national

A science that knows no country: Pandemic preparedness, global risk, sovereign science

Curated on February 14, 2018August 3, 2018 by Stefaan Verhulst

Paper by J. Benjamin Hurlbut: “… examines political norms and relationships associated with governance of pandemic risk. Through a pair of linked controversies over scientific access to H5N1 flu virus and genomic data, it examining the duties, obligations, and allocations of authority articulated around the imperative for globally free-flowing information and around the corollary imperative for a science that is set free to produce such information.

It argues that scientific regimes are laying claim to a kind of sovereignty, particularly in moments where scientific experts call into question the legitimacy of claims grounded in national sovereignty, by positioning the norms of scientific practice, including a commitment to unfettered access to scientific information and to the authority of science to declare what needs to be known, as essential to global governance. Scientific authority occupies a constitutional position insofar as it figures centrally in the repertoire of imaginaries that shape how a global community is imagined: what binds that community together and what shared political commitments, norms, and subjection to delegated authority are seen as necessary for it to be rightly governed….(More)”.

Building Trust in Data and Statistics

Curated on February 14, 2018August 3, 2018 by Stefaan Verhulst

Shaida Badiee at UN World Data Forum: …What do we want for a 2030 data ecosystem?

Hope to achieve: A world where data are part of the DNA and culture of decision-making, used by all and valued as an important public good. A world where citizens trust the systems that produce data and have the skills and means to use and verify their quality and accuracy. A world where there are safeguards in place to protect privacy, while bringing the benefits of open data to all. In this world, countries value their national statistical systems, which are working independently with trusted partners in the public and private sectors and citizens to continuously meet the changing and expanding demands from data users and policy makers. Private sector data generators are generously sharing their data with public sector. And gaps in data are closing, making the dream of “leaving no one behind” come true, with SDG goals on the path to being met by 2030.

Hope to avoid: A world where large corporations control the bulk of national and international data and statistics with only limited sharing with the public sector, academics, and citizens. The culture of every man for himself and who pays, wins, dominates data sharing practices. National statistical systems are under-resourced and under-valued, with low trust from users, further weakening them and undermining their independence from political interference and their ability to control quality. The divide between those who have and those who do not have access, skills, and the ability to use data for decision-making and policy has widened. Data systems and their promise to count the uncounted and “leave no one behind” are falling behind due to low capacity and poor standards and institutions, and the hope of the 2030 agenda is fading.

With this vision in mind, are we on the right path? An optimist would say we are closer to the data ecosystem that we want to achieve. However, there are also some examples of movement in the wrong direction. There is no magic wand to make our wish come true, but a powerful enabler would be building trust in data and statistics. Therefore, this should be included as a goal in all our data strategies and action plans.

Here are some important building blocks underlying trust in data and statistics:

Building strong organizational infrastructure, governance, and partnerships;
Following sound data standards and principles for production, sharing, interoperability, and dissemination; and
Addressing the last mile in the data value chain to meet users’ needs, create value with data, and ensure meaningful impacts…(More)”.

Is full transparency good for democracy?

Curated on February 8, 2018August 3, 2018 by Stefaan Verhulst

Austin Sarat at The Conversation: “Public knowledge about what government officials do is essential in a representative democracy. Without such knowledge, citizens cannot make informed choices about who they want to represent them or hold public officials accountable.

Political theorists have traced arguments about publicity and democracy back to ancient Greece and Rome. Those arguments subsequently flowered in the middle of the 19th century.

For example, writing about British parliamentary democracy, the famous philosopher Jeremy Bentham urged that legislative deliberation be carried out in public. Public deliberation, in his view, would be an important factor in “constraining the members of the assembly to perform their duty” and in securing “the confidence of the people.”

Moreover, Bentham noted that “suspicion always attaches to mystery.”

Even so, Bentham did not think the public had an unqualified “right to know.” As he put it, “It is not proper to make the law of publicity absolute.” Bentham acknowledged that publicity “ought to be suspended” when informing the public would “favor the projects of an enemy.”

Well into the 20th century, the U.S. and other democracies existed with far less public transparency than Bentham advocated.

Push for transparency

The authors of a 2016 U.S. Congressional report on access to government information observed that, “Throughout the first 150 years of the federal government, access to government information does not appear to have been a major issue for the federal branches or the public.” In short, the public generally did not demand more information than the government provided….

For at least the last 50 years, American legal and political institutions have tried to find a balance between publicity and secrecy. The courts have identified limits to claims of executive privilege like those made by President Nixon during Watergate. Watergate also led Congress in 1978 to pass the Foreign Intelligence Surveillance Act, or FISA. That act created a special court, whose procedures were highlighted in the Nunes memo. The FISA court authorizes collection of intelligence information between foreign powers and “agents of foreign powers.”

Finding the proper balance between making information public in order to foster accountability and the government’s concern for national security is not easy. Just look to the heated debates that accompanied passage of the Patriot Act and what WikiLeaks did in 2010 when it published more than 300,000 classified U.S. Army field reports.

Americans can make little progress in resolving such debates until they can get beyond the cynical, partisan use of slogans like “the public’s right to know” and “full transparency” by President Trump’s loyalists. Now more than ever, Americans must understand how and when transparency contributes to the strength and vitality of our democratic institutions and how and when the invocation of the public’s right to know is being used to erode them….(More)”.

Handbook on Participatory Governance

Curated on January 28, 2018August 3, 2018 by Stefaan Verhulst

Book edited by Hubert Heinelt: “Can participatory governance really improve the quality of democracy? Concentrating on democracy beyond governmental structures, this Handbook argues that it is a political task to engage individuals at all levels of governance.

The Handbook on Participatory Governance reveals that transforming governance arrangements does in fact enhance democracy and that the democratic quality of participatory governance is crucial. The contributors reflect on the notion of democracy and participatory governance and how they relate to each other. Case studies are presented from regional, national and international levels, to identify how governance can be turned into a participatory form. With chapters reviewing participatory governance’s role alongside power, science and employment relations, innovative ideas for future progress in participatory governance are presented….(More)”.

People Power

Curated on January 23, 2018August 3, 2018 by Stefaan Verhulst

Report from the Commission on the Future of Localism (UK): “…When we think about power we tend to look upwards – towards Westminster-based institutions and elected politicians. Those who wish to see greater localism often ask politicians to give it away and push power downwards. But this is looking at things the wrong way round. Instead, we need to start with the power of community. The task of our political system should be to support this, harness it, and reflect it in our national debate.

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Our Commission has heard evidence about what makes a powerful community. While different communities build and experience power in different ways, there are common sources. We heard how the power of any community lies with its people, their collective ideas, innovation, creativity and local knowledge, as well as their sense of belonging, connectedness and shared identity. We need to bring this into political life much more effectively via a renewed effort to foster localism in future.

However, our Commission has also heard about a fundamental imbalance of power that is preventing this power of community from coming to life and restricting collective agency: top-down decisions leaving community groups and local councils unable to make the change they know their neighbourhood needs; a lack of trust and risk aversion from public bodies, dampening community energy; a lack of control and access to local resources, limiting the scope of local action….(More)”.

StatCan now crowdsourcing cannabis data

Curated on January 23, 2018August 3, 2018 by Stefaan Verhulst

Kyle Duggan at iPolitics: “The national statistics agency is launching a crowdsourcing project to find out how much weed Canadians are consuming and how much it costs them.

Statistics Canada is searching for the best picture of consumption it can find ahead of legalization, and is turning to average Canadians to improve its rough estimates about a product that’s largely been accessed illegally by the population.

Thursday it released a suite of “experimental” data that make up its current best guesses on Canadian consumption habits, along with a crowdsourcing website and app to get its own estimates – a project officials said is an experiment itself.

Statscan is also rolling out a quarterly cannabis survey this year.

The agency has been combing through historical research on legal and illegal cannabis prices, scraping price data from illegal vendors online and, for some data, is relying largely on the self-reporting website priceofweed.com to assemble as much pot information as possible, even if it’s not perfect data.

The agency has been quietly preparing for the July legalization deadline by compiling health, justice and economic datasets and scouring to fill in the blanks where it can. Come July, legal cannabis will suddenly also need to be rolled into other important data products, like the GDP accounts….(More)”.

Congress Is Broken. CrowdLaw Could Help Fix It.

Curated on January 23, 2018August 3, 2018 by Stefaan Verhulst

Beth Noveck in Forbes: “The way Congress makes law is simply no longer viable. In David Schoenbrod’s recent book DC Confidential, he outlines “five tricks” politicians use to take credit in front of television cameras in order to further political party agendas while passing the blame and the buck to future generations for bad legislation. Although Congress makes the laws that govern all Americans, people also feel disenfranchised. One study concludes that “the preferences of the average American appear to have only a minuscule, near-zero, statistically non-significant impact upon public policy.” But technology offers the promise of improving both the quality and accountability of lawmaking by opening up the process to more and more diverse expertise and input from the public at every stage of the legislative process. We call such open and participatory lawmaking: “CrowdLaw.”

Moving Beyond the Ballot Box

Around the world, there are already over two dozen examples of local legislatures and national parliaments turning to the internet to improve the legitimacy and effectiveness of the laws they make; we need to do the same here if we are to begin to fix congressional dysfunction.

For example, Finland’s Citizen’s Initiative Act at the national level, like Madrid’s Decide initiative at the local level, allows any member of the public with the requisite signatures to propose new legislation, meaning that not only interest groups and politicians get to set the agenda for lawmaking.

In France, the Parlement & Citoyens platform allows the public to respond to a problem posed by a representative by contributing information about both causes and solutions. Relevant citizen input is then synthesized, debated, and incorporated into the resulting draft legislation. This brings greater empiricism into the legislative process through public contribution of expertise….(More)”.

They Are Watching You—and Everything Else on the Planet

Curated on January 23, 2018August 3, 2018 by Stefaan Verhulst

Cover article by Robert Draper for Special Issue of the National Geographic: “Technology and our increasing demand for security have put us all under surveillance. Is privacy becoming just a memory?…

In 1949, amid the specter of European authoritarianism, the British novelist George Orwell published his dystopian masterpiece 1984, with its grim admonition: “Big Brother is watching you.” As unsettling as this notion may have been, “watching” was a quaintly circumscribed undertaking back then. That very year, 1949, an American company released the first commercially available CCTV system. Two years later, in 1951, Kodak introduced its Brownie portable movie camera to an awestruck public.

Today more than 2.5 trillion images are shared or stored on the Internet annually—to say nothing of the billions more photographs and videos people keep to themselves. By 2020, one telecommunications company estimates, 6.1 billion people will have phones with picture-taking capabilities. Meanwhile, in a single year an estimated 106 million new surveillance cameras are sold. More than three million ATMs around the planet stare back at their customers. Tens of thousands of cameras known as automatic number plate recognition devices, or ANPRs, hover over roadways—to catch speeding motorists or parking violators but also, in the case of the United Kingdom, to track the comings and goings of suspected criminals. The untallied but growing number of people wearing body cameras now includes not just police but also hospital workers and others who aren’t law enforcement officers. Proliferating as well are personal monitoring devices—dash cams, cyclist helmet cameras to record collisions, doorbells equipped with lenses to catch package thieves—that are fast becoming a part of many a city dweller’s everyday arsenal. Even less quantifiable, but far more vexing, are the billions of images of unsuspecting citizens captured by facial-recognition technology and stored in law enforcement and private-sector databases over which our control is practically nonexistent.

Those are merely the “watching” devices that we’re capable of seeing. Presently the skies are cluttered with drones—2.5 million of which were purchased in 2016 by American hobbyists and businesses. That figure doesn’t include the fleet of unmanned aerial vehicles used by the U.S. government not only to bomb terrorists in Yemen but also to help stop illegal immigrants entering from Mexico, monitor hurricane flooding in Texas, and catch cattle thieves in North Dakota. Nor does it include the many thousands of airborne spying devices employed by other countries—among them Russia, China, Iran, and North Korea.

We’re being watched from the heavens as well. More than 1,700 satellites monitor our planet. From a distance of about 300 miles, some of them can discern a herd of buffalo or the stages of a forest fire. From outer space, a camera clicks and a detailed image of the block where we work can be acquired by a total stranger….

This is—to lift the title from another British futurist, Aldous Huxley—our brave new world. That we can see it coming is cold comfort since, as Carnegie Mellon University professor of information technology Alessandro Acquisti says, “in the cat-and-mouse game of privacy protection, the data subject is always the weaker side of the game.” Simply submitting to the game is a dispiriting proposition. But to actively seek to protect one’s privacy can be even more demoralizing. University of Texas American studies professor Randolph Lewis writes in his new book, Under Surveillance: Being Watched in Modern America, “Surveillance is often exhausting to those who really feel its undertow: it overwhelms with its constant badgering, its omnipresent mysteries, its endless tabulations of movements, purchases, potentialities.”

The desire for privacy, Acquisti says, “is a universal trait among humans, across cultures and across time. You find evidence of it in ancient Rome, ancient Greece, in the Bible, in the Quran. What’s worrisome is that if all of us at an individual level suffer from the loss of privacy, society as a whole may realize its value only after we’ve lost it for good.”…(More)”.

Extracting crowd intelligence from pervasive and social big data

Curated on January 20, 2018August 3, 2018 by Stefaan Verhulst

Introduction by Leye Wang, Vincent Gauthier, Guanling Chen and Luis Moreira-Matias of Special Issue of the Journal of Ambient Intelligence and Humanized Computing: “With the prevalence of ubiquitous computing devices (smartphones, wearable devices, etc.) and social network services (Facebook, Twitter, etc.), humans are generating massive digital traces continuously in their daily life. Considering the invaluable crowd intelligence residing in these pervasive and social big data, a spectrum of opportunities is emerging to enable promising smart applications for easing individual life, increasing company profit, as well as facilitating city development. However, the nature of big data also poses fundamental challenges on the techniques and applications relying on the pervasive and social big data from multiple perspectives such as algorithm effectiveness, computation speed, energy efficiency, user privacy, server security, data heterogeneity and system scalability. This special issue presents the state-of-the-art research achievements in addressing these challenges. After the rigorous review process of reviewers and guest editors, eight papers were accepted as follows.

The first paper “Automated recognition of hypertension through overnight continuous HRV monitoring” by Ni et al. proposes a non-invasive way to differentiate hypertension patients from healthy people with the pervasive sensors such as a waist belt. To this end, the authors train a machine learning model based on the heart rate data sensed from waists worn by a crowd of people, and the experiments show that the detection accuracy is around 93%.

The second paper “The workforce analyzer: group discovery among LinkedIn public profiles” by Dai et al. describes two users’ group discovery methods among LinkedIn public profiles. One is based on K-means and another is based on SVM. The authors contrast results of both methods and provide insights about the trending professional orientations of the workforce from an online perspective.

The third paper “Tweet and followee personalized recommendations based on knowledge graphs” by Pla Karidi et al. present an efficient semantic recommendation method that helps users filter the Twitter stream for interesting content. The foundation of this method is a knowledge graph that can represent all user topics of interest as a variety of concepts, objects, events, persons, entities, locations and the relations between them. An important advantage of the authors’ method is that it reduces the effects of problems such as over-recommendation and over-specialization.

The fourth paper “CrowdTravel: scenic spot profiling by using heterogeneous crowdsourced data” by Guo et al. proposes CrowdTravel, a multi-source social media data fusion approach for multi-aspect tourism information perception, which can provide travelling assistance for tourists by crowd intelligence mining. Experiments over a dataset of several popular scenic spots in Beijing and Xi’an, China, indicate that the authors’ approach attains fine-grained characterization for the scenic spots and delivers excellent performance.

The fifth paper “Internet of Things based activity surveillance of defence personnel” by Bhatia et al. presents a comprehensive IoT-based framework for analyzing national integrity of defence personnel with consideration to his/her daily activities. Specifically, Integrity Index Value is defined for every defence personnel based on different social engagements, and activities for detecting the vulnerability to national security. In addition to this, a probabilistic decision tree based automated decision making is presented to aid defence officials in analyzing various activities of a defence personnel for his/her integrity assessment.

The sixth paper “Recommending property with short days-on-market for estate agency” by Mou et al. proposes an estate with short days-on-market appraisal framework to automatically recommend those estates using transaction data and profile information crawled from websites. Both the spatial and temporal characteristics of an estate are integrated into the framework. The results show that the proposed framework can estimate accurately about 78% estates.

The seventh paper “An anonymous data reporting strategy with ensuring incentives for mobile crowd-sensing” by Li et al. proposes a system and a strategy to ensure anonymous data reporting while ensuring incentives simultaneously. The proposed protocol is arranged in five stages that mainly leverage three concepts: (1) slot reservation based on shuffle, (2) data submission based on bulk transfer and multi-player dc-nets, and (3) incentive mechanism based on blind signature.

The last paper “Semantic place prediction from crowd-sensed mobile phone data” by Celik et al. semantically classifes places visited by smart phone users utilizing the data collected from sensors and wireless interfaces available on the phones as well as phone usage patterns, such as battery level, and time-related information, with machine learning algorithms. For this study, the authors collect data from 15 participants at Galatasaray University for 1 month, and try different classification algorithms such as decision tree, random forest, k-nearest neighbour, naive Bayes, and multi-layer perceptron….(More)”.