Tag Archives: Open Research

Data Diversity Podcast #2 – Dr Alfredo Cortell-Nicolau

Research Data, Uncategorized, , ,

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!

Open Research for Inclusion – event round up

Humanities, Open Research at Cambridge Conference, Publishing, Supporting Open Research

Dr Mandy Wigdorowitz, Open Research Community Manager, Cambridge University Libraries

On Friday 17 November 2023, participants from across Cambridge and beyond gathered for a hybrid meeting on Open Research from different perspectives. Hosted by Cambridge University Libraries at Downing College, ‘Open Research for Inclusion: Spotlighting Different Voices in Open Research at Cambridge‘ drew attention to different areas of Open Research that have been at the forefront of recent discussions in Cambridge by showcasing the scope and breadth of open practices in typically under-represented disciplines and contexts. These included the Arts, Humanities, and Social Sciences, the GLAM sector (Galleries, Libraries, Archives, and Museums), and research from and about the Global South. A total of 84 in-person and 75 online attendees participated in the day-long event consisting of a keynote address, two talks, two panels, and a workshop.

The conference opened with a welcome address from Professor Anne Ferguson-Smith CBE FRS FMedSci, Pro-Vice-Chancellor for Research and International Partnerships and the Arthur Balfour Professor of Genetics. Professor Ferguson-Smith emphasised the significance and timeliness of the conference and how it underscores the importance of the Open Research movement. She encouraged attendees to be open to new ideas, approaches, and perspectives that center around Open Research and to celebrate the richness of diversity in research.

Our keynote speaker, Dr Siddharth Soni, Isaac Newton Trust Fellow at Cambridge Digital Humanities and affiliated lecturer at the Faculty of English, then addressed the audience with a talk on Common Ground, Common Duty: Open Humanities and the Global South, providing an account of how to think against neoliberal conceptions of ‘open’ and to reimagine what openness might look like if the Global South was viewed as a common ground space for building an open and international university culture. Dr Soni’s address set the tone for a rich, multi-layered exploration of Open Research on the day, urging attendees to think of open humanities as a form of knowledge that seeks to alter the form and content of knowledge systems rather than just opening Euro-American knowledge systems to global publics.

Dr Siddharth Soni Common Ground, Common Duty: Open Humanities and the Global South

The next talk was from Dr Stefania Merlo from the McDonald Institute for Archaeological Research and Dr Rebecca Roberts from the McDonald Institute for Archaeological Research and Fitzwilliam Museum who further explored the theme of the Global South in their practical perspective on how they managed the curation of digital archives for heritage management from their work on the projects: Mapping Africa’s Endangered Archaeological Sites and Monuments (MAEASaM) and Mapping Archaeological Heritage in South Asia (MAHSA). They reflected on the opportunities and challenges relating to the production and dissemination of information about archaeological sites and monuments in projects across Africa and South Asia as well as their experience working with and learning from local communities.

Dr Stefania Merlo and Dr Rebecca Roberts Open Data for Open Research – Reflections on the Curation of Digital Archives for Heritage Management in the Global South

An Open Research panel session was next which featured panellists with diverse backgrounds and expertise who addressed registrants’ pre-submitted and live questions. Some questions included the meaning of Open Research, its advantages and challenges, how Open Research can be engaged with by researchers (and in particular, early career researchers), and how it can be rewarded and embedded into the culture of research practices. There was engaging insights and debate amongst the panellists, led by Bertrand Russell Professor of Philosophy, Professor Alexander Bird. He shared the platform with Philosophy of Science Professor, Professor Anna Alexandrova, Psychiatry PhD student Luisa Fassi, Cambridge University Libraries (CUL) Interim Head of Open Research Services Dr Sacha Jones, Cambridge University Press & Assessment’s Research Data Manager Dr Kiera McNeice, and Cambridge’s Head of Research Culture Liz Simmonds.

Open Research Panel

Following lunch, a second panel of scholars working across the GLAM sector (Galleries, Libraries, Archives and Museums) took place. The panel was chaired by CUL’s Scholarly Communication Specialist, Dr Samuel Moore, and brought together experts who showcased their diverse work in this sector, from software development and museum practices to infrastructure and archiving support. The panel included Dr Mary Chester-Kadwell, CUL’s Senior Software Developer and Lead Research Software Engineer at Cambridge Digital Humanities, Isaac Newton Trust Research Associate in Conservation Dr Ayesha Fuentes from the Museum of Archaeology and Anthropology, Dr Agustina Martinez-Garcia, CUL’s Head of Open Research Systems, and Dr Amelie Roper, CUL’s Head of Research. Each panellist presented on a specialist area, including Open Research code and data practices in digital humanities, collections research, teaching and learning collections care, and Open Research infrastructure. A lively discussion followed from the presentations.

GLAM panel

In a workshop session, Tim Fellows, Product Manager for Octopus, outlined how Octopus is a free and alternative publishing model that can practically foster Open Research. The platform, funded by UKRI, is designed for researchers to share ‘micro publications’ that more closely represent how research is conducted at each stage of a project. In a demonstration of the platform, Tim Fellows showed how Octopus works, it’s design, user interface, and application all with the aim of aiding reproducibility, facilitating new ways of sharing research, and removing barriers to both publishing and accessing research. An in-depth discussion followed which centered on the ways the platform can be used as well as its uptake and application across various disciplines.

Tim Fellows Octopus.ac: Alternative Publishing Model to Foster Open Research

The final talk of the day was on Open Research and the coloniality of knowledge presented by Professor Joanna Page, Director of CRASSH and Professor of Latin American Studies. She discussed the topic with a specific focus on the questions of possession and access by outlining projects by three Latin American artists who have engaged with Humboldt’s legacy and the coloniality of knowledge. Using videos and imagery, Professor Page encouraged the audience to consider how they might identify where the principles of Open Research conflict with those of inclusion and cognitive justice, and what might be done to reconcile those ambitions across diverse cultures and communities. An engaging discussion ensued.

Professor Joanna Page Open Research and the Coloniality of Knowledge

A drinks reception brought the event to a close, allowing attendees a chance to mingle, network and continue the discussions. 

Special thanks to all speakers, attendees, and volunteers for making this event such a success. Stay tuned for information about our 2024 Open Research conference.

Data Diversity Podcast #1 – Danny van der Haven

Research Data, , ,

Last week, the Research Data Team at the Office of Scholarly Communication recorded the inaugural Data Diversity Podcast with Data Champion Danny van der Haven from the Department of Material Science and Metallurgy.

As is the theme of the podcast, we spoke to Danny about his relationship with data and learned from his experiences as a researcher. The conversation also touched on the differences between lab research and working with human participants, his views on objectivity in scientific research, and how unexpected findings can shed light on datasets that were previously insignificant. We also learn about Danny’s current PhD research studying the properties of pharmaceutical powders to enhance the production of medication tablets.   

Click here to listen to the full conversation.

If you have heart rate data, you do not want to get a different diagnosis if you go to a different doctor. Ideally, you would get the same diagnosis with every doctor, so the operator or the doctor should not matter, but only the data should matter.
– Danny van der Haven

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What is data to you?  

Danny: I think I’m going to go for a very general description. I think that you have data as soon as you record something in any way. If it’s a computer signal or if it’s something written down in your lab notebook, I think that is already data. So, it can be useless data, it can be useful data, it can be personal data, it can be sensitive data, it can be data that’s not sensitive, but I would consider any recording of any kind already data. The experimental protocol that you’re trying to draft? I think that’s already data.   

If you’re measuring something, I don’t think it’s necessarily data when you’re measuring it. I think it becomes data only when it is recorded. That’s how I would look at it. Because that’s when you have to start thinking about the typical things that you need to consider when dealing with regular data, sensitive data or proprietary data etc.   

When you’re talking about sensitive data, I would say that any data or information of which the public disclosure or dissemination may be undesirable for any given reason. That’s really when I start to draw the distinction between data and sensitive data. That’s more my personal view on it, but there’s also definitely a legal or regulatory view. Looking for example at the ECG, the electrocardiogram, you can take the electrical signal from one of the 12 stickers on a person’s body. I think there is practically nobody that’s going to call that single electrical signal personal data or health data, and most doctors wouldn’t bat an eye.   

But if you would take, for example, the heart rate per minute that follows from the full ECG, then it becomes not only personal data but also becomes health data, because then it starts to say something about your physiological state, your biology, your body. So there’s a transition here that is not very obvious. Because I would say that heart rate is obviously health data and the electrical signal from one single sticker is quite obviously not health data. But where is the change? Because what if I have the electrical signal from all 12 stickers? Then I can calculate the heart rate from the signal of all the 12 stickers. In this case, I would start labelling this as health data already. But even then, before it becomes health data, you also need to know where the stickers are on the body.   

So when is it health data? I would say that somebody with decent technical knowledge, if they know where the stickers are, can already compute the heart rate. So then it becomes health data, even if it’s even if it’s not on the surface. A similar point is when metadata becomes real data. For example, your computer always saves that date and time you modified files. But sometimes, if you have sensitive systems or you have people making appointments, even such simple metadata can actually become sensitive data.   

On working within the constraints of GDPR  

Danny: We struggled with that because with our startup Ares Analytics, we also ran into the issues with GDPR. In the Netherlands at the time, GDPR was interpreted really stringently by the Dutch government. Data was not anonymous if you could, in any way, no matter how difficult, retrace the data to the person. Some people are not seeing these possibilities, but just to take it really far: if I would be a hacker with infinite resources, I could say I’m going to hack into the dataset and see the moments that the data that were recorded. And then I can hack into the calendar of everybody whose GPS signal was at the hospital on this day, and then I can probably find out who at that time was taking the test… I mean is that reasonable? Is anybody ever going do that? If you put those limitations on data because that is a very, very remote possibility; is that fair or are you going hinder research too much? I understand the cautionary principle in this case, but it ends up being a struggle for us in in that sense.  

Lutfi: Conceivably, data will lose its value. If you really go to the full extent on how to anonymise something, then you will be dataless really because the only true way to anonymise and to protect the individual is to delete the data.  

Danny: You can’t. You’re legally not allowed to because you need to know what data was recorded with certain participants. Because if some accident happens to this person five years later, and you had a trial with this person, you need to know if your study had something to do with that accident. This is obvious when you you’re testing drugs. So in that sense, the hospital must have a non-anonymised copy, they must. But if they have a non-anonymized copy and I have an anonymised copy… If you overlay your data sets, you can trace back the identity. So, this is of course where you end up with a with a deadlock.  

What is your relationship to data?  

Danny: I see my relationship to data more as a role that I play with respect to the data, and I have many roles that I cycle through. I’m the data generator in the lab. Then at some point, I’m the data processor when I’m working on it, and then I am the data manager when I’m storing it and when I’m trying to make my datasets Open Access. To me, that varies, and it seems more like a functional role. All my research depends on the data.  

Lutfi: Does the data itself start to be more or less humanised along the way, or do you always see it as you’re working on someone, a living, breathing human being, or does that only happen toward the end of that spectrum?   

Danny: Well, I think I’m very have the stereotypical scientist mindset in that way. To me, when I’m working on it, in the moment, I guess it’s just numbers to me. When I am working on the data and it eventually turns into personal and health data, then I also become the data safe guarder or protector. And I definitely do feel that responsibility, but I am also trying to avoid bias. I try not to make a personal connection with the data in any sense. When dealing with people and human data, data can be very noisy. To control tests properly, you would like to be double blind. You would like not to know who did a certain test, you would like not to know the answer beforehand, more or less, as in who’s more fit or less fit. But sometimes you’re the same person as the person who collected the data, and you actually cannot avoid knowing that. But there are ways that you can trick yourself to avoid that. For example, you can label the data in certain clever way and you make sure that the labelling is only something that you see afterwards.   

Even in very dry physical lab data, for example microscopy of my powders, the person recording it can introduce a significant bias because of how they tap the microscopy slide when there’s powder on it. Now, suddenly, I’m making an image of two particles that are touching instead of two separate particles. I think it’s also kind of my duty, that when I do research, to make the data, how I acquire it, and how it’s processed to be as independent of the user as possible. Because otherwise user variation is going to overlap with my results and that’s not something I want, because I want to look at the science itself, not who did the science. 

Lutfi: In a sentence, in terms of the sort of accuracy needed for your research, the more dehumanised the data is, the more accurate the data so to speak.   

Danny: I don’t like the phrasing of the word “dehumanised”. I guess I would say that maybe we should be talking about not having person-specific or operator-specific data. If you have heart rate data, you do not want to get a different diagnosis if you go to a different doctor. Ideally, you would get the same diagnosis with every doctor, so the operator or the doctor should not matter, but only the data should matter. 

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If you would like to be a guest on the Data Diversity Podcast and have some interesting data related stories to share, please get in touch with us at info@data.cam.ac.uk and state your interest. We look forward to hearing from you!