Open science: after the COVID-19 pandemic there can be no return to closed working


Article by Virginia Barbour and Martin Borchert: “In the few months since the first case of COVID-19 was identified, the underlying cause has been isolated, its symptoms agreed on, its genome sequenced, diagnostic tests developed, and potential treatments and vaccines are on the horizon. The astonishingly short time frame of these discoveries has only happened through a global open science effort.

The principles and practices underpinning open science are what underpin good research—research that is reliable, reproducible, and has the broadest impact possible. It specifically requires the application of principles and practices that make research FAIR (Findable, Accessible, Interoperable, Reusable); researchers are making their data and preliminary publications openly accessible, and then publishers are making the peer-reviewed research immediately and freely available to all. The rapid dissemination of research—through preprints in particular as well as journal articles—stands in contrast to what happened in the 2003 SARS outbreak when the majority of research on the disease was published well after the outbreak had ended.

Many outside observers might reasonably assume, given the digital world we all now inhabit, that science usually works like this. Yet this is very far from the norm for most research. Science is not something that just happens in response to emergencies or specific events—it is an ongoing, largely publicly funded, national and international enterprise….

Sharing of the underlying data that journal articles are based on is not yet a universal requirement for publication, nor are researchers usually recognised for data sharing.

There are many benefits associated with an open science model. Image adapted from: Gaelen Pinnock/UCT; CC-BY-SA 4.0 .

Once published, even access to research is not seamless. The majority of academic journals still require a subscription to access. Subscriptions are expensive; Australian universities alone currently spend more than $300 million per year on subscriptions to academic journals. Access to academic journals also varies between universities with varying library budgets. The main markets for subscriptions to the commercial journal literature are higher education and health, with some access to government and commercial….(More)”.

Are there laws of history?


Amanda Rees at AEON: “…If big data could enable us to turn big history into mathematics rather than narratives, would that make it easier to operationalise our past? Some scientists certainly think so.

In February 2010, Peter Turchin, an ecologist from the University of Connecticut, predicted that 2020 would see a sharp increase in political volatility for Western democracies. Turchin was responding critically to the optimistic speculations of scientific progress in the journal Nature: the United States, he said, was coming to the peak of another instability spike (regularly occurring every 50 years or so), while the world economy was reaching the point of a ‘Kondratiev wave’ dip, that is, a steep downturn in a growth-driven supercycle. Along with a number of ‘seemingly disparate’ social pointers, all indications were that serious problems were looming. In the decade since that prediction, the entrenched, often vicious, social, economic and political divisions that have increasingly characterised North American and European society, have made Turchin’s ‘quantitative historical analysis’ seem remarkably prophetic.

A couple of years earlier, in July 2008, Turchin had made a series of trenchant claims about the nature and future of history. Totting up in excess of ‘200 explanations’ proposed to account for the fall of the Roman empire, he was appalled that historians were unable to agree ‘which explanations are plausible and which should be rejected’. The situation, he maintained, was ‘as risible as if, in physics, phlogiston theory and thermodynamics coexisted on equal terms’. Why, Turchin wanted to know, were the efforts in medicine and environmental science to produce healthy bodies and ecologies not mirrored by interventions to create stable societies? Surely it was time ‘for history to become an analytical, and even a predictive, science’. Knowing that historians were themselves unlikely to adopt such analytical approaches to the past, he proposed a new discipline: ‘theoretical historical social science’ or ‘cliodynamics’ – the science of history.

Like C P Snow 60 years before him, Turchin wanted to challenge the boundary between the sciences and humanities – even as periodic attempts to apply the theories of natural science to human behaviour (sociobiology, for example) or to subject natural sciences to the methodological scrutiny of the social sciences (science wars, anyone?) have frequently resulted in hostile turf wars. So what are the prospects for Turchin’s efforts to create a more desirable future society by developing a science of history?…

In 2010, Cliodynamics, the flagship journal for this new discipline, appeared, with its very first article (by the American sociologist Randall Collins) focusing on modelling victory and defeat in battle in relation to material resources and organisational morale. In a move that paralleled Comte’s earlier argument regarding the successive stages of scientific complexity (from physics, through chemistry and biology, to sociology), Turchin passionately rejected the idea that complexity made human societies unsuitable for quantitative analysis, arguing that it was precisely that complexity which made mathematics essential. Weather predictions were once considered unreliable because of the sheer complexity of managing the necessary data. But improvements in technology (satellites, computers) mean that it’s now possible to describe mathematically, and therefore to model, interactions between the system’s various parts – and therefore to know when it’s wise to carry an umbrella. With equal force, Turchin insisted that the cliodynamic approach was not deterministic. It would not predict the future, but instead lay out for governments and political leaders the likely consequences of competing policy choices.

Crucially, and again on the back of the abundantly available and cheap computer power, cliodynamics benefited from the surge in interest in the digital humanities. Existing archives were being digitised, uploaded and made searchable: every day, it seemed, more data were being presented in a format that encouraged quantification and enabled mathematical analysis – including the Old Bailey’s online database, of which Wolf had fallen foul. At the same time, cliodynamicists were repositioning themselves. Four years after its initial launch, the subtitle of their flagship journal was renamed, from The Journal of Theoretical and Mathematical History to The Journal of Quantitative History and Cultural Evolution. As Turchin’s editorial stated, this move was intended to position cliodynamics within a broader evolutionary analysis; paraphrasing the Russian-American geneticist Theodosius Dobzhansky, he claimed that ‘nothing in human history makes sense except in the light of cultural evolution’. Given Turchin’s ecological background, this evolutionary approach to history is unsurprising. But given the historical outcomes of making politics biological, it is potentially worrying….

Mathematical, data-driven, quantitative models of human experience that aim at detachment, objectivity and the capacity to develop and test hypotheses need to be balanced by explicitly fictional, qualitative and imaginary efforts to create and project a lived future that enable their audiences to empathically ground themselves in the hopes and fears of what might be to come. Both, after all, are unequivocally doing the same thing: using history and historical experience to anticipate the global future so that we might – should we so wish – avoid civilisation’s collapse. That said, the question of who ‘we’ are does, always, remain open….(More)”.

National Academies, National Science Foundation Create Network to Connect Decision-Makers with Social Scientists on Pressing COVID-19 Questions


Press Release: “The National Academies of Sciences, Engineering, and Medicine and the National Science Foundation announced today the formation of a Societal Experts Action Network (SEAN) to connect social and behavioral science researchers with decision-makers who are leading the response to COVID-19. SEAN will respond to the most pressing social, behavioral, and economic questions that are being asked by federal, state, and local officials by working with appropriate experts to quickly provide actionable answers.

The new network’s activities will be overseen by an executive committee in coordination with the National Academies’ Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats, established earlier this year to provide rapid expert input on urgent questions facing the federal government on the COVID-19 pandemic. Standing committee members Robert Groves, executive vice president and provost at Georgetown University, and Mary T. Bassett, director of the François-Xavier Bagnoud Center for Health and Human Rights at Harvard University, will co-chair the executive committee to manage SEAN’s solicitation of questions and expert responses, anticipate leaders’ research needs, and guide the dissemination of network findings.

SEAN will include individual researchers from a broad range of disciplines as well as leading national social and behavioral science institutions. Responses to decision-maker requests may range from individual phone calls and presentations to written committee documents such as Rapid Expert Consultations.

“This pandemic has broadly impacted all aspects of life — not just our health, but our work, families, education, supply chains, and even the global environment,” said Marcia McNutt, president of the National Academy of Sciences. “Therefore, to address the myriad questions that are being raised by mayors, governors, local representatives, and other leaders, we must recruit the full range of scientific expertise from across the social, natural, and biomedical sciences.”   

“Our communities and our society at large are facing a range of complex issues on multiple fronts due to COVID-19,” said Arthur Lupia, head of the Directorate for Social, Behavioral, and Economic Sciences at the National Science Foundation. “These are human-centered issues affecting our daily lives — the education and well-being of our children, the strength of our economy, the health of our loved ones, neighbors, and so many more. Through SEAN, social and behavioral scientists will provide actionable, evidence-driven guidance to our leaders across the U.S. who are working to support our communities and speed their recovery.”…(More)”.

A data sharing method in the open web environment: Data sharing in hydrology


Paper by Jin Wang et al: “Data sharing plays a fundamental role in providing data resources for geographic modeling and simulation. Although there are many successful cases of data sharing through the web, current practices for sharing data mostly focus on data publication using metadata at the file level, which requires identifying, restructuring and synthesizing raw data files for further usage. In hydrology, because the same hydrological information is often stored in data files with different formats, modelers should identify the required information from multisource data sets and then customize data requirements for their applications. However, these data customization tasks are difficult to repeat, which leads to repetitive labor. This paper presents a data sharing method that provides a solution for data manipulation based on a structured data description model rather than raw data files. With the structured data description model, multisource hydrological data can be accessed and processed in a unified way and published as data services using a designed data server. This study also proposes a data configuration manager to customize data requirements through an interactive programming tool, which can help in using the data services. In addition, a component-based data viewer is developed for the visualization of multisource data in a sharable visualization scheme. A case study that involves sharing and applying hydrological data is designed to examine the applicability and feasibility of the proposed data sharing method….(More)”.

Epistemic Humility—Knowing Your Limits in a Pandemic


Essay by Erik Angner: “Ignorance,” wrote Charles Darwin in 1871, “more frequently begets confidence than does knowledge.”

Darwin’s insight is worth keeping in mind when dealing with the current coronavirus crisis. That includes those of us who are behavioral scientists. Overconfidence—and a lack of epistemic humility more broadly—can cause real harm.

In the middle of a pandemic, knowledge is in short supply. We don’t know how many people are infected, or how many people will be. We have much to learn about how to treat the people who are sick—and how to help prevent infection in those who aren’t. There’s reasonable disagreement on the best policies to pursue, whether about health care, economics, or supply distribution. Although scientists worldwide are working hard and in concert to address these questions, final answers are some ways away.

Another thing that’s in short supply is the realization of how little we know. Even a quick glance at social or traditional media will reveal many people who express themselves with way more confidence than they should…

Frequent expressions of supreme confidence might seem odd in light of our obvious and inevitable ignorance about a new threat. The thing about overconfidence, though, is that it afflicts most of us much of the time. That’s according to cognitive psychologists, who’ve studied the phenomenon systematically for half a century. Overconfidence has been called “the mother of all psychological biases.” The research has led to findings that are at the same time hilarious and depressing. In one classic study, for example, 93 percent of U.S. drivers claimed to be more skillful than the median—which is not possible.

“But surely,” you might object, “overconfidence is only for amateurs—experts would not behave like this.” Sadly, being an expert in some domain does not protect against overconfidence. Some research suggests that the more knowledgeable are more prone to overconfidence. In a famous study of clinical psychologists and psychology students, researchers asked a series of questions about a real person described in psychological literature. As the participants received more and more information about the case, their confidence in their judgment grew—but the quality of their judgment did not. And psychologists with a Ph.D. did no better than the students….(More)”.

We Have the Power to Destroy Ourselves Without the Wisdom to Ensure That We Don’t


EdgeCast by Toby Ord: “Lately, I’ve been asking myself questions about the future of humanity, not just about the next five years or even the next hundred years, but about everything humanity might be able to achieve in the time to come.

The past of humanity is about 200,000 years. That’s how long Homo sapiens have been around according to our current best guess (it might be a little bit longer). Maybe we should even include some of our other hominid ancestors and think about humanity somewhat more broadly. If we play our cards right, we could live hundreds of thousands of years more. In fact, there’s not much stopping us living millions of years. The typical species lives about a million years. Our 200,000 years so far would put us about in our adolescence, just old enough to be getting ourselves in trouble, but not wise enough to have thought through how we should act.

But a million years isn’t an upper bound for how long we could live. The horseshoe crab, for example, has lived for 450 million years so far. The Earth should remain habitable for at least that long. So, if we can survive as long as the horseshoe crab, we could have a future stretching millions of centuries from now. That’s millions of centuries of human progress, human achievement, and human flourishing. And if we could learn over that time how to reach out a little bit further into the cosmos to get to the planets around other stars, then we could have longer yet. If we went seven light-years at a time just making jumps of that distance, we could reach almost every star in the galaxy by continually spreading out from the new location. There are already plans in progress to send spacecraft these types of distances. If we could do that, the whole galaxy would open up to us….

Humanity is not a typical species. One of the things that most worries me is the way in which our technology might put us at risk. If we look back at the history of humanity these 2000 centuries, we see this initially gradual accumulation of knowledge and power. If you think back to the earliest humans, they weren’t that remarkable compared to the other species around them. An individual human is not that remarkable on the Savanna compared to a cheetah, or lion, or gazelle, but what set us apart was our ability to work together, to cooperate with other humans to form something greater than ourselves. It was teamwork, the ability to work together with those of us in the same tribe that let us expand to dozens of humans working together in cooperation. But much more important than that was our ability to cooperate across time, across the generations. By making small innovations and passing them on to our children, we were able to set a chain in motion wherein generations of people worked across time, slowly building up these innovations and technologies and accumulating power….(More)”.

Covid-19 Changed How the World Does Science, Together


Matt Apuzzo and David D. Kirkpatrick at The New York Times: “…Normal imperatives like academic credit have been set aside. Online repositories make studies available months ahead of journals. Researchers have identified and shared hundreds of viral genome sequences. More than 200 clinical trials have been launched, bringing together hospitals and laboratories around the globe.

“I never hear scientists — true scientists, good quality scientists — speak in terms of nationality,” said Dr. Francesco Perrone, who is leading a coronavirus clinical trial in Italy. “My nation, your nation. My language, your language. My geographic location, your geographic location. This is something that is really distant from true top-level scientists.”

On a recent morning, for example, scientists at the University of Pittsburgh discovered that a ferret exposed to Covid-19 particles had developed a high fever — a potential advance toward animal vaccine testing. Under ordinary circumstances, they would have started work on an academic journal article.

“But you know what? There is going to be plenty of time to get papers published,” said Paul Duprex, a virologist leading the university’s vaccine research. Within two hours, he said, he had shared the findings with scientists around the world on a World Health Organization conference call. “It is pretty cool, right? You cut the crap, for lack of a better word, and you get to be part of a global enterprise.”…

Several scientists said the closest comparison to this moment might be the height of the AIDS epidemic in the 1990s, when scientists and doctors locked arms to combat the disease. But today’s technology and the pace of information-sharing dwarfs what was possible three decades ago.

As a practical matter, medical scientists today have little choice but to study the coronavirus if they want to work at all. Most other laboratory research has been put on hold because of social distancing, lockdowns or work-from-home restrictions.

The pandemic is also eroding the secrecy that pervades academic medical research, said Dr. Ryan Carroll, a Harvard Medical professor who is involved in the coronavirus trial there. Big, exclusive research can lead to grants, promotions and tenure, so scientists often work in secret, suspiciously hoarding data from potential competitors, he said.

“The ability to work collaboratively, setting aside your personal academic progress, is occurring right now because it’s a matter of survival,” he said….(More)”.

Synthetic data offers advanced privacy for the Census Bureau, business


Kate Kaye at IAPP: “In the early 2000s, internet accessibility made risks of exposing individuals from population demographic data more likely than ever. So, the U.S. Census Bureau turned to an emerging privacy approach: synthetic data.

Some argue the algorithmic techniques used to develop privacy-secure synthetic datasets go beyond traditional deidentification methods. Today, along with the Census Bureau, clinical researchers, autonomous vehicle system developers and banks use these fake datasets that mimic statistically valid data.

In many cases, synthetic data is built from existing data by filtering it through machine learning models. Real data representing real individuals flows in, and fake data mimicking individuals with corresponding characteristics flows out.

When data scientists at the Census Bureau began exploring synthetic data methods, adoption of the internet had made deidentified, open-source data on U.S. residents, their households and businesses more accessible than in the past.

Especially concerning, census-block-level information was now widely available. Because in rural areas, a census block could represent data associated with as few as one house, simply stripping names, addresses and phone numbers from that information might not be enough to prevent exposure of individuals.

“There was pretty widespread angst” among statisticians, said John Abowd, the bureau’s associate director for research and methodology and chief scientist. The hand-wringing led to a “gradual awakening” that prompted the agency to begin developing synthetic data methods, he said.

Synthetic data built from the real data preserves privacy while providing information that is still relevant for research purposes, Abowd said: “The basic idea is to try to get a model that accurately produces an image of the confidential data.”

The plan for the 2020 census is to produce a synthetic image of that original data. The bureau also produces On the Map, a web-based mapping and reporting application that provides synthetic data showing where workers are employed and where they live along with reports on age, earnings, industry distributions, race, ethnicity, educational attainment and sex.

Of course, the real census data is still locked away, too, Abowd said: “We have a copy and the national archives have a copy of the confidential microdata.”…(More)”.

Birth of Intelligence: From RNA to Artificial Intelligence


Book by Daeyeol Lee: “What is intelligence? How did it begin and evolve to human intelligence? Does a high level of biological intelligence require a complex brain? Can man-made machines be truly intelligent? Is AI fundamentally different from human intelligence? In Birth of Intelligence, distinguished neuroscientist Daeyeol Lee tackles these pressing fundamental issues. To better prepare for future society and its technology, including how the use of AI will impact our lives, it is essential to understand the biological root and limits of human intelligence. After systematically reviewing biological and computational underpinnings of decision making and intelligent behaviors, Birth of Intelligence proposes that true intelligence requires life…(More)”.

The Rules of Contagion: Why Things Spread–And Why They Stop


Book by Adam Kucharski: “From ideas and infections to financial crises and “fake news,” why the science of outbreaks is the science of modern life.


These days, whenever anything spreads, whether it’s a YouTube fad or a political rumor, we say it went viral. But how does virality actually work? In The Rules of Contagion, epidemiologist Adam Kucharski explores topics including gun violence, online manipulation, and, of course, outbreaks of disease to show how much we get wrong about contagion, and how astonishing the real science is.
Why did the president retweet a Mussolini quote as his own? Why do financial bubbles take off so quickly? Why are disinformation campaigns so effective? And what makes the emergence of new illnesses–such as MERS, SARS, or the coronavirus disease COVID-19–so challenging? By uncovering the crucial factors driving outbreaks, we can see how things really spread — and what we can do about it….(More)”.