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)”.
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)”.
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, 2003; Chesbrough, 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)”.
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)”.
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)”.
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)”
Paper by Anthony Simonofski, Monique Snoeck and Benoît Vanderose: “As citizens have more and more opportunities to participate in public life, it is essential that administrations integrate this participation in their e-government processes. A smarter, more participatory, governance is a well-recognized and essential part of any city that wants to become “Smart” and generate public value. In this chapter, we will focus on the impact of this participatory approach on the development of e-government services by the city. Therefore, the goal of this chapter is to identify which methods administrations can apply to co-create their
As citizens have more and more opportunities to participate in public life, it is essential that administrations integrate this participation in their e-government processes. A smarter, more participatory, governance is a well-recognized and essential part of any city that wants to become “Smart” and generate public value. In this chapter, we will focus on the impact of this participatory approach on the development of e-government services by the city. Therefore, the goal of this chapter is to identify which methods administrations can apply to co-create their e-government services with citizens and to understand the gap between the methods used in practice and citizens’ preferences.
This chapter contributes to research and practice in different ways. First, the literature review allows the identification of eight participation methods to co-create e-government services. Second, we further examine these methods by means of 28 in-depth interviews, a questionnaire sent to public servants and a questionnaire sent to citizens. This multi-method approach allows identifying the barriers and drivers of public servants regarding the co-creation of e-government services but also the citizens’ perception of these methods. By contrasting the identified methods with their implementation, we better understand the discrepancies between literature and practice. At the same time, this chapter will give practitioners a repository of participation methods as well as information about the perception public servants and citizens have of them. Finally, we expect the insights provided in this chapter will stimulate research on the practical use of all these different methods…(More)”
Article by Elisa Lironi: “…Information and communication technology (ICT) can be used to implement more participatory mechanisms and foster democratic processes. Often referred to as e-democracy, there is a large range of very different possibilities for online engagement, including e-initiatives, e-consultations, crowdsourcing, participatory budgeting, and e-voting. Many European countries have started exploring ICT’s potential to reach more citizens at a lower cost and to tap into the so-called wisdom of the crowd, as governments attempt to earn citizens’ trust and revitalize European democracy by developing more responsive, transparent, and participatory decisionmaking processes.
For instance, when Anne Hidalgo was elected mayor of Paris in May 2014, one of her priorities was to make the city more collaborative by allowing Parisians to propose policy and develop projects together. In order to build a stronger relationship with the citizens, she immediately started to implement a citywide participatory budgeting project for the whole of Paris, including all types of policy issues. It started as a small pilot, with the city of Paris putting forward fifteen projects that could be funded with up to about 20 million euros and letting citizens vote on which projects to invest in, via ballot box or online. Parisians and local authorities deemed this experiment successful, so Hidalgo decided it was worth taking further, with more ideas and a bigger pot of money. Within two years, the level of participation grew significantly—from 40,000 voters in 2014 to 92,809 in 2016, representing 5 percent of the total urban population. Today, Paris Budget Participatif is an official platform that lets Parisians decide how to spend 5 percent of the investment budget from 2014 to 2020, amounting to around 500 million euros. In addition, the mayor also introduced two e-democracy platforms—Paris Petitions, for e-petitions, and Idée Paris, for e-consultations. Citizens in the French capital now have multiple channels to express their opinions and contribute to the development of their city.
In Latvia, civil society has played a significant role in changing how legislative procedures are organized. ManaBalss (My Voice) is a grassroots NGO that creates tools for better civic participation in decisionmaking processes. Its online platform, ManaBalss.lv, is a public e-participation website that lets Latvian citizens propose, submit, and sign legislative initiatives to improve policies at both the national and municipal level. …
In Finland, the government itself introduced an element of direct democracy into the Finnish political system, through the 2012 Citizens’ Initiative Act (CI-Act) that allows citizens to submit initiatives to the parliament. …
Other civic tech NGOs across Europe have been developing and experimenting with a variety of digital tools to reinvigorate democracy. These include initiatives like Science For You (SCiFY) in Greece, Netwerk Democratie in the Netherlands, and the Citizens Foundation in Iceland, which got its start when citizens were asked to crowdsource their constitution in 2010.
Outside of civil society, several private tech companies are developing digital platforms for democratic participation, mainly at the local government level. One example is the Belgian start-up CitizenLab, an online participation platform that has been used by more than seventy-five municipalities around the world. The young founders of CitizenLab have used technology to innovate the democratic process by listening to what politicians need and including a variety of functions, such as crowdsourcing mechanisms, consultation processes, and participatory budgeting. Numerous other European civic tech companies have been working on similar concepts—Cap Collectif in France, Delib in the UK, and Discuto in Austria, to name just a few. Many of these digital tools have proven useful to elected local or national representatives….
While these initiatives are making a real impact on the quality of European democracy, most of the EU’s formal policy focus is on constraining the power of the tech giants rather than positively aiding digital participation….(More)”
Book edited by Allan Afuah, Christopher L. Tucci, and Gianluigi Viscusi: “Examples of the value that can be created and captured through crowdsourcing go back to at least 1714 when the UK used crowdsourcing to solve the Longitude Problem, obtaining a solution that would enable the UK to become the dominant maritime force of its time. Today, Wikipedia uses crowds to provide entries for the world’s largest and free encyclopedia. Partly fueled by the value that can be created and captured through crowdsourcing, interest in researching the phenomenon has been remarkable.
Despite this – or perhaps because of it – research into crowdsourcing has been conducted in different research silos, within the fields of management (from strategy to finance to operations to information systems), biology, communications, computer science, economics, political science, among others. In these silos, crowdsourcing takes names such as broadcast search, innovation tournaments, crowdfunding, community innovation, distributed innovation, collective intelligence, open source, crowdpower, and even open innovation. This book aims to assemble chapters from many of these silos, since the ultimate potential of crowdsourcing research is likely to be attained only by bridging them. Chapters provide a systematic overview of the research on crowdsourcing from different fields based on a more encompassing definition of the concept, its difference for innovation, and its value for both private and public sector….(More)”.