.  If we accept a gold-only view of open access,  how can we objectively assess the sustainability of alternative models?
  3. A move to a ‘gold only’ OA world would shift the barrier from reading to publishing content. Springer Nature recently announced a waiver policy for researchers from about 70 lower income countries. This still excludes many researchers worldwide e.g. from Brazil and South Africa, perpetuating neo-colonial attitudes towards the creation of scholarly content and reinforcing existing institutional inequalities within countries. Any waiver programme for APCs should be “no-questions-asked” regardless of where researchers are based. This would need to be properly costed and part of the justification of the APC (point 1).
  4. As of January 2023, several UK institutions have rights retention policies in place, with more expected to follow in the coming months. Individual researchers can also use rights retention strategy by themselves. Rights retention statements allow researchers to meet UK funder’s requirement by depositing their author-accepted manuscript without embargo. I believe Springer Nature should publicly state that they will allow any author worldwide to maintain their rights on their own author-accepted manuscripts.
  5. Over half of Springer Nature’s hybrid journals failed to meet their 2021 targets for open access articles within hybrid journals.  Those hybrid journals that fail again this year to meet their targets will be removed from cOAlition S’s transformative journal program.  Having some journals ineligible for cOAlition S funding but part of a UK read-and-publish deal would further complicate an already confusing system.  It would also question Springer Nature’s commitment to open access.

A detailed public critique of the deal is not possible because of the confidential nature of the negotiations.  Finances aside, I feel there was one element that was simply unworkable and unethical due to it requiring scholars to keep one aspect confidential if the deal were accepted.

The UK is one of only a few countries with a  heavy reliance on transformative agreements.  Sweden has already decided that transformative agreements are not sustainable and the transition period should finish at the end of 2024. Coalition S has also confirmed it will end its support of hybrid journals by the end of 2024. I would like to see the UK move away from transformative agreements. We could instead work internationally to promote more ethical and sustainable alternatives that put scholars at the heart of scholarly communication. In particular, the APC model has been tried, and introduces as many headaches as it has tried to solve. 

It is time instead to try new approaches.  There are several interesting models being developed by forward-looking organizations that the UK could endorse.  For example, MIT press recently launched shift+OPEN as a way to flip subscription based journals to diamond open access model.  Another interesting approach is Subscribe to Open where journals drop their paywall if a threshold amount of subscriptions are received.  Money saved on dealing with legacy publishers like Springer Nature is better spent investing in our own infrastructure and new approaches.