Putri, D.A., CH Karlina, M., Tanaya, J., at the Centre for Innovation Policy and Governance, Indonesia: “In 2011, Indonesia started its Open Government journey when along with seven other countries it initiated Open Government Partnership. Following the global declaration, Indonesia launched the Open Government Indonesia (OGI) in January 2012 with the aim to introduce open government reforms, including open data. This initiative is supported by Law No. 14/2008 on Freedom of Information. Despite its early stage, the implementation of Open Government in Indonesia has shown promising developments, with three action plans enacted in the last four years. In the Southeast Asian region, Indonesia could be considered a pioneer in implementing the open data initiative at national as well as sub-national levels. In some cases, the open data initiative at sub- national level has even surpassed the progress at the national level. Jakarta, for example, became the first city to have its own gubernatorial bylaw on data and system management, which requires the city administration and agencies to open its public data, thus leading to the birth of open data initiatives in the city. The city also have Jakarta Smart City that connect sub-districts officials with the citizen. Jakarta Smart City is an initiative that promote openness of the government through public service delivery. This paper aims to take a closer look on the dynamics of citizens-generated data in Jakarta and how Jakarta smart city program contributes to the implementation of open data….(More)”
Global Indicators of Regulatory Governance
Worldbank: “The Global Indicators of Regulatory Governance project is an initiative of the World Bank’sGlobal Indicators Group, which produces a range of datasets and benchmarking products on regulations and business activity around the world. These datasets include Doing Business,Enterprise Surveys, Enabling the Business of Agriculture and Women, Business and the Law.
The Global Indicators of Regulatory Governance project explores how governments interact with the public when shaping regulations that affect their business community. Concerned stakeholders could be professional associations, civic groups or foreign investors. The project charts how interested groups learn about new regulations being considered, and the extent to which they are able to engage with officials on the content. It also measures whether or not governments assess the possible impact of new regulations in their countries (including economic, social and environmental considerations) and whether those calculations form part of the public consultation. Finally, Global Indicators of Regulatory Governance capture two additional components of a predictable regulatory environment: the ability of stakeholders to challenge regulations, and the ability of people to access all the laws and regulations currently in force in one, consolidated place.
The project grew out of an increasing recognition of the importance of transparency and accountability in government actions. Citizen access to the government rulemaking process is central for the creation of a business environment in which investors make long-range plans and investments. Greater levels of consultation are also associated with a higher quality of regulation…(More) ( View project summary (PDF, 190KB)”
Mapping Momentum
Report by Rachel Sinha and Tim Draimin:”As we hurtle towards a human community of 9.7 billion people by the year 2050, coupled with new technologies and the growing challenges of our planet’s carrying capacity, there is more and more discussion of systems and how they change or are created. The post-war era has witnessed an unprecedented growth of global, national and regional systems but systemic challenges like climate change and inequality are undermining the viability and resilience of our 20th century systems.
It’s against this backdrop that a movement is starting to gain traction. A community of practitioners trying to shift incumbent systems no longer fit for purpose and build new ones that work for our current reality.
But this field is nascent and largely unsupported. In this publication, we have created two maps designed to shine a light on the work of this group of pioneers. We offer these with the hypothesis that the field will be better able to organize itself if it can see itself more clearly. Our theory of change? A clearer picture leads to greater connectivity, connectivity leads to stronger networks, and accelerates the best initiatives we so badly need if we are to effectively shift systems….(More)”
Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction
New book by Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller & Steven Goldfeder: “Bitcoin and Cryptocurrency Technologies provides a comprehensive introduction to the revolutionary yet often misunderstood new technologies of digital currency. Whether you are a student, software developer, tech entrepreneur, or researcher in computer science, this authoritative and self-contained book tells you everything you need to know about the new global money for the Internet age.
How do Bitcoin and its block chain actually work? How secure are your bitcoins? How anonymous are their users? Can cryptocurrencies be regulated? These are some of the many questions this book answers. It begins by tracing the history and development of Bitcoin and cryptocurrencies, and then gives the conceptual and practical foundations you need to engineer secure software that interacts with the Bitcoin network as well as to integrate ideas from Bitcoin into your own projects. Topics include decentralization, mining, the politics of Bitcoin, altcoins and the cryptocurrency ecosystem, the future of Bitcoin, and more.
- An essential introduction to the new technologies of digital currency
- Covers the history and mechanics of Bitcoin and the block chain, security, decentralization, anonymity, politics and regulation, altcoins, and much more
- Features an accompanying website that includes instructional videos for each chapter, homework problems, programming assignments, and lecture slides…(More)”.
See also: Coursera course
Can mobile usage predict illiteracy in a developing country?
Pål Sundsøy at arXiv: “The present study provides the first evidence that illiteracy can be reliably predicted from standard mobile phone logs. By deriving a broad set of mobile phone indicators reflecting users financial, social and mobility patterns we show how supervised machine learning can be used to predict individual illiteracy in an Asian developing country, externally validated against a large-scale survey. On average the model performs 10 times better than random guessing with a 70% accuracy. Further we show how individual illiteracy can be aggregated and mapped geographically at cell tower resolution. Geographical mapping of illiteracy is crucial to know where the illiterate people are, and where to put in resources. In underdeveloped countries such mappings are often based on out-dated household surveys with low spatial and temporal resolution. One in five people worldwide struggle with illiteracy, and it is estimated that illiteracy costs the global economy more than 1 trillion dollars each year. These results potentially enable cost-effective, questionnaire-free investigation of illiteracy-related questions on an unprecedented scale…(More)”.
Designing an Active, Healthier City
Meera Senthilingam in the New York Times: “Despite a firm reputation for being walkers, New Yorkers have an obesity epidemic on their hands. Lee Altman, a former employee of New York City’s Department of Design and Construction, explains it this way: “We did a very good job at designing physical activity out of our daily lives.”
According to the city’s health department, more than half of the city’s adult population is either overweight (34 percent) or obese (22 percent), and the convenience of their environment has contributed to this. “Everything is dependent on a car, elevator; you sit in front of a computer,” said Altman, “not moving around a lot.”
This is not just a New York phenomenon. Mass urbanization has caused populations the world over to reduce the amount of time they spend moving their bodies. But the root of the problem runs deep in a city’s infrastructure.
Safety, graffiti, proximity to a park, and even the appeal of stairwells all play roles in whether someone chooses to be active or not. But only recently have urban developers begun giving enough priority to these factors.
Planners in New York have now begun employing a method known as “active design” to solve the problem. The approach is part of a global movement to get urbanites onto their streets and enjoying their surroundings on foot, bike or public transport.
“We can impact public health and improve health outcomes through the way that we design,” said Altman, a former active design coordinator for New York City. She now lectures as an adjunct assistant professor inColumbia University’s urban design program.
“The communities that have the least access to well-maintained sidewalks and parks have the highest risk of obesity and chronic disease,” said Joanna Frank, executive director of the nonprofit Center for Active Design; her work focuses on creating guidelines and reports, so that developers and planners are aware, for example, that people have been “less likely to walk down streets, less likely to bike, if they didn’t feel safe, or if the infrastructure wasn’t complete, so you couldn’t get to your destination.”
Even adding items as straightforward as benches and lighting to a streetscape can greatly increase the likelihood of someone’s choosing to walk, she said.
This may seem obvious, but without evidence its importance could be overlooked. “We’ve now established that’s actually the case,” said Frank.
How can things change? According to Frank, four areas are critical: transportation, recreation, buildings and access to food….(More)”
Data at the Speed of Life
Marc Gunther at The Chronicle of Philanthropy: “Can pregnant women in Zambia be persuaded to deliver their babies in hospitals or clinics rather than at home? How much are villagers in Cambodia willing to pay for a simple latrine? What qualities predict success for a small-scale entrepreneur who advises farmers?
Governments, foundations, and nonprofits that want to help the world’s poor regularly face questions like these. Answers are elusive. While an estimated $135 billion in government aid and another $15 billion in charitable giving flow annually to developing countries, surprisingly few projects benefit from rigorous evaluations. Those that do get scrutinized in academic studies often don’t see the results for years, long after the projects have ended.
IDinsight puts data-driven research on speed. Its goal is to produce useful, low-cost research results fast enough that nonprofits can use it make midcourse corrections to their programs….
IDinsight calls this kind of research “decision-focused evaluation,” which sets it apart from traditional monitoring and evaluation (M&E) and academic research. M&E, experts say, is mostly about accountability and outputs — how many training sessions were held, how much food was distributed, and so on. Usually, it occurs after a program is complete. Academic studies are typically shaped by researchers’ desire to break new ground and publish on topics of broad interest. The IDinsight approach aims instead “for contemporaneous decision-making rather than for publication in the American Economic Review,” says Ruth Levine, who directs the global development program at the William and Flora Hewlett Foundation.
A decade ago, Ms. Levine and William Savedoff, a senior fellow at the Center for Global Development, wrote an influential paper entitled “When Will We Ever Learn? Improving Lives Through Impact Evaluation.” They lamented that an “absence of evidence” for the effectiveness of global development programs “not only wastes money but denies poor people crucial support to improve their lives.”
Since then, impact evaluation has come a “huge distance,” Ms. Levine says….
Actually, others are. Innovations for Poverty Action recently created the Goldilocks Initiative to do what it calls “right fit” evaluations leading to better policy and programs, according to Thoai Ngo, who leads the effort. Its first clients include GiveDirectly, which facilitates cash transfers to the extreme poor, and Splash, a water charity….All this focus on data has generated pushback. Many nonprofits don’t have the resources to do rigorous research, according to Debra Allcock Tyler, chief executive at Directory of Social Change, a British charity that provides training, data, and other resources for social enterprises.
All this focus on data has generated pushback. Many nonprofits don’t have the resources to do rigorous research, according to Debra Allcock Tyler, chief executive at Directory of Social Change, a British charity that provides training, data, and other resources for social enterprises.
“A great deal of the time, data is pointless,” Allcock Tyler said last year at a London seminar on data and nonprofits. “Very often it is dangerous and can be used against us, and sometimes it takes away precious resources from other things that we might more usefully do.”
A bigger problem may be that the accumulation of knowledge does not necessarily lead to better policies or practices.
“People often trust their experience more than a systematic review,” says Ms. Levine of the Hewlett Foundation. IDinsight’s Esther Wang agrees. “A lot of our frustration is looking at the development world and asking why are we not accountable for the money that we are spending,” she says. “That’s a waste that none of us really feels is justifiable.”…(More)”
Research in the Crowdsourcing Age, a Case Study
Report by Paul Hitlin (Pew): “How scholars, companies and workers are using Mechanical Turk, a ‘gig economy’ platform, for tasks computers can’t handle
Digital age platforms are providing researchers the ability to outsource portions of their work – not just to increasingly intelligent machines, but also to a relatively low-cost online labor force comprised of humans. These so-called “online outsourcing” services help employers connect with a global pool of free-agent workers who are willing to complete a variety of specialized or repetitive tasks.
Because it provides access to large numbers of workers at relatively low cost, online outsourcing holds a particular appeal for academics and nonprofit research organizations – many of whom have limited resources compared with corporate America. For instance, Pew Research Center has experimented with using these services to perform tasks such as classifying documents and collecting website URLs. And a Google search of scholarly academic literature shows that more than 800 studies – ranging from medical research to social science – were published using data from one such platform, Amazon’s Mechanical Turk, in 2015 alone.1
The rise of these platforms has also generated considerable commentary about the so-called “gig economy” and the possible impact it will have on traditional notions about the nature of work, the structure of compensation and the “social contract” between firms and workers. Pew Research Center recently explored some of the policy and employment implications of these new platforms in a national survey of Americans.
Proponents say this technology-driven innovation can offer employers – whether companies or academics – the ability to control costs by relying on a global workforce that is available 24 hours a day to perform relatively inexpensive tasks. They also argue that these arrangements offer workers the flexibility to work when and where they want to. On the other hand, some critics worry this type of arrangement does not give employees the same type of protections offered in more traditional work environments – while others have raised concerns about the quality and consistency of data collected in this manner.
A recent report from the World Bank found that the online outsourcing industry generated roughly $2 billion in 2013 and involved 48 million registered workers (though only 10% of them were considered “active”). By 2020, the report predicted, the industry will generate between $15 billion and $25 billion.
Amazon’s Mechanical Turk is one of the largest outsourcing platforms in the United States and has become particularly popular in the social science research community as a way to conduct inexpensive surveys and experiments. The platform has also become an emblem of the way that the internet enables new businesses and social structures to arise.
In light of its widespread use by the research community and overall prominence within the emerging world of online outsourcing, Pew Research Center conducted a detailed case study examining the Mechanical Turk platform in late 2015 and early 2016. The study utilizes three different research methodologies to examine various aspects of the Mechanical Turk ecosystem. These include human content analysis of the platform, a canvassing of Mechanical Turk workers and an analysis of third party data.
The first goal of this research was to understand who uses the Mechanical Turk platform for research or business purposes, why they use it and who completes the work assignments posted there. To evaluate these issues, Pew Research Center performed a content analysis of the tasks posted on the site during the week of Dec. 7-11, 2015.
A second goal was to examine the demographics and experiences of the workers who complete the tasks appearing on the site. This is relevant not just to fellow researchers that might be interested in using the platform, but as a snapshot of one set of “gig economy” workers. To address these questions, Pew Research Center administered a nonprobability online survey of Turkers from Feb. 9-25, 2016, by posting a task on Mechanical Turk that rewarded workers for answering questions about their demographics and work habits. The sample of 3,370 workers contains any number of interesting findings, but it has its limits. This canvassing emerges from an opt-in sample of those who were active on MTurk during this particular period, who saw our survey and who had the time and interest to respond. It does not represent all active Turkers in this period or, more broadly, all workers on MTurk.
Finally, this report uses data collected by the online tool mturk-tracker, which is run by Dr. Panagiotis G. Ipeirotis of the New York University Stern School of Business, to examine the amount of activity occurring on the site. The mturk-tracker data are publically available online, though the insights presented here have not been previously published elsewhere….(More)”
Postal big data: Global flows as proxy indicators for national wellbeing
Data Driven Journalism: “A new project has developed an innovative means to approximate socioeconomic indicators by analyzing the network of international postal flows.
The project used 14 million aggregated electronic postal records from 187 countries collected by the Universal Postal Union over a four-year period (2010-2014) to create an international network showing the way post flows around the world.
In addition, the project builds upon previous research efforts using global flow networks, derived from the five following open data sources:
- World Trade Network available from the MIT Atlas Project
- Global Migration Network available from the Global Migration Project
- IP Traceroute Network available from the DIMES Project
- Digital Communications Network available from the Mesh of Civilizations Project
- Flight Network data available from ICAO
For each network, a country’s degree of connectivity for incoming and outgoing flows was quantified using the Jaccard coefficient and Spearman’s rank correlation coefficient….
To understand these connections in the context of socioeconomic indicators, the researchers then compared these positions to the values of GDP, Life expectancy, Corruption Perception Index, Internet penetration rate, Happiness index, Gini index, Economic Complexity Index, Literacy, Poverty, CO2 emissions, Fixed phone line penetration, Mobile phone users, and the Human Development Index.
Image: Spearman rank correlations between global flow network degrees and socioeconomic indicators (CC BY 4.0).
From this analysis, the researchers revealed that:
- The best-performing degree, in terms of consistently high performance across indicators is the global degree, suggesting that looking at how well connected a country is in the global multiplex can be more indicative of its socioeconomic profile as a whole than looking at single networks.
- GDP per capita and life expectancy are most closely correlated with the global degree, closely followed by the postal, trade and IP weighed degrees – indicative of a relationship between national wealth and the flow of goods and information.
- Similarly to GDP, the rate of poverty of a country is best represented by the global degree, followed by the postal degree. The negative correlation indicates that the more impoverished a country is, the less well connected it is to the rest of the world.
- Low human development (high rank) is most highly negatively correlated with the global degree, followed by the postal, trade and IP degrees. This shows that high human development (low rank) is associated with high global connectivity and activity in terms of incoming and outgoing flows of information and goods. ….Read the fully study here.”
Bridging data gaps for policymaking: crowdsourcing and big data for development
Anthony Swan for the DevPolicyBlog: “…By far the biggest innovation in data collection is the ability to access and analyse (in a meaningful way) user-generated data. This is data that is generated from forums, blogs, and social networking sites, where users purposefully contribute information and content in a public way, but also from everyday activities that inadvertently or passively provide data to those that are able to collect it.
User-generated data can help identify user views and behaviour to inform policy in a timely way rather than just relying on traditional data collection techniques (census, household surveys, stakeholder forums, focus groups, etc.), which are often cumbersome, very costly, untimely, and in many cases require some form of approval or support by government.
It might seem at first that user-generated data has limited usefulness in a development context due to the importance of the internet in generating this data combined with limited internet availability in many places. However, U-Report is one example of being able to access user-generated data independent of the internet.
U-Report was initiated by UNICEF Uganda in 2011 and is a free SMS based platform where Ugandans are able to register as “U-Reporters” and on a weekly basis give their views on topical issues (mostly related to health, education, and access to social services) or participate in opinion polls. As an example, Figure 1 shows the result from a U-Report poll on whether polio vaccinators came to U-Reporter houses to immunise all children under 5 in Uganda, broken down by districts. Presently, there are more than 300,000 U-Reporters in Uganda and more than one million U-Reporters across 24 countries that now have U-Report. As an indication of its potential impact on policymaking,UNICEF claims that every Member of Parliament in Uganda is signed up to receive U-Report statistics.
Figure 1: U-Report Uganda poll results
U-Report and other platforms such as Ushahidi (which supports, for example, I PAID A BRIBE, Watertracker, election monitoring, and crowdmapping) facilitate crowdsourcing of data where users contribute data for a specific purpose. In contrast, “big data” is a broader concept because the purpose of using the data is generally independent of the reasons why the data was generated in the first place.
Big data for development is a new phrase that we will probably hear a lot more (see here [pdf] and here). The United Nations Global Pulse, for example, supports a number of innovation labs which work on projects that aim to discover new ways in which data can help better decision-making. Many forms of “big data” are unstructured (free-form and text-based rather than table- or spreadsheet-based) and so a number of analytical techniques are required to make sense of the data before it can be used.
Measures of Twitter activity, for example, can be a real-time indicator of food price crises in Indonesia [pdf] (see Figure 2 below which shows the relationship between food-related tweet volume and food inflation: note that the large volume of tweets in the grey highlighted area is associated with policy debate on cutting the fuel subsidy rate) or provide a better understanding of the drivers of immunisation awareness. In these examples, researchers “text-mine” Twitter feeds by extracting tweets related to topics of interest and categorising text based on measures of sentiment (positive, negative, anger, joy, confusion, etc.) to better understand opinions and how they relate to the topic of interest. For example, Figure 3 shows the sentiment of tweets related to vaccination in Kenya over time and the dates of important vaccination related events.
Figure 2: Plot of monthly food-related tweet volume and official food price statistics
Figure 3: Sentiment of vaccine related tweets in Kenya
Another big data example is the use of mobile phone usage to monitor the movement of populations in Senegal in 2013. The data can help to identify changes in the mobility patterns of vulnerable population groups and thereby provide an early warning system to inform humanitarian response effort.
The development of mobile banking too offers the potential for the generation of a staggering amount of data relevant for development research and informing policy decisions. However, it also highlights the public good nature of data collected by public and private sector institutions and the reliance that researchers have on them to access the data. Building trust and a reputation for being able to manage privacy and commercial issues will be a major challenge for researchers in this regard….(More)”