Politics and Open Science: How the European Open Science Cloud Became Reality (the Untold Story)


Jean-Claude Burgelman at Data Intelligence: “This article will document how the European Open Science Cloud (EOSC) emerged as one of the key policy intentions to foster Open Science (OS) in Europe. It will describe some of the typical, non-rational roadblocks on the way to implement EOSC. The article will also argue that the only way Europe can take care of its research data in a way that fits the European specificities fully, is by supporting EOSC.

It is fair to say—note the word FAIR here—that realizing the European Open Science Cloud (EOSC) is now part and parcel of the European Data Science (DS) policy. In particular since EOSC will be from 2021 in the hands of the independent EOSC Association and thus potentially way out of the so-called “Brussels Bubble”.

This article will document the whole story of how EOSC emerged in this “bubble” as one of the policy intentions to foster Open Science (OS) in Europe. In addition, it will describe some of the typical, non-rational roadblocks on the way to implement EOSC. The article will also argue that the only way Europe can take care of its research data in a way that fits the European specificities fully, is by supporting EOSC….(More)”

Rising to the Challenge: how to get the best value from using prizes to drive innovation for development


Report by Cheryl Brown, Catherine Gould, Clare Stott: “An innovation inducement prize enables funders to pursue development goals without them having to know in advance which approaches or participants are most likely to succeed. Innovation prizes also often directly engage with the intended beneficiaries or those connected with them, in solving the problems.

At a time when development spending is under increasing pressure to show value for money (VFM), innovation prizes are considered as an alternative to mainstream funding options. While costs are likely to have accrued through prize design and management, no cash payments are made until the prize is successfully awarded. The funder may anticipate obtaining more results than those directly paid for through the prize award.

The purpose of this report is to answer two questions: do innovation prizes work for development, and if so, when do they offer value over other forms of funding?

To date, few evaluations have been published that would help funders answer these questions for themselves. DFID commissioned the Ideas to Impact programme, which was delivered by an IMC Worldwide-led consortium and evaluated by Itad, to fill this gap by testing a range of innovation prizes targeted at different development issues and this report synthesises the findings from the evaluations and follow-up reviews of six of these prizes….(More)”.

Tackling Societal Challenges with Open Innovation


Introduction to Special Issue of California Management Review by Anita M. McGahan, Marcel L. A. M. Bogers, Henry Chesbrough, and Marcus Holgersson: “Open innovation includes external knowledge sources and paths to market as complements to internal innovation processes. Open innovation has to date been driven largely by business objectives, but the imperative of social challenges has turned attention to the broader set of goals to which open innovation is relevant. This introduction discusses how open innovation can be deployed to address societal challenges—as well as the trade-offs and tensions that arise as a result. Against this background we introduce the articles published in this Special Section, which were originally presented at the sixth Annual World Open Innovation Conference….(More)”.

The Few, the Tired, the Open Source Coders


Article by Clive Thompson: “…When the open source concept emerged in the ’90s, it was conceived as a bold new form of communal labor: digital barn raisings. If you made your code open source, dozens or even hundreds of programmers would chip in to improve it. Many hands would make light work. Everyone would feel ownership.

Now, it’s true that open source has, overall, been a wild success. Every startup, when creating its own software services or products, relies on open source software from folks like Thornton: open source web-server code, open source neural-net code. But, with the exception of some big projects—like Linux—the labor involved isn’t particularly communal. Most are like Bootstrap, where the majority of the work landed on a tiny team of people.

Recently, Nadia Eghbal—the head of writer experience at the email newsletter platform Substack—published Working in Public, a fascinating book for which she spoke to hundreds of open source coders. She pinpointed the change I’m describing here. No matter how hard the programmers worked, most “still felt underwater in some shape or form,” Eghbal told me.

Why didn’t the barn-raising model pan out? As Eghbal notes, it’s partly that the random folks who pitch in make only very small contributions, like fixing a bug. Making and remaking code requires a lot of high-level synthesis—which, as it turns out, is hard to break into little pieces. It lives best in the heads of a small number of people.

Yet those poor top-level coders still need to respond to the smaller contributions (to say nothing of requests for help or reams of abuse). Their burdens, Eghbal realized, felt like those of YouTubers or Instagram influencers who feel overwhelmed by their ardent fan bases—but without the huge, ad-based remuneration.

Sometimes open source coders simply walk away: Let someone else deal with this crap. Studies suggest that about 9.5 percent of all open source code is abandoned, and a quarter is probably close to being so. This can be dangerous: If code isn’t regularly updated, it risks causing havoc if someone later relies on it. Worse, abandoned code can be hijacked for ill use. Two years ago, the pseudonymous coder right9ctrl took over a piece of open source code that was used by bitcoin firms—and then rewrote it to try to steal cryptocurrency….(More)”.

The Open Innovation in Science research field: a collaborative conceptualisation approach


Paper by Susanne Beck et al: “Openness and collaboration in scientific research are attracting increasing attention from scholars and practitioners alike. However, a common understanding of these phenomena is hindered by disciplinary boundaries and disconnected research streams. We link dispersed knowledge on Open Innovation, Open Science, and related concepts such as Responsible Research and Innovation by proposing a unifying Open Innovation in Science (OIS) Research Framework. This framework captures the antecedents, contingencies, and consequences of open and collaborative practices along the entire process of generating and disseminating scientific insights and translating them into innovation. Moreover, it elucidates individual-, team-, organisation-, field-, and society‐level factors shaping OIS practices. To conceptualise the framework, we employed a collaborative approach involving 47 scholars from multiple disciplines, highlighting both tensions and commonalities between existing approaches. The OIS Research Framework thus serves as a basis for future research, informs policy discussions, and provides guidance to scientists and practitioners….(More)”.

German coronavirus experiment enlists help of concertgoers


Philip Oltermann at the Guardian: “German scientists are planning to equip 4,000 pop music fans with tracking gadgets and bottles of fluorescent disinfectant to get a clearer picture of how Covid-19 could be prevented from spreading at large indoor concerts.

As cultural mass gatherings across the world remain on hold for the foreseeable future, researchers in eastern Germany are recruiting volunteers for a “coronavirus experiment” with the singer-songwriter Tim Bendzko, to be held at an indoor stadium in the city of Leipzig on 22 August.

Participants, aged between 18 and 50, will wear matchstick-sized “contact tracer” devices on chains around their necks that transmit a signal at five-second intervals and collect data on each person’s movements and proximity to other members of the audience.

Inside the venue, they will also be asked to disinfect their hands with a fluorescent hand-sanitiser – designed to not just add a layer of protection but allow scientists to scour the venue with UV lights after the concerts to identify surfaces where a transmission of the virus through smear infection is most likely to take place.

Vapours from a fog machine will help visualise the possible spread of coronavirus via aerosols, which the scientists will try to predict via computer-generated models in advance of the event.

The €990,000 cost of the Restart-19 project will be shouldered between the federal states of Saxony and Saxony-Anhalt. The project’s organisers say the aim is to “identify a framework” for how larger cultural and sports events could be held “without posing a danger for the population” after 30 September….

To stop the Leipzig experiment from becoming the source of a new outbreak, signed-up volunteers will be sent a DIY test kit and have a swab at a doctor’s practice or laboratory 48 hours before the concert starts. Those who cannot show proof of a negative test at the door will be denied entry….(More)”.

To recover faster from Covid-19, open up: Managerial implications from an open innovation perspective


Paper by Henry Chesbrough: “Covid-19 has severely tested our public health systems. Recovering from Covid-19 will soon test our economic systems. Innovation will have an important role to play in recovering from the aftermath of the coronavirus. This article discusses both how to manage innovation as part of that recovery, and also derives some lessons from how we have responded to the virus so far, and what those lessons imply for managing innovation during the recovery.

Covid-19’s assault has prompted a number of encouraging developments. One development has been the rapid mobilization of scientists, pharmaceutical companies and government officials to launch a variety of scientific initiatives to find an effective response to the virus. As of the time of this writing, there are tests underway of more than 50 different compounds as possible vaccines against the virus.1 Most of these will ultimately fail, but the severity of the crisis demands that we investigate every plausible candidate. We need rapid, parallel experimentation, and it must be the test data that select our vaccine, not internal political or bureaucratic processes.

A second development has been the release of copious amounts of information about the virus, its spread, and human responses to various public health measures. The Gates Foundation, working with the Chan-Zuckerberg Foundation and the White House Office of Science and Technology Policy have joined forces to publish all of the known medical literature on the coronavirus, in machine-readable form. This was done with the intent to accelerate the analysis of the existing research to identify possible new avenues of attack against Covid-19. The coronavirus itself was synthesized early on in the outbreak by scientists in China, providing the genetic sequence of the virus, and showing where it differed from earlier viruses such as SARS and MERS. This data was immediately shared widely with scientists and researchers around the world. At the same time, GITHUB and the Humanitarian Data Exchange each have an accumulating series of datasets on the geography of the spread of the disease (including positive test cases, hospitalizations, and deaths).

What these developments have in common is openness. In fighting a pandemic, speed is crucial, and the sooner we know more and are able to take action, the better for all of us. Opening up mobilizes knowledge from many different places, causing our learning to advance and our progress against the disease to accelerate. Openness unleashes a volunteer army of researchers, working in their own facilities, across different time zones, and different countries. Openness leverages the human capital available in the world to tackle the disease, and also accesses the physical capital (such as plant and equipment) already in place to launch rapid testing of possible solutions. This openness corresponds well to an academic body of work called open innovation (Chesbrough, 2003Chesbrough, 2019).

Innovation is often analyzed in terms of costs, and the question of whether to “make or buy” often rests on which approach costs less. But in a pandemic, time is so valuable and essential, that the question of costs is far less important than the ability to get to a solution sooner. The Covid-19 disease appears to be doubling every 3–5 days, so a delay of just a few weeks in the search for a new vaccine (they normally take 1–2 years to develop, or more) might witness multiple doublings of size of the population infected with the disease. It is for this reason that Bill Gates is providing funds to construct facilities in advance for producing the leading vaccine candidates. Though the facilities for the losing candidates will not be used, it will save precious time to make the winning vaccine in high volume, once it is found.

Open innovation can help speed things up….(More)”.

Unleashing the Crowd: Collaborative Solutions to Wicked Business and Societal Problems


Book by Ann Majchrzak and Arvind Malhotra: “This book disrupts the way practitioners and academic scholars think about crowds, crowdsourcing, innovation, and new organizational forms in this emerging period of ubiquitous access to the internet. The authors argue that the current approach to crowdsourcing unnecessarily limits the crowd to offering ideas, locking out those of us with knowledge about a problem.  They use data from 25 case studies of flash crowds — anonymous strangers answering online announcements to participate in a 7-10 day innovation challenge — half of whom were unleashed from the limitations of focusing on ideas.  Yet, these crowds were able to develop new business models, new product lines, and offer useful solutions to global problems in fields as diverse as health care insurance, software development, and societal change. This book, which offers a theory of collective production of innovative solutions explaining the practices that the crowds organically followed, will revolutionize current assumptions about how innovation and crowdsourcing should be managed for commercial as well as societal purposes….(More)”.

Whose Commons? Data Protection as a Legal Limit of Open Science


Mark Phillips and Bartha M. Knoppers in the Journal of Law, Medicine and Ethics: “Open science has recently gained traction as establishment institutions have come on-side and thrown their weight behind the movement and initiatives aimed at creation of information commons. At the same time, the movement’s traditional insistence on unrestricted dissemination and reuse of all information of scientific value has been challenged by the movement to strengthen protection of personal data. This article assesses tensions between open science and data protection, with a focus on the GDPR.

Powerful institutions across the globe have recently joined the ranks of those making substantive commitments to “open science.” For example, the European Commission and the NIH National Cancer Institute are supporting large-scale collaborations, such as the Cancer Genome Collaboratory, the European Open Science Cloud, and the Genomic Data Commons, with the aim of making giant stores of genomic and other data readily available for analysis by researchers. In the field of neuroscience, the Montreal Neurological Institute is midway through a novel five-year project through which it plans to adopt open science across the full spectrum of its research. The commitment is “to make publicly available all positive and negative data by the date of first publication, to open its biobank to registered researchers and, perhaps most significantly, to withdraw its support of patenting on any direct research outputs.” The resources and influence of these institutions seem to be tipping the scales, transforming open science from a longstanding aspirational ideal into an existing reality.

Although open science lacks any standard, accepted definition, one widely-cited model proposed by the Austria-based advocacy effort openscienceASAP describes it by reference to six principles: open methodology, open source, open data, open access, open peer review, and open educational resources. The overarching principle is “the idea that scientific knowledge of all kinds should be openly shared as early as is practical in the discovery process.” This article adopts this principle as a working definition of open science, with a particular emphasis on open sharing of human data.

As noted above, many of the institutions committed to open science use the word “commons” to describe their initiatives, and the two concepts are closely related. “Medical information commons” refers to “a networked environment in which diverse sources of health, medical, and genomic information on large populations become widely shared resources.” Commentators explicitly link the success of information commons and progress in the research and clinical realms to open science-based design principles such as data access and transparent analysis (i.e., sharing of information about methods and other metadata together with medical or health data).

But what legal, as well as ethical and social, factors will ultimately shape the contours of open science? Should all restrictions be fought, or should some be allowed to persist, and if so, in what form? Given that a commons is not a free-for-all, in that its governing rules shape its outcomes, how might we tailor law and policy to channel open science to fulfill its highest aspirations, such as universalizing practical access to scientific knowledge and its benefits, and avoid potential pitfalls? This article primarily concerns research data, although passing reference is also made to the approach to the terms under which academic publications are available, which are subject to similar debates….(More)”.

When Patients Become Innovators


Article by Harold DeMonaco, Pedro Oliveira, Andrew Torrance, Christiana von Hippel, and Eric von Hippel: “Patients are increasingly able to conceive and develop sophisticated medical devices and services to meet their own needs — often without any help from companies that produce or sell medical products. This “free” patient-driven innovation process enables them to benefit from important advances that are not commercially available. Patient innovation also can provide benefits to companies that produce and sell medical devices and services. For them, patient do-it-yourself efforts can be free R&D that informs and amplifies in-house development efforts.

In this article, we will look at two examples of free innovation in the medical field — one for managing type 1 diabetes and the other for managing Crohn’s disease. We will set these cases within the context of the broader free innovation movement that has been gaining momentum in an array of industries1 and apply the general lessons of free innovation to the specific circumstances of medical innovation by patients….

What is striking about both of these cases is that neither commercial medical producers nor the clinical care system offered a solution that these patients urgently needed. Motivated patients stepped forward to develop solutions for themselves, entirely without commercial support.4

Free innovation in the medical field follows the general pattern seen in many other areas, including crafts, sporting goods, home and garden equipment, pet products, and apparel.5 Enabled by technology, social media, and a keen desire to find solutions aligned with their own needs, consumers of all kinds are designing new products for themselves….(More)”