All posts by Lutfi Bin Othman

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!

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,…

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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!