Jasper Bovenberg, David Peloquin, Barbara Bierer, Mark Barnes, and Bartha Maria Knoppers at Science: “Since the advent of the European Union (EU) General Data Protection Regulation (GDPR) in 2018, the biomedical research community has struggled to share data with colleagues and consortia outside the EU, as the GDPR limits international transfers of personal data. A July 2020 ruling of the Court of Justice of the European Union (CJEU) reinforced obstacles to sharing, and even data transfer to enable essential research into coronavirus disease 2019 (COVID-19) has been restricted in a recent Guidance of the European Data Protection Board (EDPB). We acknowledge the valid concerns that gave rise to the GDPR, but we are concerned that the GDPR’s limitations on data transfers will hamper science globally in general and biomedical science in particular (see the text box) (1)—even though one stated objective of the GDPR is that processing of personal data should serve humankind, and even though the GDPR explicitly acknowledges that the right to the protection of personal data is not absolute and must be considered in relation to its function in society and be balanced against other fundamental rights. We examine whether there is room under the GDPR for EU biomedical researchers to share data from the EU with the rest of the world to facilitate biomedical research. We then propose solutions for consideration by either the EU legislature, the EU Commission, or the EDPB in its planned Guidance on the processing of health data for scientific research. Finally, we urge the EDPB to revisit its recent Guidance on COVID-19 research….(More)“.
Situating Open Data: Global Trends in Local Contexts
Open Access Book edited by Danny Lämmerhirt, Ana Brandusescu, Natalia Domagala & Patrick Enaholo: “Open data and its effects on society are always woven into infrastructural legacies, social relations, and the political economy. This raises questions about how our understanding and engagement with open data shifts when we focus on its situated use.
To shed a light on these questions, Situating Open Data provides several empirical accounts of open data practices, the local implementation of global initiatives, and the development of new open data ecosystems. Drawing on case studies in different countries and contexts, the chapters demonstrate the practices and actors involved in open government data initiatives unfolding within different socio-political settings.
The book proposes three recommendations for researchers, policy-makers and practitioners. First, beyond upskilling through ‘data literacy’ programmes, open data initiatives should be specified through the kinds of data practices and effects they generate. Second, global visions of open data implementation require more studies of the resonances and tensions created in localised initiatives. And third, research into open data ecosystems requires more attention to the histories and legacies of information infrastructures and how these shape who benefits from open data flows.
As such, this volume departs from the framing of data as a resource to be deployed. Instead, it proposes a prism of different data practices in different contexts through which to study the social relations, capacities, infrastructural histories and power structures affecting open data initiatives. It is hoped that the contributions collected in Situating Open Data will spark critical reflection about the way open data is locally practiced and implemented. The contributions should be of interest to open data researchers, advocates, and those in or advising government administrations designing and rolling out effective open data initiatives….(More)”.
Science and Scientists Held in High Esteem Across Global Publics
Pew Research: “As publics around the world look to scientists and the research and development process to bring new treatments and preventive strategies for the novel coronavirus, a new international survey finds scientists and their research are widely viewed in a positive light across global publics, and large majorities believe government investments in scientific research yield benefits for society.
Still, the wide-ranging survey, conducted before the COVID-19 outbreak reached pandemic proportions, reveals ambivalence about certain scientific developments – in areas such as artificial intelligence and genetically modified foods – often exists alongside high trust for scientists generally and positive views in other areas such as space exploration….
Scientists as a group are highly regarded, compared with other prominent groups and institutions in society. In all publics, majorities have at least some trust in scientists to do what is right. A median of 36% have “a lot” of trust in scientists, the same share who say this about the military, and much higher than the shares who say this about business leaders, the national government and the news media.
Still, an appreciation for practical experience, more so than expertise, in general, runs deep across publics. A median of 66% say it’s better to rely on people with practical experience to solve pressing problems, while a median of 28% say it’s better to rely on people who are considered experts about the problems, even if they don’t have much practical experience….(More)”.
The Wisdom of the Crowd: Promoting Media Development through Deliberative Initiatives
Report by Craig Matasick: “…innovative new set of citizen engagement practices—collectively known as deliberative democracy—offers important lessons that, when applied to the media development efforts, can help improve media assistance efforts and strengthen independent media environments around the world. At a time when disinformation runs rampant, it is more important than ever to strengthen public demand for credible information, reduce political polarization, and prevent media capture. Deliberative democracy approaches can help tackle these issues by expanding the number and diversity of voices that participate in policymaking, thereby fostering greater collective action and enhancing public support for media reform efforts.
Through a series of five illustrative case studies, the report demonstrates how deliberative democracy practices can be employed in both media development and democracy assistance efforts, particularly in the Global South. Such initiatives produce recommendations that take into account a plurality of voices while building trust between citizens and decision-makers by demonstrating to participants that their issues will be heard and addressed. Ultimately, this process can enable media development funders and practitioners to identify priorities and design locally relevant projects that have a higher likelihood for long-term impact.
– Deliberative democracy approaches, which are characterized by representative participation and moderated deliberation, provide a framework to generate demand-driven media development interventions while at the same time building greater public support for media reform efforts.
– Deliberative democracy initiatives foster collaboration across different segments of society, building trust in democratic institutions, combatting polarization, and avoiding elite capture.
– When employed by news organizations, deliberative approaches provide a better understanding of the issues their audiences care most about and uncover new problems affecting citizens that might not otherwise have come to light….(More)”.
Private Sector Data for Humanitarian Response: Closing the Gaps
Jos Berens at Bloomberg New Economy Forum: “…Despite these and other examples, data sharing between the private sector and humanitarian agencies is still limited. Out of 281 contributing organizations on HDX, only a handful come from the private sector.
So why don’t we see more use of private sector data in humanitarian response? One obvious set of challenges concerns privacy, data protection and ethics. Companies and their customers are often wary of data being used in ways not related to the original purpose of data collection. Such concerns are understandable, especially given the potential legal and reputational consequences of personal data breaches and leaks.
Figuring out how to use this type of sensitive data in an already volatile setting seems problematic, and it is — negotiations between public and private partners in the middle of a crisis often get hung up on a lack of mutual understanding. Data sharing partnerships negotiated during emergencies often fail to mature beyond the design phase. This dynamic creates a loop of inaction due to a lack of urgency in between crises, followed by slow and halfway efforts when action is needed most.
To ensure that private sector data is accessible in an emergency, humanitarian organizations and private sector companies need to work together to build partnerships before a crisis. They can do this by taking the following actions:
- Invest in relationships and build trust. Both humanitarian organizations and private sector organizations should designate focal points who can quickly identify potentially useful data during a humanitarian emergency. A data stewards network which identifies and connects data responsibility leaders across organizations, as proposed by the NYU Govlab, is a great example of how such relations could look. Efforts to build trust with the general public regarding private sector data use for humanitarian response should also be strengthened, primarily through transparency about the means and purpose of such collaborations. This is particularly important in the context of COVID-19, as noted in the UN Comprehensive Response to COVID-19 and the World Economic Forum’s ‘Great Reset’ initiative…(More)”.
An Open-Source Tool to Accelerate Scientific Knowledge Discovery
Mozilla: “Timely and open access to novel outputs is key to scientific research. It allows scientists to reproduce, test, and build on one another’s work — and ultimately unlock progress.
The most recent example of this is the research into COVID-19. Much of the work was published in open access journals, swiftly reviewed and ultimately improving our understanding of how to slow the spread and treat the disease. Although this rapid increase in scientific publications is evident in other domains too, we might not be reaping the benefits. The tools to parse and combine this newly created knowledge have roughly remained the same for years.
Today, Mozilla Fellow Kostas Stathoulopoulos is launching Orion — an open-source tool to illuminate the science behind the science and accelerate knowledge discovery in the life sciences. Orion enables users to monitor progress in science, visually explore the scientific landscape, and search for relevant publications.
Orion collects, enriches and analyses scientific publications in the life sciences from Microsoft Academic Graph.
Users can leverage Orion’s views to interact with the data. The Exploration view shows all of the academic publications in a three-dimensional visualization. Every particle is a paper and the distance between them signifies their semantic similarity; the closer two particles are, the more semantically similar. The Metrics view visualizes indicators of scientific progress and how they have changed over time for countries and thematic topics. The Search view enables the users to search for publications by submitting either a keyword or a longer query, for example, a sentence or a paragraph of a blog they read online….(More)”.
Why Modeling the Spread of COVID-19 Is So Damn Hard
Matthew Hutson at IEEE Spectrum: “…Researchers say they’ve learned a lot of lessons modeling this pandemic, lessons that will carry over to the next.
The first set of lessons is all about data. Garbage in, garbage out, they say. Jarad Niemi, an associate professor of statistics at Iowa State University who helps run the forecast hub used by the CDC, says it’s not clear what we should be predicting. Infections, deaths, and hospitalization numbers each have problems, which affect their usefulness not only as inputs for the model but also as outputs. It’s hard to know the true number of infections when not everyone is tested. Deaths are easier to count, but they lag weeks behind infections. Hospitalization numbers have immense practical importance for planning, but not all hospitals release those figures. How useful is it to predict those numbers if you never have the true numbers for comparison? What we need, he said, is systematized random testing of the population, to provide clear statistics of both the number of people currently infected and the number of people who have antibodies against the virus, indicating recovery. Prakash, of Georgia Tech, says governments should collect and release data quickly in centralized locations. He also advocates for central repositories of policy decisions, so modelers can quickly see which areas are implementing which distancing measures.
Researchers also talked about the need for a diversity of models. At the most basic level, averaging an ensemble of forecasts improves reliability. More important, each type of model has its own uses—and pitfalls. An SEIR model is a relatively simple tool for making long-term forecasts, but the devil is in the details of its parameters: How do you set those to match real-world conditions now and into the future? Get them wrong and the model can head off into fantasyland. Data-driven models can make accurate short-term forecasts, and machine learning may be good for predicting complicated factors. But will the inscrutable computations of, for instance, a neural network remain reliable when conditions change? Agent-based models look ideal for simulating possible interventions to guide policy, but they’re a lot of work to build and tricky to calibrate.
Finally, researchers emphasize the need for agility. Niemi of Iowa State says software packages have made it easier to build models quickly, and the code-sharing site GitHub lets people share and compare their models. COVID-19 is giving modelers a chance to try out all their newest tools, says Meyers, of the University of Texas. “The pace of innovation, the pace of development, is unlike ever before,” she says. “There are new statistical methods, new kinds of data, new model structures.”…(More)”.
Public Sector Tech: New tools for the new normal
Special issue by ZDNet exploring “how new technologies like AI, cloud, drones, and 5G are helping government agencies, public organizations, and private companies respond to the events of today and tomorrow…:
- How data is making the EMS to emergency room hand-off easier
- What data tells us about first responders dealing with COVID-19 cases
- GE Healthcare and Microsoft partner to help hospitals fight COVID-19
- Running to the fight: How Verizon brought hospital ship USNS Comfort online to aid NYC COVID-19 response
- How AI and ML is helping first responders
- Startup uses network automation to help hospitals solve wi-fi problems
- How drones can augment first responders
- Cloud platform modernizes 911 system by adding location data, chat and video to emergency calls
- Microsoft is dedicating significant tech resources to COVID-19 first responder organizations
- How fire departments can extinguish money, space, and data loss with the cloud
- Samsung demos MCPTX video call on AWS
- Best security and surveillance drones for business in 2020: Impossible Aerospace, Microdrones, DJI, and more“
Exploring Digital Government Transformation in the EU – Understanding public sector innovation in a data-driven society
Report edited by Misuraca, G., Barcevičius, E. and Codagnone, C.: “This report presents the final results of the research “Exploring Digital Government Transformation in the EU: understanding public sector innovation in a data-driven society”, in short DigiGov. After introducing the design and methodology of the study, the report provides a summary of the findings of the comprehensive analysis of the state of the art in the field, conducted reviewing a vast body of scientific literature, policy documents and practitioners generated reports in a broad range of disciplines and policy domains, with a focus on the EU. The scope and key dimensions underlying the development of the DigiGov-F conceptual framework are then presented. This is a theory-informed heuristic instrument to help mapping the effects of Digital Government Transformation and able to support defining change strategies within the institutional settings of public administration. Further, the report provides an overview of the findings of the empirical case studies conducted, and employing experimental or quasi-experimental components, to test and refine the conceptual framework proposed, while gathering evidence on impacts of Digital Government Transformation, through identifying real-life drivers and barriers in diverse Member States and policy domains. The report concludes outlining future research and policy recommendations, as well as depicting possible scenarios for future Digital Government Transformation, developed as a result of a dedicated foresight policy lab. This was conducted as part of the expert consultation and stakeholder engagement process that accompanied all the phases of the research implementation. Insights generated from the study also serve to pave the way for further empirical research and policy experimentation, and to contribute to the policy debate on how to shape Digital Europe at the horizon 2040….(More)”.
Research 4.0: research in the age of automation
Report by Rob Procter, Ben Glover, and Elliot Jones: “There is a growing consensus that we are at the start of a fourth industrial revolution, driven by developments in Artificial Intelligence, machine learning, robotics, the Internet of Things, 3-D printing, nanotechnology, biotechnology, 5G, new forms of energy storage and quantum computing. This report seeks to understand what impact AI is having on the UK’s research sector and what implications it has for its future, with a particular focus on academic research.
Building on our interim report, we find that AI is increasingly deployed in academic research in the UK in a broad range of disciplines. The combination of an explosion of new digital data sources with powerful new analytical tools represents a ‘double dividend’ for researchers. This is allowing researchers to investigate questions that would have been unanswerable just a decade ago. Whilst there has been considerable take-up of AI in academic research, the report highlights that steps could be taken to ensure even wider adoption of these new techniques and technologies, including wider training in the necessary skills for effective utilisation of AI, faster routes to culture change and greater multi-disciplinary collaboration.
This report recognises that the Covid-19 pandemic means universities are currently facing significant pressures, with considerable demands on their resources whilst simultaneously facing threats to income. But as we emerge from the current crisis, we urge policy makers and universities to consider the report’s recommendations and take steps to fortify the UK’s position as a place of world-leading research. Indeed, the current crisis has only reminded us of the critical importance of a highly functioning and flourishing research sector. The report recommends:
The current post-16 curriculum should be reviewed to ensure all pupils receive a grounding in basic digital, quantitative and ethical skills necessary to ensure the effective and appropriate utilisation of AI.A UK-wide audit of research computing and data infrastructure provision is conducted to consider how access might be levelled up.
UK Research and Innovation (UKRI) should consider incentivising institutions to utilise AI wherever it can offer benefits to the economy and society in their future spending on research and development.
Universities should take steps to ensure that it is easier for researchers to move between academia and industry, for example, by putting less emphasis on publications, and recognise other outputs and measures of achievement when hiring for academic posts….(More)”.