Professor Petar Jandrić 'Viral Modernity: Covid-19 and the promise of open science'
From Nelly Iacobescu
According to the World Health Organisation (2020), “the current outbreak of coronavirus disease (COVID-19) (…) was first reported from Wuhan, China, on 31 December 2019”. 30 days later, on 31 January 2020, UK’s Wellcome Trust issued a statement entitled ‘Sharing research data and findings relevant to the novel coronavirus (COVID-19) outbreak’. Initially signed by 67 large organisations such as the European Commission and mainstream academic publishers such as Elsevier and Springer Nature, the statement resulted with unprecedented level of global research collaboration. At the moment of writing this abstract, and only 60 days after the outbreak of the epidemic, this research collaboration has already returned some fascinating results – virus genome has been mapped, reliable tests have been developed, and the first trial of the vaccine has started (Park 2020).
Such success of open science has resulted in some bombastic predictions about its future. “When the story of the coronavirus (2019-nCOV) is finally written, it might well become a template for the utopian dream of open science — where research data is shared freely, unrestrained by competition, paywalls and patents.” (Crowe 2020) There is no doubt that such developments would not be possible without the principles of open science – free sharing of datasets and research results, quick review and publishing procedures, and, above all, decommodification of all Covid-19 related research. Only two months after the outbreak of the epidemic, however, the principles of open science have already bumped into some natural limitations including but not limited to questionable verifiability of (some) published results to data deluge (Peters, Jandrić and McLaren 2020).
This presentation uses the case of the coronavirus (2019-nCOV) to explore viral modernity as a concept that is based upon the nature of viruses, the ancient and critical role they play in evolution and culture, and the basic application to understanding the role and forms of bioinformation in the social world. While the exact flow and dynamic of the collective response to Covid-19 will surely be analysed long after the epidemic is gone, the presentation exposes some major challenges it has introduced to the scientific community since the outbreak of the epidemic.
Petar Jandrić is Professor at the Zagreb University of Applied Sciences, Croatia. His previous academic affiliations include Croatian Academic and Research Network, National e-Science Centre at the University of Edinburgh, Glasgow School of Art, and Cass School of Education at the University of East London. Petar’s background is in physics, education and information science, his research interests are situated at the post-disciplinary intersections between technologies, pedagogies and the society, and research methodologies of his choice are inter-, trans-, and anti-disciplinarity. His recent books include Education and Technological Unemployment (2019), Mobility, Data, and Learner Agency in Networked Learning (2020), and Postdigital Dialogues on Critical Pedagogy, Liberation Theology and Information Technology (2020). Petar is Editor-in-Chief of Postdigital Science and Education journal https://www.springer.com/journal/42438 and book series https://www.springer.com/series/16439. Personal website: http://petarjandric.com/.
World Health Organisation (2020). Coronavirus disease (COVID-19) outbreak. https://www.who.int/emergencies/diseases/novel-coronavirus-2019. Accessed 28 February 2020.
Wellcome Trust (2020). Press Release: Sharing research data and findings relevant to the novel coronavirus (COVID-19) outbreak. 31 January. https://wellcome.ac.uk/press-release/sharing-research-data-and-findings-relevant-novel-coronavirus-covid-19-outbreak. Accessed 28 February 2020.
Park, A. (2020). COVID-19 Vaccine Shipped, and Drug Trials Start. Time, 25 February. https://time.com/5790545/first-covid-19-vaccine/. Accessed 28 February 2020.
Crowe, K. (2020). 'We're opening everything': Scientists share coronavirus data in unprecedented way to contain, treat disease. CBC News, 1 February. https://www.cbc.ca/news/health/coronavirus-2019-ncov-science-virus-genome-who-research-collaboration-1.5446948. Accessed 28 February 2020.
Peters, M.A., Jandrić, P., & McLaren, P. (forthcoming 2020). Viral Modernity: Covid-19 and the promise of open science. Educational Philosophy and Theory.
TITLE SLIDE: I gave this presentation on Friday, 22nd May 2020, at the Centre for Research in Digital Education, Moray House School of Education, University of Edinburgh. Due to technical difficulties the presentation was not recorded, and I did this re-run on next Monday. While this re-run will surely miss some excitement of talking to a large audience, I do hope it will be of use.
SLIDE 2: I am a professor of education at Zagreb University of Applied Sciences in Croatia, and a visiting professor of education and the University of Wolverhampton in the UK.
I have been an associate and visiting scholar at Edinburgh’s Centre for Research in Digital Education for more than a decade, yet this is my first online seminar for the centre.
SLIDE 3: Early this year I started following news
reports about the coronavirus. I had just returned from a visiting
professorship in Beijing; unlike many of people in the western world, I took my
Chinese friends very seriously. Nevertheless, the virus seemed so far… Soon
after, the virus came to Europe. I truly felt for my friends from Spain and
Italy, who reported unimaginable horror stories about their friends and relatives
suffocating in packed hospitals while waiting for someone’s death to get their
ventilator. Yet the virus still seemed so far… First cases of Covid-19 were
reported from Slovenia, and a doctor died in a village less than hour’s drive
from my home. But Slovenia and Croatia have not been the same country for more
than 30 years: the virus still seemed so far… Finally, the virus arrived to my
hometown Zagreb, Croatia, and like the most of the world, on 13 March 2020
Croatian government introduced harsh lockdown measures against the rising
pandemic of the coronavirus.
SLIDE 4: While the whole population was confined to their homes, at 6:24 am on the Sunday morning of 22 March 2020, Croatia’s capital Zagreb (population ca 1 million) was hit by a 5.5 Richter earthquake. Within seconds, my partner and I ran from our flat at the third floor of a 100-year old Austro-Hungarian building and found ourselves in the street. Barefoot and in our pyjamas, we found ourselves talking to neighbours known and unknown, while more than 30 aftershocks shook the city for the rest of the day. Less than five minutes after the first shock it began to snow, and we all chuckled at a bitter viral Facebook message saying: ‘And now we’re waiting for locusts’.
In the midst of unprecedented lockdown measures, Zagreb was hit by the strongest earthquake in 140 years—and its citizens were equally unprepared for both. To add insult to injury, recommended responses to these disasters are directly opposed—the virus is avoided by staying at home, while (consequences of) the earthquake are avoided by going out. Faced with the invisible threat of the virus and the visible threat of being buried alive, no-one has returned to their flats. Someone made a quick beer run to the nearby gas station, and we had a nice little corona-party at the ruins of our beloved city. Few days later, doctors and patients had another nice little corona-party in their emergency rooms… But who could blame terrified people for risking a possibility to contract the virus in the face of failing walls and ceilings?
SLIDE 5: The world has united against the coronavirus. People have exhibited remarkable solidarity. People were singing from their windows and balconies, praising essential workers such as doctors, nurses, and shopkeepers. After the earthquake, Zagreb received a lot of love and support from all parts of the world. In the world of research, ‘the Covid-19 pandemic has initiated historically unprecedented levels of collaboration and openness.’
SLIDE 6: In February, Michael Peters emailed Peter McLaren and me with an idea to co-author an article on the pandemic. At that point, Michael was coming from the future – and I was living in the past. As the three of us slowly developed the first paper about viral modernity (Peters, Jandrić and McLaren 2020), and then the second paper
SLIDE 7: about a viral theory of post-truth (Peters, McLaren and Jandrić 2020), my theoretical interest has started to develop.
SLIDE 8: So I sat down and wrote an urgent editorial for Postdigital Science and Education which concluded:
I invite all postdigital scholars to take this voice seriously, get out of our comfort zones, and explore all imaginable aspects of this large social experiment that the Covid-19 pandemic has lain down in front of us.
SLIDE 9: Then I issued several calls: for 500-word testimonies, for shorter commentary articles, for full-length original articles…
Some of my calls went viral, at least by academic standards: since then, I accepted contributions by more than 130 authors. My name was out there early, so I received many invites and wrote 7-8 articles on the Covid.
On 3 March, I also wrote an outline for this presentation. And while I researched so many aspects of the Covid in the meantime, and while it would be completely legitimate to change the content of this presentation in the light of new developments, I decided to stick to the plan. In this presentation, I therefore present an updated version of argument outlined in my first article on the coronavirus co-authored with Peter McLaren and Michael Peters.
SLIDE 10: Slowly but surely, other journals started issuing similar calls.
Only few months after these horrendous events from videos I showed in the beginning, we are looking at, is serious cluttering of research space. Yes we need to make sense of the Covid-19 crisis, but how do we do that? How do 130 authors in Postdigital Science and Education contribute to making sense of the crisis and developing adequate measures against it? Who will read all this thousands, actually more like hundreds of thousands, words we so carefully wrote and edited?
Arguably, time is crucial. We got crisis on our hands, and we need to make sense of this crisis here and now. While Covid-19 will surely be analysed in many decades to come, we need to look into current developments …
SLIDE 11: I’ll just give a brief introduction here. In late 20th century human society has experienced a vast wave of digitalization. We digitized images, music, books, and (human) genome. In 1996, the cloning of Dolly the Sheep has marked a symbolic change in research direction.
According to Craig Venter, We’re actually starting at a new point: we’ve been digitizing biology, and now we’re trying to go from that digital code into a new phase of biology, with designing and synthesizing life. When we sequenced the human genome, it was going from the analog world of biology into the digital world of the computer. Now we’re trying to ask: can we regenerate life, or can we create new life, out of this digital universe? (Venter, 2008)
In our postdigital age, contagious diseases such as Covid-19 are at the same time biological (they arrive from nature, and affect human bodies), social and cultural (they illicit socially and culturally constructed responses) and postdigital (Covid-19 research is enabled and powered by digital technology).
Developed within a postdigital context, world’s response to the threat of Covid-19 says a lot about the viral nature of our modernity.
SLIDE 12: On 31 December 2019 we heard first news about the coronavirus. Exactly one month later, on 31 January 2020, UK’s Wellcome Trust issued a statement you can see on your screens. Initially signed by 67 large organisations such as the European Commission and mainstream academic publishers such as Elsevier and Springer Nature, the statement committed to ensure that:
all peer-reviewed research publications relevant to the outbreak are made immediately open access, or freely available at least for the duration of the outbreak
research findings relevant to the outbreak are shared immediately with the WHO upon journal submission, by the journal and with author knowledge
research findings are made available via preprint servers before journal publication, or via platforms that make papers openly accessible before peer review, with clear statements regarding the availability of underlying data
researchers share interim and final research data relating to the outbreak, together with protocols and standards used to collect the data, as rapidly and widely as possible - including with public health and research communities and the WHO
authors are clear that data or preprints shared ahead of submission will not pre-empt its publication in these journals (Wellcome Trust, 2020Wellcome Trust. (2020, 31 January). Press Release: Sharing research data and findings relevant to the novel coronavirus (Covid-19) outbreak.
Within days, research organisations have started to share results of their work on Covid-19 and academic publishers have quickly developed global infrastructure which enables such sharing.
SLIDE 13: Here is an example from Springer…
SLIDE 14: Here is an example from Taylor and Francis…
SLIDE 15: And here is an example from my work. As editor of Springer journal Postdigital Science and Education, I take active part in this effort.
SLIDE 16: The principles of open science have quickly brought about some impressive results. Within weeks, Chinese scientists “had sequenced the viral genome, deciphering the virus’s genetic code — a vital key to diagnosing and ultimately treating the disease. They immediately shared that critical genetic roadmap with researchers all over the world. That early collaboration allowed doctors in other countries to be ready when the first cases appeared outside China.” (Crowe, 2020)
This ground-breaking reaction of medical profession brings sends a larger message. As one of the commentators notes,
“When the story of the coronavirus (2019-nCOV) is finally written, it might well become a template for the utopian dream of open science — where research data is shared freely, unrestrained by competition, paywalls and patents.” (Crowe, 2020)
SLIDE 17: However, the principles of open science have also bumped into problems.
While I was doing research for my first COvid article, Google Scholar search for articles about the Covid-19 virus published between 1 January and 28 February 2020 returned 2,140 unique results. At a time, researchers looking for Covid-19 related academic articles in Google Scholar were faced with reading an average of 36 articles per day, and I predicted that this number will soon grow rapidly.
Day before yesterday, while I was preparing this presentation article count was about 215 000 articles. Divide this increase with the number of days, and you'll get an astonishing number of almost 2630 new articles per day. You can say, ok, but Scholar is hardly relevant.
SLIDE 18: Perhaps, but even if we look at the curated database, Web of Science, we are still speaking of 161 articles per day. Not words, articles. So how do we make sense of these articles?
Discounting for all disciplinary divisions and so on, it is very obvious that human beings just cannot read so much material.
And we are mere 6 months into the pandemic – how much material will we be dealing with in 5 years from now?
SLIDE 19: In 1986 The University of Chicago library scientist Don Swanson coined the phrase ‘undiscovered public knowledge’ to dramatise how solutions to long-standing problems may already be present in the academic literature, but academics are not motivated to read across fields sufficiently to put the pieces from different disciplines together. He occassionally updated the theory, and here you can see the first update from 1996.
SLIDE 20: Last year, just before the outbreak of the Corona, Steve Fuller and I looked back at Swanson’s ideas and updated them – and our update is now very relevant
So the critique here is at least three levels: 1) there’s more stuff than can be reasonably read; 2) disciplinary specialisation exacerbates the problem; 3) as a result, when we ask money for ‘new research’, we may end up reinventing the wheel, in the sense that the answer may already exist and we just don’t know it.
SLIDE 21: But let’s return to Swanson. What he says, basically, is that computers can help us systematize information, but their workings are still primarily aimed at helping people rather than making independent decisions.
Here at Edinburgh’s digital education group you have developed some of the most sophisticated critiques of data science in education, and I won’t get deeply into that because there are people in this audience who surely know much more about the topic than I do. Instead, I’d like to speak about something else… I’d like to speak about ways in which this research sits in the wider scheme of academic infosphere.
SLIDE 22: So what do we do? I know that I can read only a small portion of what gets published. I also know that Edinburgh’s Digital Ed group is one of the best out there, so I regularly read your publications. We occasionally publish together, and edit issues in places such as Learning, Media and Technology, Postdigital Science and Education, or edited books,. Then there’s Neil Selwyn’s group in Melbourne, then few others… we meet at conferences, we edit, publish, read, and refer to each other’s works.
Here I can deeply engage with your argument, write something myself, and it is likely that at least some of you will deeply engage with my argument. And if you fail to engage with my work, it will probably not be because you did not read it, but because you did not find it relevant enough – and this is a clear message that I should direct my research elsewhere.
Now such elitism has many problems. I’m not going to talk about ethical problems. But from a purely information science perspective, how much do we all together miss with this approach?
SLIDE 23: An alternative to the elite model is this. Here we have many voices, that we cannot hear individually, so we process them using AIs. We cannot reach into depth of any individual voice, but we can take into account many different voices.
Indeed, the AIs have brought about some impressive results in fields from medicine from digital humanities. Yet the problem here is, that computers and AIs are still unable to provide depth of insight characteristic for human beings.
Few days ago Ben Williamson gave an amazing keynote at Networked Learning Conference 2020 – apparently a recording will be available on their website at some point, and I encourage you to take a look.
SLIDE 24: Here, Ben shows a prime example of what Peters has called bioinformationalism. Networked learning bodies appear as the outcome of computational analyses that depend on data infrastructures, analytics algorithms and the apparatuses of new digital laboratories for educational research, knowledge production, and policy influence. These developments are poised to transform how educational research is conducted, and how the bodies and lives of students are perceived as objects of policy and practice.
SLIDE 25: Time to wrap up. The question of bioinformationalism is not new, and this group here does some of the best research in the field. So what can we learn from Covid-19?
Already in 2012, Michael Peters has developed the notion of viral modernity, which draws a close association between viral behaviours and information science. Indeed, we are not just dealing with the Covid-19 virus – we are also dealing with viral behaviour of our sciences’ response to the virus.
Remember the beginning of the presentation, when I described the dilemma of response to earthquake during the pandemic? As I noted, recommended responses to these disasters are directly opposed—the virus is avoided by staying at home, while (consequences of) the earthquake are avoided by going out. Faced with the invisible threat of the virus and the visible threat of being buried alive, no-one has returned to their flats.
In our research, we are facing a similar dilemma – we are reacting to the biological virus, by engaging in what can be considered as viral academic behaviours. Let me give you an example.
SLIDE 26: My journal, Postdigital Science and Education, is a host, a fertile ground for the bioinformationalist virus of Covid-19 research. With articles by 130 authors accepted for publication in less then 3 months, I, editor of PDSE, am what epidemiologists call a super spreader of the virus. Moray House, which has organised this symposium, is also a virus. And all of you, writing about the virus, are also the virus.
Of course we need to research and publish about the corona – by any means, I am not saying that we should ignore the pandemic. However, I think that we should become aware of viral nature of our responses, and that we should start to self-reflect on this nature.
SLIDE 27: Here are two ideas. First, we should turn the blade of our own work on posthumanism inwards. Outward-looking research is hugely important, as it develops theories and practices we urgently need. Yet I believe that this research needs to be supplemented with development of reflexivity in regards to our own work, in regards to our own contribution to the academic infodemic, in regards to our own position within viral modernity.
SLIDE 28: While I was preparing this presentation, I went out to the balcony to have a cup of coffee and took my iPad to check my Facebook - -I and found this example. I did not put the example here to offend or attack anyone, because I am – with all these calls and published papers – actually a much worse offender than the author of this post.
But I do want to point out that we all work and support research culture of essentially viral nature – research culture which contributes to production of so much material, that human beings cannot follow it anymore.
Therefore, my first point is that we should question that research culture, and try to develop it in more sustainable directions.
SLIDE 29: Secondly, an interesting idea which could provide a possible way forward is Gregory Bateson’s concept of ‘ecology of good ideas’. Right now, our ecologies of good ideas are either deeply elitist, or suffer from all drawbacks of data and algorithmic science.
So my question is: How do we expand our ecology of good ideas to avoid problems associated with data science? And, vice versa, how do we avoid an ecology of bad ideas?
This question can be approached from within data science, and most researchers these days arrive to some great results in this way – just take a look at some recent developments in digital humanities.
Yet I also believe that this question cannot be answered only within the framework of data science. To develop new ecologies of good ideas, however counterintuitive this may sound, we also need to reach beyond data.
SLIDE 30: There is a lot of good philosophy of technology, in works of people such as Bernard Stiegler, looking at this. These people show that ideas are dialectically inter-related with their ecologies. They clarify that ecologies of good ideas are always political. They develop some political and epistemic directions for that… and so on.
However, all this work has been developed before Covid-19, and I think that following lessons learned from the pandemic, there is a lot of good work to be done in development of ecologies of good ideas in relation to viral modernity and viral science.
SLIDE 31: I’m coming to an end to this presentation, so I’ll just briefly wrap up. Covid-19 teaches us an important lesson. Education sciences, which have been struggling with the bioniformationalist challenge for a while now, have now bumped into another connected yet nevertheless distinct problem – viral modernity, and viral nature of our sciences. I would argue, that we need to take the concept of bioninformationalism and viral modernity very seriously. Whether we like it or not, we are the virus, and we co-create the cultures and ecologies in which viruses flourish.
SLIDE 32: Remember the Muppet show? We are not these guys in the left, criticising from our lodges – we are Miss Piggy dancing at the centre of the stage of viral modernity.
I would argue, that education researchers urgently need to start developing own theories and practices of bioinformationalism and viral modernity. This needs to be done at the same time from within data science, and also from outside of data science.
We need to re-examine our own research cultures, and research ideas, to try and become less viral in our research.
Bateson’s concept of ecology of good ideas could be a possible starting point for our work, but there are surely others.
Being an academic editor, my first impulse is to start rethinking our publishing and researching practices. Yet I’m sure that you people will have many other ideas, and I look forward to hear them.