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.

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. 

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!