Pigeon patrol takes flight to tackle London’s air pollution crisis

Curated on Posted on by Stefaan Verhulst

 at The Guardian: They’ve been driven from Trafalgar square for being a nuisance, derided as rats with wings and maligned as a risk to public health.

But now pigeons could play a small part in helping Londoners overcome one of the capital’s biggest health problems – its illegal levels of air pollution blamed for thousands of deaths a year.

On Monday, a flock of half a dozen racing pigeons were set loose from a rooftop in Brick Lane by pigeon fancier, Brian Woodhouse, with one strapped with a pollution sensor to its back and one with a GPS tracker.

But while the 25g sensor records the nitrogen dioxide produced by the city’s diesel cars, buses, and trucks and tweets it at anyone who asks for a reading, its real purpose – and the use of the pigeons – is to raise awareness.

“It is a scandal. It is a health and environmental scandal for humans – and pigeons. We’re making the invisible visible,” said Pierre Duquesnoy, who won a London Design Festival award for the idea last year.

“Most of the time when we talk about pollution people think about Beijing or other places, but there are some days in the year when pollution was higher and more toxic in London than Beijing, that’s the reality.”

He said he was inspired by the use of pigeons in the first and second world wars to deliver information and save lives, but they were also a practical way of taking mobile air quality readings and beating London’s congested roads. They fly relatively low, at 100-150ft, and fast, at speeds up to 80mph.

“There’s something about taking what is seen as a flying rat and reversing that into something quite positive,” said Duquesnoy, who is creative director at marketing agency DigitasLBI.

Gary Fuller, an air quality expert at King’s College London, said it was the first time he had heard of urban animals being put to such use.

“It’s great that unemployed pigeons from Trafalgar Square are being put to work. Around 15 years ago tests were done on around 150 stray dogs in Mexico City, showing the ways in which air pollution was affecting lungs and heart health. But this is the first time that I’ve heard of urban wild animals being used to carry sensors to give us a picture of the air pollution over our heads.”

The release of the pigeons for three days this week, dubbed the Pigeon Air Patrol, came as moderate to high pollution affected much of the city, with Battersea recording ‘very high’, the top of the scale.

Elsewhere in the UK, Stockton-on-tees and Middlesbrough recorded high pollution readings and the forecast is for moderate and possibly high pollution in urban areas in northern England and Scotland on Tuesday. Other areas will have low pollution levels….(More).

Cities, Data, and Digital Innovation

Curated on Posted on by Stefaan Verhulst

Paper by Mark Kleinman: “Developments in digital innovation and the availability of large-scale data sets create opportunities for new economic activities and new ways of delivering city services while raising concerns about privacy. This paper defines the terms Big Data, Open Data, Open Government, and Smart Cities and uses two case studies – London (U.K.) and Toronto – to examine questions about using data to drive economic growth, improve the accountability of government to citizens, and offer more digitally enabled services. The paper notes that London has been one of a handful of cities at the forefront of the Open Data movement and has been successful in developing its high-tech sector, although it has so far been less innovative in the use of “smart city” technology to improve services and lower costs. Toronto has also made efforts to harness data, although it is behind London in promoting Open Data. Moreover, although Toronto has many assets that could contribute to innovation and economic growth, including a growing high-technology sector, world-class universities and research base, and its role as a leading financial centre, it lacks a clear narrative about how these assets could be used to promote the city. The paper draws some general conclusions about the links between data innovation and economic growth, and between open data and open government, as well as ways to use big data and technological innovation to ensure greater efficiency in the provision of city services…(More)“

The 4 Types of Cities and How to Prepare Them for the Future

Curated on Posted on by Stefaan Verhulst

John D. Macomber at Harvard Business Review: “The prospect of urban innovation excites the imagination. But dreaming up what a “smart city” will look like in some gleaming future is, by its nature, a utopian exercise. The messy truth is that cities are not the same, and even the most innovative approach can never achieve universal impact. What’s appealing for intellectuals in Copenhagen or Amsterdam is unlikely to help millions of workers in Jakarta or Lagos. To really make a difference, private entrepreneurs and civic entrepreneurs need to match projects to specific circumstances. An effective starting point is to break cities into four segments across two distinctions: legacy vs. new cities, and developed vs. emerging economies. The opportunities to innovate will differ greatly by segment.

Segment 1: Developed Economy, Legacy City
Examples: London, Detroit, Tokyo, Singapore

Characteristics: Any intervention in a legacy city has to dismantle something that existed before — a road or building, or even a regulatory authority or an entrenched service business. Slow demographic growth in developed economies creates a zero-sum situation (which is part of why the licensed cabs vs Uber/Lyft contest is so heated). Elites live in these cities, so solutions arise that primarily help users spend their excess cash. Yelp, Zillow, and Trip Advisor are examples of innovations in this context.
Implications for city leaders: Leaders should try to establish a setting where entrepreneurs can create solutions that improve quality of life — without added government expense. …

Implications for entrepreneurs: Denizens of developed legacy cities have discretionary income. …

Segment 2: Emerging Economy, Legacy City
Examples: Mumbai, São Paolo, Jakarta

Characteristics: Most physical and institutional structures are already in place in these megacities, but with fast-growing populations and severe congestion, there is an opportunity to create value by improving efficiency and livability, and there is a market of customers with cash to pay for these benefits.

Implications for city leaders: Leaders should loosen restrictions so that private finance can invest in improvements to physical infrastructure, to better use what already exists. …

Implications for entrepreneurs: Focus on public-private partnerships (PPP). …

Segment 3: Emerging Economy, New City
Examples: Phu My Hung, Vietnam; Suzhou, China; Astana, Kazakhstan; Singapore (historically)

Characteristics: These cities tend to have high population growth and high growth rates in GDP per capita, demographic and economic tailwinds that help to boost returns. The urban areas have few existing physical or social structures to dismantle as they grow, hence fewer entrenched obstacles to new offerings. There is also immediate ROI for investments in basic services as population moves in, because they capture new revenues from new users. Finally, in these cities there is an important chance to build it right the first time, notably with respect to the roads, bridges, water, and power that will determine both economic competitiveness and quality of life for decades. The downside? If this chance is missed, new urban agglomerations will be characterized by informal sprawl and new settlements will be hard to reach after the fact with power, roads, and sanitation.
Implications for city leaders: Leaders should first focus on building hard infrastructure that will support services such as schools, hospitals, and parks. …

Implications for entrepreneurs: In these cities, it’s too soon to think about optimizing existing infrastructure or establishing amusing ways for wealthy people to spend their disposable income. …

Segment 4: Developed Economy, New City
Examples and characteristics: Such cities are very rare. All the moment, almost all self-proclaimed “new cities” in the developed world are in fact large, integrated real-estate developments with an urban theme, usually in close proximity to a true municipality. Examples of these initiatives include New Songdo City in South Korea, Masdar City in Abu Dhabi, and Hafen City Hamburg in Germany.

Implications for city leaders: These satellites of existing metropolises compete for jobs and to attract talented participants in the creative economy. ….

Implications for entrepreneurs: Align with city leaders on services that are important to knowledge workers, and help build the cities’ brand. ….

Cities are different. So are solutions….(More)

Letting the people decide … but will government listen?

Curated on Posted on by Stefaan Verhulst

 in The Mandarin: “If we now have the technology to allow citizens to vote directly on all issues, what job remains for public servants?

While new technology may provide new options to contribute, the really important thing is governmental willingness to actually listen, says Maria Katsonis, the Victorian Department of Premier and Cabinet’s director of equality.

The balance between citizen consultation and public service expertise in decision-making remains a hot debate, with South Australian Premier Jay Weatherill warning last year that while expertise in policy is important, overzealous bureaucrats and politicians can disenfranchise citizens.

The internet is assisting government to attain opinions from people more easily than ever before. SA, for example, has embraced the use of citizen juries in policy formation through its youSAy portal — though as yet on only some issues. Finland has experimented with digitally crowdsourcing input into the policymaking process.

The Victorian government, meanwhile, has received blowback around claims its recent announcement for a “skyrail” in Melbourne’s south-eastern suburbs went ahead with very little consultation…

Indeed, even a direct vote doesn’t mean the government is really listening to the people. A notable example of a government using a poorly designed popular vote to rubber stamp its own intentions was an online poll in Queensland on whether to cut public transport fares which was worded to suit the government’s own predilections.

Giving citizens the tools to contribute

Katsonis said she didn’t want to “diss crowdsourcing”; governments should think about where using it might be appropriate, and where it might not. Directly crowdsourcing legislation is perhaps not the best way to use the “wisdom of the crowd”, she suggested….The use of people’s panels to inform policy and budgeting — for example at the City of Melbourne — shows some promise as one tool to improve engagement. Participants of people’s panels — which see groups of ordinary citizens being given background information about the task at hand and then asked to come up with a proposal for what to do — tend to report a higher trust in governmental processes after they’ve gained some experience of the difficulty of making those decisions.

One of the benefits of that system is the chance to give participants the tools to understand those processes for themselves, rather than going in cold, as some other direct participation tools do….

Despite the risks, processes such as citizens’ panels are still a more nuanced approach than calls for frequent referenda or the new breed of internet-based political parties, such as Australia’s Online Direct Democracy, that promise their members of parliament will vote however a majority of voters tell them to….(More)”

Open data and (15 million!) new measures of democracy

Curated on Posted on by Stefaan Verhulst

Joshua Tucker in the Washington Post: “Last month the University of Gothenberg’s V-Dem Institute released a new“Varieties of Democracy” dataset. It provides about 15 million data points on democracy, including 39 democracy-related indices. It can be accessed at v-dem.net along with supporting documentation. I asked Staffan I. Lindberg, Director of the V-Dem Institute and one of the directors of the project, a few questions about the new data. What follows is a lightly edited version of his answers.


Women’s Political Empowerment Index for Southeast Asia (Data: V-Dem data version 5; Figure V-Dem Institute, University of Gothenberg, Sweden)

Joshua Tucker: What is democracy, and is it even really to have quantitative measures on democracy?

Staffan Lindberg: There is no consensus on the definition of democracy and how to measure it. The understanding of what a democracy really is varies across countries and regions. This motivates the V-Dem approach not to offer one standard definition of the concept but instead to distinguish among five principles different versions of democracy: Electoral, Liberal, Participatory, Deliberative, and Egalitarian democracy. All of these principles have played prominent roles in current and historical discussions about democracy. Our measurement of these principles are based on two types of data, factual data collected by assisting researchers and survey responses by country experts, which are combined using a rather complex measurement model (which is a“custom-designed Bayesian ordinal item response theory model”, for details see the V-Dem Methodology document)….(More)

Big data’s big role in humanitarian aid

Curated on Posted on by Stefaan Verhulst

Mary K. Pratt at Computerworld: “Hundreds of thousands of refugees streamed into Europe in 2015 from Syria and other Middle Eastern countries. Some estimates put the number at nearly a million.

The sheer volume of people overwhelmed European officials, who not only had to handle the volatile politics stemming from the crisis, but also had to find food, shelter and other necessities for the migrants.

Sweden, like many of its European Union counterparts, was taking in refugees. The Swedish Migration Board, which usually sees 2,500 asylum seekers in an average month, was accepting 10,000 per week.

“As you can imagine, with that number, it requires a lot of buses, food, registration capabilities to start processing all the cases and to accommodate all of those people,” says Andres Delgado, head of operational control, coordination and analysis at the Swedish Migration Board.

Despite the dramatic spike in refugees coming into the country, the migration agency managed the intake — hiring extra staff, starting the process of procuring housing early, getting supplies ready. Delgado credits a good part of that success to his agency’s use of big data and analytics that let him predict, with a high degree of accuracy, what was heading his way.

“Without having that capability, or looking at the tool every day, to assess every need, this would have crushed us. We wouldn’t have survived this,” Delgado says. “It would have been chaos, actually — nothing short of that.”

The Swedish Migration Board has been using big data and analytics for several years, as it seeks to gain visibility into immigration trends and what those trends will mean for the country…./…

“Can big data give us peace? I think the short answer is we’re starting to explore that. We’re at the very early stages, where there are shining examples of little things here and there. But we’re on that road,” says Kalev H. Leetaru, creator of the GDELT Project, or the Global Database of Events, Language and Tone, which describes itself as a comprehensive “database of human society.”

The topic is gaining traction. A 2013 report, “New Technology and the Prevention of Violence and Conflict,” from the International Peace Institute, highlights uses of telecommunications technology, including data, in several crisis situations around the world. The report emphasizes the potential these technologies hold in helping to ease tensions and address problems.

The report’s conclusion offers this idea: “Big data can be used to identify patterns and signatures associated with conflict — and those associated with peace — presenting huge opportunities for better-informed efforts to prevent violence and conflict.”

That’s welcome news to Noel Dickover. He’s the director of PeaceTech Data Networks at the PeaceTech Lab, which was created by the U.S. Institute of Peace (USIP) to advance USIP’s work on how technology, media and data help reduce violent conflict around the world.

Such work is still in the nascent stages, Dickover says, but people are excited about its potential. “We have unprecedented amounts of data on human sentiment, and we know there’s value there,” he says. “The question is how to connect it.”

Dickover is working on ways to do just that. One example is the Open Situation Room Exchange (OSRx) project, which aims to “empower greater collective impact in preventing or mitigating serious violent conflicts in particular arenas through collaboration and data-sharing.”…(More)

Open Data Is Changing the World in Four Ways…

Curated on Posted on by Stefaan Verhulst

 at The GovLab Blog: “New repository of case studies documents the impact of open data globally: odimpact.org.

odimpact-tweet-3

Despite global commitments to and increasing enthusiasm for open data, little is actually known about its use and impact. What kinds of social and economic transformation has open data brought about, and what is its future potential? How—and under what circumstances—has it been most effective? How have open data practitioners mitigated risks and maximized social good?

Even as proponents of open data extol its virtues, the field continues to suffer from a paucity of empiricalevidence. This limits our understanding of open data and its impact.

Over the last few months, The GovLab (@thegovlab), in collaboration with Omidyar Network(@OmidyarNetwork), has worked to address these shortcomings by developing 19 detailed open data case studies from around the world. The case studies have been selected for their sectoral and geographic representativeness. They are built in part from secondary sources (“desk research”), and also from more than60 first-hand interviews with important players and key stakeholders. In a related collaboration withOmidyar Network, Becky Hogge(@barefoot_techie), an independent researcher, has developed an additional six open data case studies, all focused on the United Kingdom.  Together, these case studies, seek to provide a more nuanced understanding of the various processes and factors underlying the demand, supply, release, use and impact of open data.

Today, after receiving and integrating comments from dozens of peer reviewers through a unique open process, we are delighted to share an initial batch of 10 case studies, as well three of Hogge’s UK-based stories. These are being made available at a new custom-built repository, Open Data’s Impact (http://odimpact.org), that will eventually house all the case studies, key findings across the studies, and additional resources related to the impact of open data. All this information will be stored in machine-readable HTML and PDF format, and will be searchable by area of impact, sector and region….(More)

Big-data analytics: the power of prediction

Curated on Posted on by Stefaan Verhulst

Rachel Willcox in Public Finance: “The ability to anticipate demands will improve planning and financial efficiency, and collecting and analysing data will enable the public sector to look ahead…

Hospitals around the country are well accustomed to huge annual rises in patient numbers as winter demand hits accident and emergency departments. But Wrightington, Wigan and Leigh NHS Foundation Trust (WWL) had to rethink service planning after unprecedented A&E demand during a sunny July 2014, which saw ambulances queuing outside the hospital. The trust now employs computer analysis to help predict and prepare for peaks in demand.

As public sector organisations grapple with ever-tighter savings targets, analysis of a broad range of historical data – big data analytics – offers an opportunity to pre-empt service requirements and so help the public sector manage demand more effectively and target scarce resources better. However, working with data to gain insight and save money is not without its challenges.

At WWL, a partnership with business support provider NHS Shared Business Services – a 50:50 joint venture between the Department of Health and technology firm Sopra Steria – resulted in a project that uses an analysis of historical data and complex algorithms to predict the most likely scenarios. In September, the partners launched HealthIntell, a suite of data reporting tools for A&E, procurement and finance.

The suite includes an application designed to help hospitals better cope with A&E pressures and meet waiting time targets. HealthIntell presents real-time data on attendances at A&E departments to doctors and other decision makers. It can predict demand on a daily and hourly basis, and allows trusts to use their own data to identify peaks and troughs – for example, the likely rise in attendances due to bad weather or major sporting events – to help deploy the right people with the right expertise at the right time….

Rikke Duus, a senior teaching fellow at University College London’s School of Management, agrees strongly that an evidence-based approach to providing services is key to efficiency gains, using data that is already available. Although the use of big data across the public sector is trailing well behind that in the private sector, pressure is mounting for it to catch up. Consumers’ experiences with private sector organisations – in particular the growing personalisation of services – is raising expectations about the sort of public services people expect to receive.

Transparency, openness and integration can benefit consumers, Duus says. “It’s about reinventing the business model to cut costs and improve efficiency. We have to use data to predict and prevent. The public-sector mindset is getting there and the huge repositories of data held across the public sector offer a great starting point, but often they don’t know how to get into it and skills are an issue,” Duus says.

Burgeoning demand for analytics expertise in retail, banking and finance has created a severe skills shortage that is allowing big-data professionals to command an average salary of £55,000 – 31% higher than the average IT position, according to a report published in November 2014 by the Tech Partnership employers’ network and business analytics company SAS. More than three quarters of posts were considered “fairly” or “very” difficult to fill, and the situation is unlikely to have eased in the interim.

Professor Robert Fildes, director of the Lancaster Centre for Forecasting, part of Lancaster University Management School, warns that public sector organisations are at a distinct disadvantage when it comes to competing for such sought-after skills.

The centre has worked on a number of public sector forecasting projects, including a Department of Health initiative to predict pay drift for its non-medical workforce and a scheme commissioned by NHS Blackpool to forecast patient activity.

“The other constraint is data,” Fildes observes. “People talk about data as if it is a uniform value. But the Department of Health doesn’t have any real data on the demand for, say, hip operations. They only have data on the operations they’ve done. The data required for analysis isn’t good enough,” he says….

Despite the challenges, projects are reaping rewards across a variety of public sector organisations. Since 2008, the London Fire Brigade (LFB) has been using software from SAS to prioritise the allocation of fire prevention resources, even pinpointing specific households most at risk of fire. The software brings together around 60 data inputs including demographic information, geographical locations, historical data, land use and deprivation levels to create lifestyle profiles for London households.

Deaths caused by fire in the capital fell by almost 50% between 2010 and 2015, according to the LFB. It attributes much of the reduction to better targeting of around 90,000 home visits the brigade carries out each year, to advise on fire safety….(More)”

 

Understanding Participatory Governance

Curated on Posted on by Stefaan Verhulst

An analysis of “Participants’ Motives for Participation” by Per Gustafson and Nils Hertting: “Despite the growing body of literature on participatory and collaborative governance, little is known about citizens’ motives for participation in such new governance arrangements. The present article argues that knowledge about these motives is essential for understanding the quality and nature of participatory governance and its potential contribution to the overall political and administrative system.

Survey data were used to explore participants’ motives for participating in a large-scale urban renewal program in Stockholm, Sweden. The program was neighborhood-based, characterized by self-selected and repeated participation, and designed to influence local decisions on the use of public resources.

Three types of motives were identified among the participants: (a) Common good motives concerned improving the neighborhood in general and contributing knowledge and competence. (b) Self-interest motives reflected a desire to improve one’s own political efficacy and to promote the interest of one’s own group or family. (c) Professional competence motives represented a largely apolitical type of motive, often based on a professional role. Different motives were expressed by different categories of participants and were also associated with different perceptions concerning program outcomes.

Further analysis suggested that participatory governance may represent both an opportunity for marginalized groups to empower themselves and an opportunity for more privileged groups to act as local “citizen representatives” and articulate the interests of their neighborhoods. These findings call for a more complex understanding of the role and potential benefits of participatory governance…(More).”

 

Core Concepts: Computational social science

Curated on Posted on by Stefaan Verhulst

Adam Mann at PNAS: “Cell phone tower data predicts which parts of London can expect a spike in crime (1). Google searches for polling place information on the day of an election reveal the consequences of different voter registration laws (2). Mathematical models explain how interactions among financial investors produce better yields, and even how they generate economic bubbles (3).

Figure

Using cell-phone and taxi GPS data, researchers classified people in San Francisco into “tribal networks,” clustering them according to their behavioral patterns. Student’s, tourists, and businesspeople all travel through the city in various ways, congregating and socializing in different neighborhoods. Image courtesy of Alex Pentland (Massachusetts Institute of Technology, Cambridge, MA).

Figure

Where people hail from in the Mexico City area, here indicated by different colors, feeds into a crime-prediction model devised by Alex Pentland and colleagues (6). Image courtesy of Alex Pentland (Massachusetts Institute of Technology, Cambridge, MA).

 These are just a few examples of how a suite of technologies is helping bring sociology, political science, and economics into the digital age. Such social science fields have historically relied on interviews and survey data, as well as censuses and other government databases, to answer important questions about human behavior. These tools often produce results based on individuals—showing, for example, that a wealthy, well-educated, white person is statistically more likely to vote (4)—but struggle to deal with complex situations involving the interactions of many different people.

 

A growing field called “computational social science” is now using digital tools to analyze the rich and interactive lives we lead. The discipline uses powerful computer simulations of networks, data collected from cell phones and online social networks, and online experiments involving hundreds of thousands of individuals to answer questions that were previously impossible to investigate. Humans are fundamentally social creatures and these new tools and huge datasets are giving social scientists insights into exactly how connections among people create societal trends or heretofore undetected patterns, related to everything from crime to economic fortunes to political persuasions. Although the field provides powerful ways to study the world, it’s an ongoing challenge to ensure that researchers collect and store the requisite information safely, and that they and others use that information ethically….(More)”