Governance Level: national

Beyond Distrust: How Americans View Their Government

Curated on Posted on by Stefaan Verhulst

Overview - 1Pew Research Center: “A year ahead of the presidential election, the American public is deeply cynical about government, politics and the nation’s elected leaders in a way that has become quite familiar.

Currently, just 19% say they can trust the government always or most of the time,among the lowest levels in the past half-century. Only 20% would describe government programs as being well-run. And elected officials are held in such low regard that 55% of the public says “ordinary Americans” would do a better job of solving national problems.

Yet at the same time, most Americans have a lengthy to-do list for this object of their frustration: Majorities want the federal government to have a major role in addressing issues ranging from terrorism and disaster response to education and the environment.

And most Americans like the way the federal government handles many of these same issues, though they are broadly critical of its handling of others – especially poverty and immigration.

A new national survey by Pew Research Center, based on more than 6,000 interviews conducted between August 27 and October 4, 2015, finds that public attitudes about government and politics defy easy categorization. The study builds upon previous reports about the government’s role and performance in 2010 and 1998. This report was made possible by The Pew Charitable Trusts, which received support for the survey from The William and Flora Hewlett Foundation.

The partisan divide over the size and scope of government remains as wide as ever: Support for smaller government endures as a Republican touchstone. Fully 80% of Republicans and Republican-leaning independents say they prefer a smaller government with fewer services, compared with just 31% of Democrats and Democratic leaners.

Yet both Republicans and Democrats favor significant government involvement on an array of specific issues. Among the public overall, majorities say the federal government should have a major role in dealing with 12 of 13 issues included in the survey, all except advancing space exploration.

There is bipartisan agreement that the federal government should play a major role in dealing with terrorism, natural disasters, food and medicine safety, and roads and infrastructure. And while the presidential campaign has exposed sharp partisan divisions over immigration policy, large majorities of both Republicans (85%) and Democrats (80%) say the government should have a major role in managing the immigration system.

But the partisan differences over government’s appropriate role are revealing – with the widest gaps on several issues relating to the social safety net….(More)

Data enriched research, data enhanced impact: the importance of UK data infrastructure.

Curated on Posted on by Stefaan Verhulst

Matthew Woollard at LSE Impact Blog: “…Data made available for reuse, such as those in the UK Data Service collection have huge potential. They can unlock new discoveries in research, provide evidence for policy decisions and help promote core data skills in the next generation of researchers. By being part of a single infrastructure, data owners and data creators can work together with the UK Data Service – rather than duplicating efforts – to engage with the people who can drive the impact of their research further to provide real benefit to society. As a service we are also identifying new ways to understand and promote our impact, and our Impact Fellow and Director of Impact and Communications, Victoria Moody, is focusing on raising the visibility of the UK Data Service holdings and developing and promoting the use and impact of the data and resources in policy-relevant research, especially to new audiences such as policymakers, government sectors, charities, the private sector and the media…..

We are improving how we demonstrate the impact of both the Service and the data which we hold, by focusing on generating more and more authentic user corroboration. Our emphasis is on drawing together evidence about the reach and significance of the impact of our data and resources, and of the Service as a whole through our infrastructure and expertise. Headline impact indicators through which we will better understand our impact cover a range of areas (outlined above) where the Service brings efficiency to data access and re-use, benefit to its users and a financial and social return on investment.

We are working to understand more about how Service data contributes to impact by tracking the use of Service data in a range of initiatives focused on developing impact from research and by developing our insight into usage of our data by our users. Data in the collection have featured in a range of impact case studies in the Research Excellence Framework 2014. We are also developing a focus on understanding the specific beneficial effect, rather than simply that data were used in an output, that is – as it appears in policy, debate or the evidential process (although important). Early thoughts in developing this process are where (ideally) cited data can be tracked through the specific beneficial outcome and on to an evidenced effect, corroborated by the end user.

data service 1

Our impact case studies demonstrate how the data have supported research which has led to policy change in a range of areas including; the development of mathematical models for Practice based Commissioning budgets for adult mental health in the UK and informing public policy on obesity; both using the Health Survey for England. Service data have also informed the development of impact around understanding public attitudes towards the police and other legal institutions using the Crime Survey for England and Wales and research to support the development of the national minimum wage using the Labour Force Survey. The cutting-edge new Demos Integration Hub maps the changing face of Britain’s diversity, revealing a mixed picture in the integration and upward mobility of ethnic minority communities and uses 2011 Census aggregate data (England and Wales) and Understanding Society….(More)”

Open government data: Out of the box

Curated on Posted on by Stefaan Verhulst

The Economist on “The open-data revolution has not lived up to expectations. But it is only getting started…

The app that helped save Mr Rich’s leg is one of many that incorporate government data—in this case, supplied by four health agencies. Six years ago America became the first country to make all data collected by its government “open by default”, except for personal information and that related to national security. Almost 200,000 datasets from 170 outfits have been posted on the data.gov website. Nearly 70 other countries have also made their data available: mostly rich, well-governed ones, but also a few that are not, such as India (see chart). The Open Knowledge Foundation, a London-based group, reckons that over 1m datasets have been published on open-data portals using its CKAN software, developed in 2010.

Jakarta’s Participatory Budget

Curated on Posted on by Stefaan Verhulst

Ramda Yanurzha in GovInsider: “…This is a map of Musrenbang 2014 in Jakarta. Red is a no-go, green means the proposal is approved.

To give you a brief background, musrenbang is Indonesia’s flavor of participatory, bottom-up budgeting. The idea is that people can propose any development for their neighbourhood through a multi-stage budgeting process, thus actively participating in shaping the final budget for the city level, which will then determine the allocation for each city at the provincial level, and so on.

The catch is, I’m confident enough to say that not many people (especially in big cities) are actually aware of this process. While civic activists tirelessly lament that the process itself is neither inclusive nor transparent, I’m leaning towards a simpler explanation that most people simply couldn’t connect the dots.

People know that the public works agency fixed that 3-foot pothole last week. But it’s less clear how they can determine who is responsible for fixing a new streetlight in that dark alley and where the money comes from. Someone might have complain to the neighbourhood leader (Pak RT) and somehow the message gets through, but it’s very hard to trace how it got through. Just keep complaining to the black box until you don’t have to. There are very few people (mainly researchers) who get to see the whole picture.

This has now changed because the brand-new Jakarta open data portal provides musrenbang data from 2009. Who proposed what to whom, for how much, where it should be implemented (geotagged!), down to kelurahan/village level, and whether the proposal is accepted into the final city budget. For someone who advocates for better availability of open data in Indonesia and is eager to practice my data wrangling skill, it’s a goldmine.

Diving In

data screenshot
All the different units of goods proposed.

The data is also, as expected, incredibly messy. While surprisingly most of the projects proposed are geotagged, there are a lot of formatting inconsistencies that makes the clean up stage painful. Some of them are minor (m? meter? meter2? m2? meter persegi?) while others are perplexing (latitude: -6,547,843,512,000  –  yes, that’s a value of more than a billion). Annoyingly, hundreds of proposals point to the center of the National Monument so it’s not exactly a representative dataset.

For fellow data wranglers, pull requests to improve the data are gladly welcome over here. Ibam generously wrote an RT extractor to yield further location data, and I’m looking into OpenStreetMap RW boundary data to create a reverse geocoder for the points.

A couple hours of scrubbing in OpenRefine yields me a dataset that is clean enough for me to generate the CartoDB map I embedded at the beginning of this piece. More precisely, it is a map of geotagged projects where each point is colored depending on whether it’s rejected or accepted.

Numbers and Patterns

40,511 proposals, some of them merged into broader ones, which gives us a grand total of 26,364 projects valued at over IDR 3,852,162,060,205, just over $250 million at the current exchange rate. This amount represents over 5% of Jakarta’s annual budget for 2015, with projects ranging from a IDR 27,500 (~$2) trash bin (that doesn’t sound right, does it?) in Sumur Batu to IDR 54 billion, 1.5 kilometer drainage improvement in Koja….(More)”

How Big Data is Helping to Tackle Climate Change

Curated on Posted on by Stefaan Verhulst

Bernard Marr at DataInformed: “Climate scientists have been gathering a great deal of data for a long time, but analytics technology’s catching up is comparatively recent. Now that cloud, distributed storage, and massive amounts of processing power are affordable for almost everyone, those data sets are being put to use. On top of that, the growing number of Internet of Things devices we are carrying around are adding to the amount of data we are collecting. And the rise of social media means more and more people are reporting environmental data and uploading photos and videos of their environment, which also can be analyzed for clues.

Perhaps one of the most ambitious projects that employ big data to study the environment is Microsoft’s Madingley, which is being developed with the intention of creating a simulation of all life on Earth. The project already provides a working simulation of the global carbon cycle, and it is hoped that, eventually, everything from deforestation to animal migration, pollution, and overfishing will be modeled in a real-time “virtual biosphere.” Just a few years ago, the idea of a simulation of the entire planet’s ecosphere would have seemed like ridiculous, pie-in-the-sky thinking. But today it’s something into which one of the world’s biggest companies is pouring serious money. Microsoft is doing this because it believes that analytical technology has finally caught up with the ability to collect and store data.

Another data giant that is developing tools to facilitate analysis of climate and ecological data is EMC. Working with scientists at Acadia National Park in Maine, the company has developed platforms to pull in crowd-sourced data from citizen science portals such as eBird and iNaturalist. This allows park administrators to monitor the impact of climate change on wildlife populations as well as to plan and implement conservation strategies.

Last year, the United Nations, under its Global Pulse data analytics initiative, launched the Big Data Climate Challenge, a competition aimed to promote innovate data-driven climate change projects. Among the first to receive recognition under the program is Global Forest Watch, which combines satellite imagery, crowd-sourced witness accounts, and public datasets to track deforestation around the world, which is believed to be a leading man-made cause of climate change. The project has been promoted as a way for ethical businesses to ensure that their supply chain is not complicit in deforestation.

Other initiatives are targeted at a more personal level, for example by analyzing transit routes that could be used for individual journeys, using Google Maps, and making recommendations based on carbon emissions for each route.

The idea of “smart cities” is central to the concept of the Internet of Things – the idea that everyday objects and tools are becoming increasingly connected, interactive, and intelligent, and capable of communicating with each other independently of humans. Many of the ideas put forward by smart-city pioneers are grounded in climate awareness, such as reducing carbon dioxide emissions and energy waste across urban areas. Smart metering allows utility companies to increase or restrict the flow of electricity, gas, or water to reduce waste and ensure adequate supply at peak periods. Public transport can be efficiently planned to avoid wasted journeys and provide a reliable service that will encourage citizens to leave their cars at home.

These examples raise an important point: It’s apparent that data – big or small – can tell us if, how, and why climate change is happening. But, of course, this is only really valuable to us if it also can tell us what we can do about it. Some projects, such as Weathersafe, which helps coffee growers adapt to changing weather patterns and soil conditions, are designed to help humans deal with climate change. Others are designed to tackle the problem at the root, by highlighting the factors that cause it in the first place and showing us how we can change our behavior to minimize damage….(More)”

Building Trust and Protecting Privacy: Progress on the President’s Precision Medicine Initiative

Curated on Posted on by Stefaan Verhulst

The White House: “Today, the White House is releasing the Privacy and Trust Principles for the President’s Precision Medicine Initiative (PMI). These principles are a foundation for protecting participant privacy and building trust in activities within PMI.

PMI is a bold new research effort to transform how we characterize health and treat disease. PMI will pioneer a new model of patient-powered research that promises to accelerate biomedical discoveries and provide clinicians with new tools, knowledge, and therapies to select which treatments will work best for which patients. The initiative includes development of a new voluntary research cohort by the National Institutes of Health (NIH), a novel regulatory approach to genomic technologies by the Food and Drug Administration, and new cancer clinical trials by the National Cancer Institute at NIH.  In addition, PMI includes aligned efforts by the Federal government and private sector collaborators to pioneer a new approach for health research and healthcare delivery that prioritizes patient empowerment through access to information and policies that enable safe, effective, and innovative technologies to be tested and made available to the public.

Following President Obama’s launch of PMI in January 2015, the White House Office of Science and Technology Policy worked with an interagency group to develop the Privacy and Trust Principles that will guide the Precision Medicine effort. The White House convened experts from within and outside of government over the course of many months to discuss their individual viewpoints on the unique privacy challenges associated with large-scale health data collection, analysis, and sharing. This group reviewed the bioethics literature, analyzed privacy policies for large biobanks and research cohorts, and released a draft set of Principles for public comment in July 2015…..

The Privacy and Trust Principles are organized into 6 broad categories:

  1. Governance that is inclusive, collaborative, and adaptable;
  2. Transparency to participants and the public;
  3. Respecting participant preferences;
  4. Empowering participants through access to information;
  5. Ensuring appropriate data sharing, access, and use;
  6. Maintaining data quality and integrity….(More)”

Does Open Data Need Journalism?

Curated on Posted on by Stefaan Verhulst

Paper by Jonathan Stoneman at Reuters Institute for Journalism: “The Open Data movement really came into being when President Obama issued his first policy paper, on his first day in office in January 2009. The US government opened up thousands of datasets to scrutiny by the public, by journalists, by policy-makers. Coders and developers were also invited to make the data useful to people and businesses in all manner of ways. Other governments across the globe followed suit, opening up data to their populations.

Opening data in this way has not resulted in genuine openness, save in a few isolated cases. In the USA and a few European countries, developers have created apps and websites which draw on Open Data, but these are not reaching a mass audience.

At the same time, journalists are not seen by government as the end users of these data. Data releases, even in the best cases, are uneven, and slow, and do not meet the needs of journalists. Although thousands of journalists have been learning and adopting the new skills of datajournalism they have tended to work with data obtained through Freedom of Information (FOI) legislation.

Stories which have resulted from datajournalists’ efforts have rarely been front page news; in many cases data-driven stories have ended up as lesser stories on inside pages, or as infographics, which relatively few people look at.

In this context, therefore, Open Data remains outside the mainstream of journalism, and out of the consciousness of the electorate, begging the question, “what are Open Data for?”, or as one developer put it – “if Open Data is the answer, what was the question?” Openness is seen as a badge of honour – scores of national governments have signed pledges to make data open, often repeating the same kind of idealistic official language as the previous announcement of a conversion to openness. But these acts are “top down”, and soon run out of momentum, becoming simply openness for its own sake. Looking at specific examples, the United States is the nearest to a success story: there is a rich ecosystem – made up of government departments, interest groups and NGOs, the media, civil society – which allows data driven projects the space to grow and the airtime to make an impact. (It probably helped that the media in the US were facing an existential challenge urgent enough to force them to embrace new, inexpensive, ways of carrying out investigative reporting).

Elsewhere data are making less impact on journalism. In the UK the new openness is being exploited by a small minority. Where data are made published on the data.gov.uk website they are frequently out of date, incomplete, or of limited new value, so where data do drive stories, these tend to be data released under FOI legislation, and the resulting stories take the form of statistics and/or infographics.

In developing countries where Open Data Portals have been launched with a fanfare – such as Kenya, and more recently Burkina Faso – there has been little uptake by coders, journalists, or citizens, and the number of fresh datasets being published drops to a trickle, and are soon well out of date. Small, apparently randomly selected datasets are soon outdated and inertia sets in.

The British Conservative Party, pledging greater openness in its 2010 manifesto, foresaw armies of “Armchair Auditors” who would comb through the data and present the government with ideas for greater efficiency in the use of public funds. Almost needless to say, these armies have never materialised, and thousands of datasets go unscrutinised by anybody. 2 In countries like Britain large amounts of data are being published but going (probably) unread and unscrutinised by anybody. At the same time, the journalists who want to make use of data are getting what they need through FOI, or even by gathering data themselves. Open Data is thus being bypassed, and could become an irrelevance. Yet, the media could be vital agents in the quest for the release of meaningful, relevant, timely data.

Governments seem in no hurry to expand the “comfort zone” from which they release the data which shows their policies at their most effective, and keeping to themselves data which paints a gloomier picture. Journalists seem likely to remain in their comfort zone, where they make use of FOI and traditional sources of information. For their part, journalists should push for better data and use it more, working in collaboration with open data activists. They need to change the habits of a lifetime and discuss their sources: revealing the source and quality of data used in a story would in itself be as much a part of the advocacy as of the actual reporting.

If Open Data are to be part of a new system of democratic accountability, they need to be more than a gesture of openness. Nor should Open Data remain largely the preserve of companies using them for commercial purposes. Governments should improve the quality and relevance of published data, making them genuinely useful for journalists and citizens alike….(More)”

Government as a Platform: a historical and architectural analysis

Curated on Posted on by Stefaan Verhulst

Paper by Bendik Bygstad and Francis D’Silva: “A national administration is dependent on its archives and registers, for many purposes, such as tax collection, enforcement of law, economic governance, and welfare services. Today, these services are based on large digital infrastructures, which grow organically in volume and scope. Building on a critical realist approach we investigate a particularly successful infrastructure in Norway called Altinn, and ask: what are the evolutionary mechanisms for a successful “government as a platform”? We frame our study with two perspectives; a historical institutional perspective that traces the roots of Altinn back to the Middle Ages, and an architectural perspective that allows for a more detailed analysis of the consequences of digitalization and the role of platforms. We offer two insights from our study: we identify three evolutionary mechanisms of national registers, and we discuss a future scenario of government platforms as “digital commons”…(More)”

Robots Will Make Leeds the First Self-Repairing City

Curated on Posted on by Stefaan Verhulst

Emiko Jozuka at Motherboard: “Researchers in Britain want to make the first “self-repairing” city by 2035. How will they do this? By creating autonomous repair robots that patrol the streets and drainage systems, making sure your car doesn’t dip into a pothole, and that you don’t experience any gas leaks.

“The idea is to create a city that behaves almost like a living organism,” said Raul Fuentes, a researcher at the School of Civil Engineering at Leeds University, who is working on the project. “The robots will act like white cells that are able to identify bacteria or viruses and attack them. It’s kind of like an immune system.”

The £4.2 million ($6.4 million) national infrastructure project is in collaboration with Leeds City Council and the UK Collaboration for Research in Infrastructures and Cities (UKCRIC). The aim is to create a fleet of robot repair workers who will live in Leeds city, spot problems, and sort them out before they become even bigger ones by 2035, said Fuentes. The project is set to launch officially in January 2016, he added.

For their five-year project—which has a vision that extends until 2050—the researchers will develop robot designs and technologies that focus on three main areas. The first is to create drones that can perch on high structures and repair things like street lamps; the second is to develop drones that can autonomously spot when a pothole is about to form and zone in and patch that up before it worsens; and the third is to develop robots that will live in utility pipes so they can inspect, repair, and report back to humans when they spot an issue.

“The robots will be living permanently in the city, and they’ll be able to identify issues before they become real problems,” explained Fuentes. The researchers are working on making the robots autonomous, and want them to be living in swarms or packs where they can communicate with one another on how best they could get the repair job done….(More)

New flu tracker uses Google search data better than Google

Curated on Posted on by Stefaan Verhulst

 at ArsTechnica: “With big data comes big noise. Google learned this lesson the hard way with its now kaput Google Flu Trends. The online tracker, which used Internet search data to predict real-life flu outbreaks, emerged amid fanfare in 2008. Then it met a quiet death this August after repeatedly coughing up bad estimates.

But big Internet data isn’t out of the disease tracking scene yet.

With hubris firmly in check, a team of Harvard researchers have come up with a way to tame the unruly data, combine it with other data sets, and continually calibrate it to track flu outbreaks with less error. Their new model, published Monday in the Proceedings of the National Academy of Sciences, out-performs Google Flu Trends and other models with at least double the accuracy. If the model holds up in coming flu seasons, it could reinstate some optimism in using big data to monitor disease and herald a wave of more accurate second-generation models.

Big data has a lot of potential, Samuel Kou, a statistics professor at Harvard University and coauthor on the new study, told Ars. It’s just a question of using the right analytics, he said.

Kou and his colleagues built on Google’s flu tracking model for their new version, called ARGO (AutoRegression with GOogle search data). Google Flu Trends basically relied on trends in Internet search terms, such as headache and chills, to estimate the number of flu cases. Those search terms were correlated with flu outbreak data collected by the Centers for Disease Control and Prevention. The CDC’s data relies on clinical reports from around the country. But compiling and analyzing that data can be slow, leading to a lag time of one to three weeks. The Google data, on the other hand, offered near real-time tracking for health experts to manage and prepare for outbreaks.

At first Google’s tracker appeared to be pretty good, matching CDC data’s late-breaking data somewhat closely. But, two notable stumbles led to its ultimate downfall: an underestimate of the 2009 H1N1 swine flu outbreak and an alarming overestimate (almost double real numbers) of the 2012-2013 flu season’s cases…..For ARGO, he and colleagues took the trend data and then designed a model that could self-correct for changes in how people search. The model has a two-year sliding window in which it re-calibrates current search term trends with the CDC’s historical flu data (the gold standard for flu data). They also made sure to exclude winter search terms, such as March Madness and the Oscars, so they didn’t get accidentally correlated with seasonal flu trends. Last, they incorporated data on the historical seasonality of flu.

The result was a model that significantly out-competed the Google Flu Trends estimates for the period between March 29, 2009 to July 11, 2015. ARGO also beat out other models, including one based on current and historical CDC data….(More)”

See also Proceedings of the National Academy of Sciences, 2015. DOI: 10.1073/pnas.1515373112

Proudly powered by WordPress