Category Archives: Open Research at Cambridge Conference

Data Diversity Podcast #5 – Abdulwahab Alshallal

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Welcome back to another edition of the Data Diversity Podcast, the Research Data podcast from the University of Cambridge Office of Scholarly Communication (OSC). If this is your first time here, in this podcast, I speak to Cambridge Data Champions about their journeys in acquiring and working with data in their research, with the hope to highlight interesting facets of data work, but also academic research in general. In this episode, I spoke to Cambridge PhD student Abdulwahab Alshallal, from the MRC Epidemiology Unit, and who is part of the Physical Activity Epidemiology research group.  

Currently for his PhD, he is exploring associations of physical activity, behaviour and fitness with cardio metabolic risk in different global populations. Abdulwahab recently presented at a Data Champion Forum, where he talked about working with datasets from international sources, specifically from non-Western nations, and discussed the barriers to collaboration and differences in the flexibility of institutions regarding data access and sharing. In this episode, we discussed those matters and also went into his aspirations for public health policy making and how his data driven mindset applies to this endeavour. 

I am of the mind that your social and physical environments are a big determinant of your physical activity and your general lifestyle behaviours. For example, it is unfair to to compare the UK and India because it is much easier to cycle in streets and walk around in the UK than it is in India, or Mexico or even Kuwait, and the barriers can be different. It could be pedestrian access, it could be heat, in my case it would be humidity. All of these factors matter, and we need to get data to represent those populations and use that data in such studies. – Abdulwahab Alshallal

The overrepresentation of data from Western studies in global understandings of fitness 

LO: Is it true to say that most of the data that is available now is all based on Western data sources and is it problematic then to use that to represent a global understanding of fitness?

AA: I would rephrase that. It is not that the data does not exist, rather, it is that its representation in the literature is absent. The data exists but when it comes to the data making into the literature and influencing policy guidelines, this is not yet prevalent. Take for example physical activity guidelines: every few years, data from a lot of the literature of what is published is gathered and used to make new recommendations for physical activity. It is through these guidelines that it was recommended that people exercise, for example, 30 to 60 minutes of physical activity per day. Now, the guidelines say that it is 150 minutes of physical activity per week, no matter which day you do it. But the data that influences these policies are mostly data from North America, Europe, Australia (because these are the data used in the literature cited for the creation of these guidelines). This implies that we do not think that it matters much to look at data from other places, because humans are humans. But I am of the mind that your social and physical environments are a big determinant of your physical activity and your general lifestyle behaviours. For example, it is unfair to to compare the UK and India because it is much easier to cycle in streets and walk around in the UK than it is in India, or Mexico or even Kuwait and the barriers can be different. It could be pedestrian access, it could be heat, in my case, it would be humidity. All of these factors matter, and we need to get data to represent those populations and use that data in such studies. 

The data does exist and thankfully I have made an effort to do include it in my research. One of the places where you can acquire this data is from the World Health Organisation (WHO). That is the most wide-ranging data source, and then the few others that I’m using are from the South Asia Biobank, which covers four countries in South Asia: India, Sri Lanka, Pakistan and Bangladesh. Another source is the biobank from the UAE Healthy Future Study which would cover the Gulf populations, and the Qatar biobank.  

Data in his research 

LO: what are the research questions that you’re asking and what and and how is data used, or what data is needed to answer those questions? 

AA: I am interested in physical activity and asking are the associations of physical activity in the different ethnic populations different or the same? Does it matter where you live in the world? And we have made progress in this discovery. You would be the first to hear this actually but we have finished up our analysis for my first paper, and this is using the WHO data. We are close to submitting the manuscript. This is a bit of a segue but it is worth mentioning because it highlights one of the problems of the literature, but this paper touches on one of the controversies in my field. What the paper addresses is that all physical activity is good for you. For some context: there has been a recent phenomenon that we found in the current literature that uses mostly European data, that views occupational and non-occupational physical activity separately. They show that non-occupational physical activity is good for you, but occupational physical activity either has no effect or is actually bad for you in terms of mortality outcomes. What is alarming for us to instigate is to frame a paper that states that in low- and low-income countries outside of Europe, there is very little concept of non-occupational leisure time physical activity. Most of your activity is going to be in travel behavior or activity during your occupation, for example if you are doing heavy manual labor like construction and farming. So, we had to investigate that and I’m glad to report that, at least in terms of our findings, we found that occupational physical activity is not bad for you. Non-occupational physical activity is also good for you and it doesn’t matter what type of activity you do. We also were able to control the proportion accumulated in either occupational and non-occupational physical activity and based on what we found, any physical activity wherever you do it is good for you. 

We need to understand the physical activity in different parts of the world. The types of activity you’re going in one part of the world is going to be different to other parts of the world so one guideline is not going to be appropriate. We currently have one guideline from The WHO for the whole world which has 150 minutes of moderate to vigorous physical activity as the goal. Does that seem appropriate for the whole world? It might not be in terms of different countries or even different population subgroups such as young versus old or men versus women, or different occupations or different activity levels, and what really is the barrier between light, physical activity and moderate activity? It is going to be relative and likely complex. This is a shift of mindset that hopefully I will be able to contribute through my research. 

The experience of acquiring data for his research from global data banks

LO: What has your experience of acquiring data from different sources been? From what I understand, there are different barriers in place to getting the data. 

AA: Just to put it out there, I think it’s completely understandable that these barriers are in place. The data that these organisations produce is particularly high-quality, high-resolution data. Besides the WHO data, the studies from the biobank’s that I have mentioned plan on collecting data every few years from the same participants so the data really tells you about the health of the population because these cohorts are meant to be representative of the population. To put this data in the hands of researchers that you do not properly vet can be quite a risk, even if it means using anonymised data, so I completely understand the barriers. 

In terms of the the difficulty in which to get that data, it has been different. In regard to WHO data – and this is not my experience, but an experience of a researcher before me, a post doc that that worked on the same data set before me – a few years back she had to go all the way to Geneva and to perform the data analysis there because they did not have an online infrastructure in order to allow researchers from abroad to use the data. That has since changed and the way that I was able to request it is through the WHO microdata Repository.  

For the South Asia Biobank, after going through the data request, researchers are given a link to the data. The data request process itself is very comprehensive and can cause delays. It takes a lot of time, and there is a lot of emphasis on the protocol. They want to make sure that you have a proper protocol to say what you’re authorized to do. If you want to make small changes, even small changes, you have to rectify them before submitting the proposal and that can cause delays. In my case it took around six months and we just received the data, so we have not had a chance to use it. 

For the UAE healthy future study, it is actually a bit more secure than that. You do go through that process of the back and forth of going through the protocol. In terms of getting the data, from what I understand, you are using it locally. I know this from a researcher that I spoke to who works between Cambridge and the UAE. To work with the UAE healthy future study data, she’s given a laptop by the University (NYU Abu Dhabi), and she must be connected to a VPN. While she while connected to the VPN, she’s using a secure platform called NYU-Box. I believe NYU uses this platform in all of its institutions; Shanghai, Abu Dhabi. I have been told that it is very secure and you can use it offline as well.  

Regarding the Qatar Biobank, I don’t know much about the data security measures of Qatar Biobank. Through my experiences, I only know about trying to get that data. They are willing to work with foreign institutions, which is good, but the main PI of the project must be based in Qatar and the analysis must be conducted in Qatar. However, I think going through that effort and that process is very much worth it because it has one of the most comprehensive data sources in all of the Middle East that is available in recent times. It was established around 2014 and they have now up to 47,000 participants and counting. 30,000 of them are Qatar nationals and around 17,000 are foreign nationals who are long term residents. You have people from various populations which includes participants who are Indian, Egyptian, Lebanese. So, you can get to look at migrant workers, you get to look at other Arabs that are living in a specific environment, meaning that you can parse genetics out of social and physical environments. There is so much you can do and in addition to that, what makes it special, for my PhD at least, is that they have treadmill data. This is where they put people through a treadmill around treadmill test and they look at their heart rate response to exercise instead of just going through self-reported physical activity or through wearables. The Qatar biobank is the only study in that region that actually uses heart rate data so we can definitely estimate fitness in that population. For this reason, it is very much worth the effort of trying to push for it.

One thing I am grappling with at the moment is policy development, which is a bit of a departure from data. On one end, I’m gathering the evidence in order to understand the different populations of the world through physical activity to look at the different trends in fitness. Then, once we have the physical activity data, how do we know which resources to allocate to? Who should we target so fitness can tell us that in terms of policy? Who needs it the most might not necessarily be in the volume of activity. – Abdulwahab Alshallal

On the difference between self-reported fitness data and objective data

LO: Are self-reported fitness data less valuable than objective data obtained from wearables? 

AA: It is important to understand that for a long time, it was difficult to get objective data. If you spoke to a researcher from 30 or 40 years ago telling them about a cohort study that would be using wearables, they would not believe you and they wouldn’t think it would be scalable and they think it would be too expensive, and so self-reported data was the only resource that we had. Also, there are downsides to data from wearables. For example, there is going to be noise and glitches with data obtained from accelerometry. So, I wouldn’t say that self-reported data is useless.

I am a big critic of self-reported data and the dependence of the literature on self-reported data and my supervisor has made mellow about it by reminding me that it gives you context. One of the things that we haven’t been able to overcome with accelerometry is knowing what is actually happening. We can tell that they are being active, but what are they doing? When are they doing it? For example, in the questionnaires (that are used to generate self-reported data), we don’t ask people when they leave work or when they start work or commuting, we ask them to estimate their physical strain while doing those things in those specific contexts. This removes from the researcher the burden of trying to estimate what activity is happening. 

In terms of accuracy of the numbers and their influence on policy? That is a good question, and I think accelerometry would answer those questions. Using wearables and attaining objective data, in terms of specific numbers, is much more valuable. But policies in the past are not necessarily based on numbers, and self-reports have benefited us and there is still continued benefit. It is about data points which have a degree of relativity. There are people who are going to misreport because they don’t remember accurately how much activity they were doing, or they might be lying because they feel self-conscious or they want people to think that they are more active, or there might be a recall bias or a social desirability bias which could all lead to misclassifications. We asked for moderate and vigorous activity, but what is moderate to me and light to you? It’s different and relative. While there are accuracy problems in self-reported data, for the most part it tells us something that is relative to people. Take for example someone who reports 30 minutes of activity throughout the whole week versus someone who is reporting 200 or 300 minutes of physical activity per week. We could tell that the person who was reporting the more minutes of activity is more likely to be someone who’s more physically active. It’s going to be aligned more with a better blood profile than the person reporting less activity and so in terms of a relative sense, it is helpful. But having the resources that we have now and the ability to use wearable data, we should be making a transition towards that, but self-reported data still has value. I think they can compliment each other and provide context for the type of activity that you’re doing. 

On data and policy making

AA: One thing I am grappling with at the moment is policy development, which is a bit of a departure from data. On one end, I’m gathering the evidence in order to understand the different populations of the world through physical activity to look at the different trends in fitness. Then, once we have the physical activity data, how do we know which resources to allocate to? Who should we target so fitness can tell us that in terms of policy? Who needs it the most might not necessarily be in the volume of activity. For example, we may have some barriers to fitness such as environmental factors like heat and humidity, also infrastructure factors such as pedestrian access, green spaces, and how these are different in different parts of the world. But how can we use these data to influence policy development? This is something I’m starting to understand and trying to get a grip on. Soon, I will begin a policy internship so I will hopefully learn more about that. I’ve had some conversations with people in physical activity policy, and I’ve learned that in terms of what would actually influence policy, I should be looking for a shared problem and the shared solution. Take for example, cycling lanes. Say you want to create more cycling lanes, but then the government says they don’t have enough money for cycling lanes so they decide against it. But then, you also have a congestion problem and you want to achieve net zero, and you also have an obesity problem. You know what can fix that? Cycling lanes. More cycling lanes means more people are going to be actively commuting and less cars on the road, so there will be less carbon. Then, they will be interested to get on board. So it’s about framing it and that’s what I’ve realized, because framing it in terms of health is not going to take you very far. But in terms of money, or the overall goal, matching them up is going to be helpful. And it’s quite a departure from the way that I’ve been doing things which is being driven by data and what is good for health.

We thank Abdulwahab for speaking with us. We are certainly excited to see how he gets on with policy making. It would be comforting to know that there is a data driven thinker in the world of policy making, especially one that is aware of, and takes into consideration, the contextual, environmental and behavioural differences of people in different communities and parts of the world when integrating data into public health policy decisions

Data Diversity Podcast (#4) – Dr Stefania Merlo (2/2)

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We return with another post featuring our Data Diversity conversation with University of Cambridge Data Champion, archaeologist Dr Stefania Merlo from the McDonald Institute of Archaeological Research, the Remote Sensing Digital Data Coordinator and project manager of the Mapping Africa’s Endangered Archaeological Sites and Monuments (MAEASaM) project and coordinator of the Metsemegologolo project. This post is short in word count but not in importance, as it touches on two reflections on the challenges of data management as a researcher who works in a global context, two aspects of present-day academia that may be relevant to many readers. This edition follows on from the previous post where Stefania talks about the challenges of extending UK-based Open Data policies to non-UK communities that may not share the same enthusiasm for making their cultural heritage artefacts available Open Access.  

In this post, Stefania reflects on how she conducts herself as a European researcher working in the African continent where her intention may sometimes be misaligned with the local data co-creators. Stefania also shares the challenge of academic mobility, where migrating from one academic institution to another results in data that is left behind, provoking an uncomfortable thought: what would happen to your data when you are suddenly rendered uncontactable? 

One would like to think that this is a rare situation, but I suspect that the situation where somebody passes away unexpectedly or even not, or somebody retires and has not made a plan for what happens to an entire careers’ data set happens more often than we know. I think it is an individual’s responsibility to make plans, but I think support should be given by the institutions and people should be accompanied through this path. – Dr Stefania Merlo

Working in the African continent and being honest about the objectives of research 

Working in Africa and in African countries, gives somebody coming from a European background, and an Italian background like me, a particular set of challenges and opportunities, because you encounter a different set up with everything – with life, and with research. Living and working in this context in various African countries, allows a researcher coming from a different background to question and challenge themselves on how they do their work. Many things that are taken for granted in other settings cannot be taken for granted in that setting. In particular that relationship with the land, with nature, and with the past. Any archaeologist that works in this setting would tell you that there are certain things that you just know from very early on that you should do. For example, although we’re dealing with the past of archaeological landscapes, you don’t just go and do your work there without acknowledging that these landscapes come in spaces and areas occupied by people today, and that those people are the custodians of the land and of the archaeology today. So there needs to be a deep engagement with communities and with people even before you put your spade in the ground. And it takes time to build relationships of trust, and relationships that then allow you to do work on your own or together, depending on what the aim of your research is.

When I do work that fulfills certain academic goals that may not be of interest to the communities that I work with, I think it is better to be honest and tell them that I’m doing this piece of work because there is an archaeological question that probably only archaeologists are interested in, and this is the part of work that I’m doing. At the same time, I think it is also important then to acknowledge that you work in a setting that includes other people, and start thinking about what work you can do with the people that are custodians of or inhabit a particular part of the world. Then you start thinking, OK, there’s a different set of activities that I can do with people that people want to do with me and let’s do that. I think that it is important to have this honesty of saying that particular things are of interest to me and to my academic community that I would like to do, and then we can negotiate together. You have to engage with the community, and I think we should be a bit more honest and a bit more specific about what the expectations from both parties are, and from the setting, we’re coming and the setting we’re going to. 

There are certain academic activities that I’m expected to do that are of no interest whatsoever for the communities that I’m working with, such as the academic publications on which my career rests. Then, there are other things that the communities are interested in that will give me no weight whatsoever in my academic career but contribute to building a relationship with the local community. These give me so much fulfillment because I realise that I am doing research work that is useful not only for my academic community, but for other people, be it students, colleagues elsewhere in the world, or the building of policies around archaeological heritage. 

Global researcher, global data 

LO: As someone who has engaged in research all over the globe, how do you deal with data that is in various places around the world? 

SM: How do I deal with my data? – poorly. I may be a digital data champion, but it has been a difficult road, and it is still a difficult road, that of even managing and curating my own data. Just to give you an example, a lot of the data I’ve collected for the past 20 years is both in analog and digital format for the same project. I have some data with me here (in Cambridge) and I still have data backed up in hard drives that I haven’t opened in a long time. The majority of my analogue data sets, maps, drawings, diaries, I have left behind in South Africa when I moved here, and I haven’t been able to bring them with me. Some of my materials are in Italy with my family. Some of my diaries I had left back in Cambridge when I left to go to Botswana in 2006 and somehow got lost. So, it has been messy and I’m not proud of it. But I’m saying it because it is a problem with a lot of researchers that have become highly mobile and have migrated from one place to another, in some cases without sufficient funding to bring all of the paperwork with them. I have been a messy data collector, since my undergraduate and PhD days, and I’ve been trying to train myself to be better, I’m still not there yet, and in part it’s just me. But I think it has also to do with this very high mobility and having to change institutions in my career so many times. And what changed is not only the location, but the requirement of what you do with data where you put it, how you avail it to yourself and to others.

And so yes, I’m not very good at it but I’m trying very hard to find a way of now putting everything together because I do feel the responsibility that comes with collecting data in different countries. Some of it is actually information that was given to me from community members or friends, or colleagues that I work with and it’s with me. 
It’s their work, it’s with me and if anything ever happens to me – if I were to change institutions, or if anything were to happen to me, including losing my memory – let me put it like that – what’s going to happen? I’ve never really thought of what would happen if I were to move or to shift? I left my previous institution quite abruptly and during COVID, and I was able to take some materials out, but some other materials I didn’t get access to and they are still all over the place.  

And then I started thinking: I have never made a plan for this kind of situation to happen. So what am I going to do now in order to make sure that these data are usable and useful for me, but perhaps also to others when I’m not present as the curator that will be able to tell you what each data asset is. I’m not even talking about the creation of metadata. Most of my photographs, digital photographs, for example, have got metadata that have been ordered. But archaeological datasets are complex, fragmented and can be dispersed so the main challenge is how would you connect the photographs with the drawings within my diary? Of course, there are dates, but it’s going take so much time for somebody else to put all of it together, especially because half of it is in digital format and half of this is in analog format. That is going be a nightmare and may not even be doable. And so, I’ve become acutely aware of the fact that we never think of this situation. We rarely think about handing over data to others in a particular form that will allow others accessibility and ability to still reuse this complex interrelated data if they were to do so. 

Worst case (data) scenario

I have another example. One of my collaborators and mentors in South Africa passed away quite suddenly a couple of years ago. They had never made a plan for what would happen to their materials. They published prolifically, so we know a lot of the research that was done over 50 years, but I am aware that they had so much more material, both physical material and files in computers. Their physical collection was transferred from their house to the University by another colleague but, to the best of my knowledge, to date, no one has been able to get access to the digital data, stored in a password protected computer. One would like to think that this is a rare situation, but I suspect that the situation where somebody passes away unexpectedly or even not, or somebody retires and has not made a plan for what happens to an entire career’s data set happens more often than we know. I think it is an individual’s responsibility to make plans, but I think support should be given by the institutions and people should be accompanied through this path. In particular, perhaps academics from other generations that may not be so knowledgeable about how to deal with data management. In particular of digital data, but also of analog data. 

Once upon a time, archaeologists used to just put everything into a library or an archive so at least we have the analog records. But again, putting them together and having them make sense is extremely difficult if we don’t think of a framework for doing so. Another issue that I’ve mentioned before is mobility. You know, how do we assist researchers that have got high mobility to deal with this every time they move? I don’t have an exact formula, but when I changed institutions before, both the institution that I was leaving and the ones that were accepting me, I was never asked ‘do you need any financial or other kind of help to transfer your data?’ I was asked to fill in forms for transferring my goods, I was given money for my visa, but nobody ever asked about my academic research and the related data. 

We once again thank Stefania for taking the time to speak to us and giving us food for thought. Stefania raises, we believe, a very important question – are we taking for granted that we will always be at hand to ensure that the data that we produce will be understood? Researchers tend to wait until a project is completed before supplying their data with the information needed to make them understood and reusable. If there’s one thing that Stefania brings to mind, is that data FAIR-ness needs to be implemented from the onset of a project and then at every juncture of the project’s lifecycle, as the research unfolds. That way, the research data will be reusable in a self-contained manner. 

The Research Data Sustainability Workshop – November 2024

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The rapid advance of computing and data centres means there is an increasing amount of generated and stored research data worldwide, leading to an emerging awareness that this may have an impact on the environment. Wellcome have recently published their Environmental sustainability policy, which stipulates that any Wellcome funded research projects must be conducted in an environmentally sustainable way. Cancer Research UK have also updated their environmental sustainability in research policy and it is anticipated that more funders will begin to adopt similar policies in the near future. 

In November we held our first Research Data Sustainability Workshop in collaboration with Cambridge University Press & Assessment (CUP&A). The aim was to address some of the areas common to researchers with a focus on how research data can impact the environment. The workshop was attended by Cambridge Data Champions and other interested researchers at the University of Cambridge. This blog summarises some of the presentations and group activities that took place at the workshop to help us to better understand the impact that processing and storing data can have on the environment and identify what steps researchers could take in their day-to-day research to help minimise their impact.  

The Invisible Cost to Storing Data 

Our first speaker at the workshop was Dr Loïc Lannelongue, Research Associate at the University of Cambridge. Loïc leads on the Green Algorithms initiative which aims to promote more environmentally sustainable computational science and has developed an online calculator to check computational carbon footprint. Loïc suggested that the aim is not that we shouldn’t have data, as we all use computing, just that we should be more aware of the work we do and the impact it has on the environment so we can make informed choices. Loïc emphasised that computing is not free, even though it might look like that to the end user. There is an invisible cost to storing data, whilst the exact costs are largely unknown, the estimates calculated for data centres suggest that they emit around 126mt of CO2 e/year. Loïc furthered explained that there are many more aspects to the footprint than just greenhouse gas emissions such as water use, toxicity, land use, minerals, metals and human toxicity. For example, there is a huge amount of water consumption needed to cool data centres, and you often find that cheaper data centres tend to use larger amounts of water. 

Loïc continued to discuss how there are a wide range of carbon footprints in research with some datasets having a large footprint. The estimate for storing data is ~10kg CO2 per tb per year, although there are many varying factors that could affect this figure. Loïc pointed out that the bottom line is – don’t store useless data! He suggested we shouldn’t stop doing research, we just have to do it better. Incentivising and addressing sustainability in Data Management Plans from the outset of projects could help. Artificial Intelligence (AI) is predicted to help to combat the impact on the environment in the future, although as AI comes at a large environmental cost, whether any benefit will outweigh the impact is still unknown. Loic has written a paper on the Ten simple rules to make your computing more sustainable, and he recommends looking at the Green DiSC Certification which is a free, open-access roadmap for anyone working in research (dry lab) to learn how to be more sustainable.

The Shift to Digital Publishing 

Next to present was Andri Johnston, Digital Sustainability Lead at CUP&A. Andri discussed how her role was newly created to address the carbon footprint within the digital publishing environment at CUP&A. In publishing, there has been a shift from print to digital, but after publishing digitally, what can be done to make it more sustainable? CUP&A are committed to being carbon zero by 2048, aiming for a 72% reduction by 2030. As 43% of all their digital emissions for the wider technology sector come from digital products such as software, CUP&A have been looking at how they can create their digital products more sustainably. They have been investigating methods to calculate digital emissions by looking at their hardware and cloud hosting, which is mostly Amazon Web Services (AWS) but they use some Cambridge data centres. Andri explained how it has been hard to find information on AWS data centres emissions and knowing whether your users use a fixed line or cellular internet network connection (some cellular network towers use backup diesel generators which have a higher environmental impact) is hard to pinpoint. AWS doesn’t supply accurate information on the emissions of using their services and Andri is fully aware that they are using data to get data!

Andri introduced the DIMPACT project (digital impact), where they are using the DIMPACT tool to report and better understand the carbon emissions of platforms serving digital media products. Carbon emissions of the academic publishing websites at CUP&A have reduced in the last year as the team looked at where they can make improvements. At CUP&A, they want to publish more and allow more to access their content globally, but this needs to be done in a sustainable way to not increase the websites’ carbon emissions. The page weight of web pages is also something to consider; heavy web pages due to media such as videos can be difficult to download for people in areas with low bandwidth so this needs to be taken into account when designing them. The Sustainable web design guide for 2023 has been produced with Wholegrain Digital, and can be downloaded for free. Andri mentioned that in the future they need to be aware of the impact of AI as it is becoming a significant part of publishing and academia and will increase energy consumption. 

Andri concluded by summarising that in academic publishing, they will always be adding more content such as videos and articles for download. It is likely that researchers may need to report on the carbon impact of research in the future, but the question on how best to do this is still to be decided. The impact of downloaded papers is also a question that the industry is struggling with, for example how many of these papers are read and stored. 

Digital Preservation: Promising for the Environment and Scholarship  

Alicia Wise who is Executive Director at CLOCKSS gave us an overview of the infrastructure in place to preserve scholarship for the long-term. This is vital to be able to reliably refer to research from the past. Alicia explained that there is an awareness to consider sustainability during preservation. When print publishing was the main research output, preservation was largely taken care of by librarians, in a digital world this is now undertaken by digital archives such as CLOCKSS. The plan is to prepare to archive research for future generations 200-500 years from now!

CLOCKSS was founded in the 1990’s to solve the problem of digital preservation. There is a now a growing collection of digitally archived books, articles, data, software and code. CLOCKSS consists of 12 mirror repository sites located across the world, all of which contain the same copies. The 12 sites are in constant communication, using network self-healing to restore the original if a problem is detected. CLOCKSS currently store 57.5 million journal articles and 530,500 books.  

CLOCKSS are a dark archive, this means they don’t provide access unless it is needed, such as when a publisher goes out of business, or a repository goes down. If this happens, the lost material is made open access. CLOCKSS have been working with the DIMPACT project to map and calculate their carbon footprint. They have looked at the servers at all their 12 repository sites to estimate the environmental impact. It became clear that not all their sites are equal. The best was their site at Stanford University, where the majority of the CLOCKSS machines are located. Stanford has a high renewable energy profile, largely due to their climate and even have their own a solar power plant! They also have a renewable, recirculating, chilled underground water system for cooling the servers. The site at Indiana University was their worst performing as this is supplied by 70% coal. The estimated carbon emissions at the Indiana University site is estimated to be 9 tonnes of carbon per month (equivalent to a fleet of 20 petrol cars). 

Alicia explained that most of the carbon emissions come from the integrity checking (self-healing network). CLOCKSS mission is to reduce the emissions, and they are looking into whether reducing the number of repository sites to 6 copies could still predict preservation will be available in 500 years’ time. They are reviewing what they need to keep and informing publishers of their contribution so they can consider this impact.  

Alicia summarised by saying that it appears that digital preservation may have a lower carbon footprint than print preservation. CLOCKSS are working with the Digital Preservation Coalition to help other digital archives reduce their footprint too (with DIMPACT), they are finalising a general tool for calculation of emissions that can be used by other archives. They don’t want to discourage long-term preservation, as currently, 25% of academic journals are not preserved anywhere. This risks access to scholarship in the future. They want to encourage preservation, but in an environmentally friendly way. 

Preserving for the future at the University of Cambridge 

There are many factors that could impact data remaining accessible now and over time. Digital Preservation maintains the integrity of digital files and ensures ongoing access to content for as long as necessary. Caylin Smith, Head of Digital Preservation at Cambridge University Libraries, gave an overview of the CUL Digital Preservation Programme that is changing how the Libraries manages its digital collection materials to ensure they can be accessed for teaching, learning, and research. These include the University’s research outputs in a wide range of content types and formats; born-digital special collections, including archives; and digitised versions of print and physical collection items.  

Preserving and providing access to data, as well as using cloud services and storing multiple copies of files and metadata, all impact the environment.  Monitoring usage of cloud services and appraising the content are two ways of working towards more responsible Digital Preservation. Within the Programme, the team is delivering a Workbench, which is a web user interface for curatorial staff to undertake collection management activities, including appraising files and metadata deposited to archives.  This work will help confirm that any deposited files, whether these are removed from a storage carrier or securely uploaded, must be preserved long term. Curatorial staff will also be alerted to any potential duplicate files, export metadata for creating archival records, and create an audit trail of appraisal activities before the files are moved to the preservation workflow and storage.  

Within the University Library, where the Digital Preservation team is based, there may be additional carbon emissions from computers kept on overnight to run workflows and e-waste (some of the devices that become obsolete may still have a use for reading data from older carriers e.g. floppy disk drives). Caylin explained that CUL pays for the cloud services and storage used by the Digital Preservation infrastructure, which means you can scale up and scale down as needed. They are considering whether there is a need for an offline backup and weighing up if the benefit to having such a backup would outweigh costs and energy consumption.  

Caylin discussed what they and other researchers could do to reduce the impact on the environment: use tools available to estimate personal carbon footprint and associated costs of research; minimise access to data where necessary to minimise use of computing. Ideally data centres and cloud computing suppliers should have green credentials so researchers can make informed choices. There is a choice to make between using second hand equipment and repair equipment where possible. At Cambridge we have the Research Cold Store which is low energy as it uses tapes and robots to store dark data, but the question remains as to whether this is really more energy efficient in the long term.   

What could help reduce the impact of research data on the environment? 

The afternoon session at the workshop involved group work to discuss two extreme hypothetical mandated scenarios for research data preservation. It allowed the pros and cons of each scenario to be addressed, how this could impact sustainability and problems that could arise. We will use the information gathered in this group session to consider what is possible right now to help researchers at the University of Cambridge make informed choices for research data sustainability. Some of the suggestions that could reduce research data storage (and carbon footprint) include improving documentation and metadata of files, regularly appraising files as part of weekly tasks and making data open to prevent duplication of research. It could also be helpful to address environmental sustainability at the start of projects such as in a Data Management Plan.  

We have learned in this workshop, that research data can have an environmental impact and as computing capabilities expand, this impact is likely to increase in the future. There are now tools available to help estimate research carbon footprints. We also need stakeholders (e.g. publishers, funders) to work together to advocate that relevant companies provide transparent information so researchers can make informed choices on managing their research data more sustainably.