Nepal Aid Workers Helped by Drones, Crowdsourcing


Shirley Wang et al in the Wall Street Journal: “….It is too early to gauge the exact impact of the technology in Nepal relief efforts, which have just begun amid chaos on the ground. Aid organizations have reported hospitals are overstretched, a shortage of capacity at Katmandu’s airport is crippling aid distribution and damaged roads and the mountainous country’s difficult terrain make reaching villages difficult.

Still, technology is playing an increasing role in the global response to humanitarian crises. Within hours of Saturday’s 7.8-magnitude temblor, U.S. giants such as Google Inc. and Facebook Inc. were offering their networks for use in verifying survivors and helping worried friends and relatives locate their loved ones.

Advances in online mapping—long used to calculate distances and plot driving routes—and the ability of camera-equipped drones are playing an increasingly important role in coordinating emergency responses at ground zero of any disaster.

A community of nonprofit groups uses satellite images, private images and open-source mapping technology to remap areas affected by the earthquake. They mark damaged buildings and roads so rescuers can identify the worst-hit areas and assess how accessible different areas are. The technology complements more traditional intelligence from aircraft.

Such crowdsourced real-time mapping technologies were first used in the 2010 Haiti earthquake, according to Chris Grundy, a professor in Geographical Information Systems at the London School of Hygiene and Tropical Medicine. The technology “has been advancing a little bit every time [every situation where it is used] as we start to see what works,” said Prof. Grundy.

The American Red Cross supplied its relief team on the Wednesday night flight to Nepal from Washington, D.C. with 50 digital maps and an inch-thick pile of paper maps that help identify where the needs are. The charity has a mapping project with the British Red Cross, Doctors Without Borders and the Humanitarian OpenStreetMap Team, a crowdsourced data-sharing group.

Almost a week after the Nepal earthquake, two more people have been pulled from the rubble in Katmandu by teams of international rescuers. But hope for finding more survivors is waning. Photo: Sean McLain/The Wall Street Journal.

Mapping efforts have grown substantially since Haiti, according to Dale Kunce, head of the geographic information systems team at the American Red Cross. In the two months after the Haiti temblor, 600 mapping contributors made 1.5 million edits, while in the first 48 hours after the Nepal earthquake, 2,000 mappers had already made three million edits, Mr. Kunce said.

Some 3,400 volunteers from around the world are now inspecting images of Nepal online to identify road networks and conditions, to assess the extent of damage and pinpoint open spaces where displaced persons tend to congregate, according to Nama Budhathoki, executive director of a nonprofit technology company called Katmandu Living Labs.

His group is operating from a cramped but largely undamaged meeting room in a central-Katmandu office building to help coordinate the global effort of various mapping organizations with the needs of agencies like Doctors Without Borders and the international Red Cross community.

In recent days the Nepal Red Cross and Nepalese army have requested and been supplied with updated maps of severely damaged districts, said Dr. Budhathoki….(More)”

Five Headlines from a Big Month for the Data Revolution


Sarah T. Lucas at Post2015.org: “If the history of the data revolution were written today, it would include three major dates. May 2013, when theHigh Level Panel on the Post-2015 Development Agenda first coined the phrase “data revolution.” November 2014, when the UN Secretary-General’s Independent Expert Advisory Group (IEAG) set a vision for it. And April 2015, when five headliner stories pushed the data revolution from great idea to a concrete roadmap for action.

The April 2015 Data Revolution Headlines

1. The African Data Consensus puts Africa in the lead on bringing the data revolution to the regional level. TheAfrica Data Consensus (ADC) envisions “a profound shift in the way that data is harnessed to impact on development decision-making, with a particular emphasis on building a culture of usage.” The ADC finds consensus across 15 “data communities”—ranging from open data to official statistics to geospatial data, and is endorsed by Africa’s ministers of finance. The ADC gets top billing in my book, as the first contribution that truly reflects a large diversity of voices and creates a political hook for action. (Stay tuned for a blog from my colleague Rachel Quint on the ADC).

2. The Sustainable Development Solutions Network (SDSN) gets our minds (and wallets) around the data needed to measure the SDGs. The SDSN Needs Assessment for SDG Monitoring and Statistical Capacity Development maps the investments needed to improve official statistics. My favorite parts are the clear typology of data (see pg. 12), and that the authors are very open about the methods, assumptions, and leaps of faith they had to take in the costing exercise. They also start an important discussion about how advances in information and communications technology, satellite imagery, and other new technologies have the potential to expand coverage, increase analytic capacity, and reduce the cost of data systems.

3. The Overseas Development Institute (ODI) calls on us to find the “missing millions.” ODI’s The Data Revolution: Finding the Missing Millions presents the stark reality of data gaps and what they mean for understanding and addressing development challenges. The authors highlight that even that most fundamental of measures—of poverty levels—could be understated by as much as a quarter. And that’s just the beginning. The report also pushes us to think beyond the costs of data, and focus on how much good data can save. With examples of data lowering the cost of doing government business, the authors remind us to think about data as an investment with real economic and social returns.

4. Paris21 offers a roadmap for putting national statistic offices (NSOs) at the heart of the data revolution.Paris21’s Roadmap for a Country-Led Data Revolution does not mince words. It calls on the data revolution to “turn a vicious cycle of [NSO] underperformance and inadequate resources into a virtuous one where increased demand leads to improved performance and an increase in resources and capacity.” It makes the case for why NSOs are central and need more support, while also pushing them to modernize, innovate, and open up. The roadmap gets my vote for best design. This ain’t your grandfather’s statistics report!

5. The Cartagena Data Festival features real-live data heroes and fosters new partnerships. The Festival featured data innovators (such as terra-i using satellite data to track deforestation), NSOs on the leading edge of modernization and reform (such as Colombia and the Philippines), traditional actors using old data in new ways (such as the Inter-American Development Bank’s fantastic energy database), groups focused on citizen-generated data (such as The Data Shift and UN My World), private firms working with big data for social good (such asTelefónica), and many others—all reminding us that the data revolution is well underway and will not be stopped. Most importantly, it brought these actors together in one place. You could see the sparks flying as folks learned from each other and hatched plans together. The Festival gets my vote for best conference of a lifetime, with the perfect blend of substantive sessions, intense debate, learning, inspiration, new connections, and a lot of fun. (Stay tuned for a post from my colleague Kristen Stelljes and me for more on Cartagena).

This month full of headlines leaves no room for doubt—momentum is building fast on the data revolution. And just in time.

With the Financing for Development (FFD) conference in Addis Ababa in July, the agreement of Sustainable Development Goals in New York in September, and the Climate Summit in Paris in December, this is a big political year for global development. Data revolutionaries must seize this moment to push past vision, past roadmaps, to actual action and results…..(More)”

These researchers want to turn phones into earthquake detectors


Russell Brandom in TheVerge: “Early warning on earthquakes can help save lives, but many countries can’t afford them. That’s why scientists are turning to another location sensor already widespread in many countries: the smartphone. A single smartphone makes for a crappy earthquake sensor — but get enough of them reporting, and it won’t matter.

A new study, published today in Science Advances, says that the right network of cell phones might be able to substitute for modern seismograph arrays, providing a crucial early warning in the event of a quake. The study looks at historical earthquake data and modern smartphone hardware (based on the Nexus 5) and comes away with a map of how a smartphone-based earthquake detector might work. As it turns out, a phone’s GPS is more powerful than you might think.

A modern phone has almost everything you could want in an earthquake sensor

Early warning systems are designed to pick up the first tremors of an earthquake, projecting where the incoming quake is centered and how strong it’s likely to be. When they work, the systems are able to give citizens and first responders crucial time to prepare for the quake. There are already seismograph-based systems in place in California, Mexico, and Japan, but poorer countries often don’t have the means to implement and maintain them. This new method wouldn’t be as good as most scientific earthquake sensors, but those can cost tens of thousands of dollars each, making a smartphone-based sensor a lot cheaper. For countries that can’t afford a seismograph-based system (which includes much of the Southern Hemisphere), it could make a crucial difference in catching quakes early.

A modern phone has almost everything you could want in an earthquake sensor: specifically, a GPS-powered location sensor, an accelerometer, and multiple data connections. There are also a lot of them, even in poor countries, so a distributed system could count on getting data points from multiple angles….(More)”

New surveys reveal dynamism, challenges of open data-driven businesses in developing countries


Alla Morrison at World Bank Open Data blog: “Was there a class of entrepreneurs emerging to take advantage of the economic possibilities offered by open data, were investors keen to back such companies, were governments tuned to and responsive to the demands of such companies, and what were some of the key financing challenges and opportunities in emerging markets? As we began our work on the concept of an Open Fund, we partnered with Ennovent (India), MDIF (East Asia and Latin America) and Digital Data Divide (Africa) to conduct short market surveys to answer these questions, with a focus on trying to understand whether a financing gap truly existed in these markets. The studies were fairly quick (4-6 weeks) and reached only a small number of companies (193 in India, 70 in Latin America, 63 in South East Asia, and 41 in Africa – and not everybody responded) but the findings were fairly consistent.

  • Open data is still a very nascent concept in emerging markets. and there’s only a small class of entrepreneurs/investors that is aware of the economic possibilities; there’s a lot of work to do in the ‘enabling environment’
    • In many regions the distinction between open data, big data, and private sector generated/scraped/collected data was blurry at best among entrepreneurs and investors (some of our findings consequently are better indicators of  data-driven rather than open data-driven businesses)
  • There’s a small but growing number of open data-driven companies in all the markets we surveyed and these companies target a wide range of consumers/users and are active in multiple sectors
    • A large percentage of identified companies operate in sectors with high social impact – health and wellness, environment, agriculture, transport. For instance, in India, after excluding business analytics companies, a third of data companies seeking financing are in healthcare and a fifth in food and agriculture, and some of them have the low-income population or the rural segment of India as an intended beneficiary segment. In Latin America, the number of companies in business services, research and analytics was closely followed by health, environment and agriculture. In Southeast Asia, business, consumer services, and transport came out in the lead.
    • We found the highest number of companies in Latin America and Asia with the following countries leading the way – Mexico, Chile, and Brazil, with Colombia and Argentina closely behind in Latin America; and India, Indonesia, Philippines, and Malaysia in Asia
  • An actionable pipeline of data-driven companies exists in Latin America and in Asia
    • We heard demand for different kinds of financing (equity, debt, working capital) but the majority of the need was for equity and quasi-equity in amounts ranging from $100,000 to $5 million USD, with averages of between $2 and $3 million USD depending on the region.
  • There’s a significant financing gap in all the markets
    • The investment sizes required, while they range up to several million dollars, are generally small. Analysis of more than 300 data companies in Latin America and Asia indicates a total estimated need for financing of more than $400 million
  • Venture capitals generally don’t recognize data as a separate sector and club data-driven companies with their standard information communication technology (ICT) investments
    • Interviews with founders suggest that moving beyond seed stage is particularly difficult for data-driven startups. While many companies are able to cobble together an initial seed round augmented by bootstrapping to get their idea off the ground, they face a great deal of difficulty when trying to raise a second, larger seed round or Series A investment.
    • From the perspective of startups, investors favor banal e-commerce (e.g., according toTech in Asia, out of the $645 million in technology investments made public across the region in 2013, 92% were related to fashion and online retail) or consumer service startups and ignore open data-focused startups even if they have a strong business model and solid key performance indicators. The space is ripe for a long-term investor with a generous risk appetite and multiple bottom line goals.
  • Poor data quality was the number one issue these companies reported.
    • Companies reported significant waste and inefficiency in accessing/scraping/cleaning data.

The analysis below borrows heavily from the work done by the partners. We should of course mention that the findings are provisional and should not be considered authoritative (please see the section on methodology for more details)….(More).”

Bloomberg Philanthropies Launches $100 Million Data for Health Program in Developing Countries


Press Release: “Bloomberg Philanthropies, in partnership with the Australian government, is launching Data for Health, a $100 million initiative that will enable 20 low- and middle-income countries to vastly improve public health data collection.  Each year the World Health Organization estimates that 65% of all deaths worldwide – 35 million each year – go unrecorded. Millions more deaths lack a documented cause. This gap in data creates major obstacles for understanding and addressing public health problems. The Data for Health initiative seeks to provide governments, aid organizations, and public health leaders with tools and systems to better collect data – and use it to prioritize health challenges, develop policies, deploy resources, and measure success. Over the next four years, Data for Health aims to help 1.2 billion people in 20 countries across Africa, Asia, and Latin America live healthier, longer lives….

“Australia’s partnership on Data for Health coincides with the launch of innovationXchange, a new initiative to embrace exploration, experimentation, and risk through a focus on innovation,” said the Hon Julie Bishop MP, Australia’s Minister for Foreign Affairs. “Greater innovation in development assistance will allow us to do a better job of tackling the world’s most daunting problems, such as a lack of credible health data.”

In addition to improving the recording of births and deaths, Data for Health will support new mechanisms for conducting public health surveys. These surveys will monitor major risk factors for early death, including non-communicable diseases (chronic diseases that are not transmitted from person to person such as cancer and diabetes). With information from these surveys, illness caused by day-to-day behaviors such as tobacco use and poor nutrition habits can be targeted, addressed and prevented. Data for Health will take advantage of the wide-spread use of mobile phone devices in developing countries to enhance the efficiency of traditional household surveys, which are typically time-consuming and expensive…(More)”

Sensor Law


Paper by Sandra Braman: For over two decades, information policy-making for human society has been increasingly supplemented, supplanted, and/or superceded by machinic decision-making; over three decades since legal decision-making has been explicitly put in place to serve machinic rather than social systems; and over four decades since designers of the Internet took the position that they were serving non-human (machinic, or daemon) users in addition to humans. As the “Internet of Things” becomes more and more of a reality, these developments increasingly shape the nature of governance itself. This paper’s discussion of contemporary trends in these diverse modes of human-computer interaction at the system level — interactions between social systems and technological systems — introduces the changing nature of the law as a sociotechnical problem in itself. In such an environment, technological innovations are often also legal innovations, and legal developments require socio-technical analysis as well as social, legal, political, and cultural approaches.

Examples of areas in which sensors are already receiving legal attention are rife. A non-comprehensive listing includes privacy concerns beginning but not ending with those raised by sensors embedded in phones and geolocation devices, which are the most widely discussed and those of which the public is most aware. Sensor issues arise in environmental law, health law, marine law, intellectual property law, and as they are raised by new technologies in use for national security purposes that include those confidence- and security-building measures intended for peacekeeping. They are raised by liability issues for objects that range from cars to ovens. And sensor issues are at the core of concerns about “telemetric policing,” as that is coming into use not only in North America and Europe, but in societies such as that of Brazil as well.

Sensors are involved in every stage of legal processes, from identification of persons of interest to determination of judgments and consequences of judgments. Their use significantly alters the historically-developed distinction among types of decision-making meant to come into use at different stages of the process, raising new questions about when, and how, human decision-making needs to dominate and when, and how, technological innovation might need to be shaped by the needs of social rather than human systems.

This paper will focus on the legal dimensions of sensors used in ubiquitous embedded computing….(More)”

Big Data for Social Good


Introduction to a Special Issue of the Journal “Big Data” by Catlett Charlie and Ghani Rayid: “…organizations focused on social good are realizing the potential as well but face several challenges as they seek to become more data-driven. The biggest challenge they face is a paucity of examples and case studies on how data can be used for social good. This special issue of Big Data is targeted at tackling that challenge and focuses on highlighting some exciting and impactful examples of work that uses data for social good. The special issue is just one example of the recent surge in such efforts by the data science community. …

This special issue solicited case studies and problem statements that would either highlight (1) the use of data to solve a social problem or (2) social challenges that need data-driven solutions. From roughly 20 submissions, we selected 5 articles that exemplify this type of work. These cover five broad application areas: international development, healthcare, democracy and government, human rights, and crime prevention.

“Understanding Democracy and Development Traps Using a Data-Driven Approach” (Ranganathan et al.) details a data-driven model between democracy, cultural values, and socioeconomic indicators to identify a model of two types of “traps” that hinder the development of democracy. They use historical data to detect causal factors and make predictions about the time expected for a given country to overcome these traps.

“Targeting Villages for Rural Development Using Satellite Image Analysis” (Varshney et al.) discusses two case studies that use data and machine learning techniques for international economic development—solar-powered microgrids in rural India and targeting financial aid to villages in sub-Saharan Africa. In the process, the authors stress the importance of understanding the characteristics and provenance of the data and the criticality of incorporating local “on the ground” expertise.

In “Human Rights Event Detection from Heterogeneous Social Media Graphs,” Chen and Neil describe efficient and scalable techniques to use social media in order to detect emerging patterns in human rights events. They test their approach on recent events in Mexico and show that they can accurately detect relevant human rights–related tweets prior to international news sources, and in some cases, prior to local news reports, which could potentially lead to more timely, targeted, and effective advocacy by relevant human rights groups.

“Finding Patterns with a Rotten Core: Data Mining for Crime Series with Core Sets” (Wang et al.) describes a case study with the Cambridge Police Department, using a subspace clustering method to analyze the department’s full housebreak database, which contains detailed information from thousands of crimes from over a decade. They find that the method allows human crime analysts to handle vast amounts of data and provides new insights into true patterns of crime committed in Cambridge…..(More)

Using open legislative data to map bill co-sponsorship networks in 15 countries


François Briatte at OpeningParliament.org: “A few years back, Kamil Gregor published a post under the title “Visualizing politics: Network analysis of bill sponsors”. His post, which focused on the lower chamber of the Czech Parliament, showed how basic social network analysis can support the exploration of parliamentary work, by revealing the ties that members of parliament create between each other through the co-sponsorship of private bills….In what follows, I would like to quickly report on a small research project that I have developed over the years, under the name “parlnet”.

Legislative data on bill co-sponsorship

This project looks at bill co-sponsorship networks in European countries. Many parliaments allow their members to co-sponsor each other’s private bills, which makes it possible to represent these parliaments as collaborative networks, where a tie exists between two MPs if they have co-sponsored legislation together.

This idea is not new: it was pioneered by James Fowler in the United States, and has been the subject of extensive research in American politics, both on the U.S. Congress and on state legislatures. Similar research also exists on the bill co-sponsorship networks of parliaments in Argentina, Chile andRomania.

Inspired by this research and by Baptiste Coulmont’s visualisation of the French lower chamber, I surveyed the parliamentary websites of the following countries:

  • all 28 current members of the European Union ;
  • 4 members of the EFTA: Iceland, Liechtenstein, Norway, and Switzerland

This search returned 19 parliamentary chambers from 15 countries for which it was (relatively) easy to extract legislative data, either through open data portals like data.riksdagen.se in Sweden ordata.stortinget.no in Norway, or from official parliamentary websites directly….After splitting the data into legislative periods separated by nationwide elections, I was able to draw a large collection of networks showing bill co-sponsorship in these 19 chambers….In this graph, each point (or node) is a Belgian MP, and each tie between two MPs indicates that they have co-sponsored at least one bill together. The colors and abbreviations used in the graph are party-related codes, which combine information on the parliamentary group and linguistic community of each MP.Because this kind of graph can be interesting to explore in more detail, I have also built interactive visualizations out of them, in order to show more detailed information on the MPs who participate in bill cosposorship…

The parlnet project was coded in R, and its code is public so that it might benefit from external contributions. The list of countries and chambers that it covers is not exhaustive: in some cases like Portugal, I simply failed to retrieve the data. More talented coders might therefore be able to add to the current database.

Bill cosponsorship networks illustrate how open legislative data provided by parliaments can be turned into interactive tools that easily convey some information about parliamentary work, including, but not limited to:

  • the role of parliamentary party leaders in managing the legislation produced by their groups
  • the impact of partisan discipline and ideology on legislative collaboration between MPs
  • the extent of cross-party cooperation in various parliamentary environments and chambers… (More)

31 cities agree to use EU-funded open innovation platform for better smart cities’ services


European Commission Press Release: “At CEBIT, 25 cities from 6 EU countries (Belgium, Denmark, Finland, Italy, Portugal and Spain) and 6 cities from Brazil will present Open & Agile Smart Cities Task Force (OASC), an initiative making it easier for city councils  and startups to improve smart city services (such as transport, energy efficiency, environmental or e-health services). This will be achieved thanks to FIWARE, an EU-funded, open source platform and cloud-based building blocks developed in the EU that can be used to develop a huge range of applications, from Smart Cities to eHealth, and from transport to disaster management. Many applications have already been built using FIWARE – from warnings of earthquakes to preventing food waste to Smartaxi apps. Find a full list of cities in the Background.

The OASC deal will allow cities to share their open data (collected from sensors measuring, for example, traffic flows) so that startups can develop apps and tools that benefit all citizens (for example, an app with traffic information for people on the move). Moreover, these systems will be shared between cities (so, an app with transport information developed in city A can be also adopted by city B, without the latter having to develop it from scratch); FIWARE will also give startups and app developers in these cities access to a global market for smart city services.

Cities from across the globe are trying to make the most of open innovation. This will allow them to include a variety of stakeholders in their activities (services are increasingly connected to other systems and innovative startups are a big part of this trend) and encourage a competitive yet attractive market for developers, thus reducing costs, increasing quality and avoiding vendor lock-in….(More)”

Turning smartphones into personal, real-time pollution-location monitors


Kurzweil Newsletter: “Scientists reporting in the ACS journal Environmental Science & Technology have used smartphone and sensing technology to better pinpoint times and locations of the worst air pollution, which is associated with respiratory and cardiovascular problems.

Most such studies create a picture of exposure based on air pollution levels outside people’s homes. This approach ignores big differences in air quality in school and work environments. It also ignores spikes in pollution that happen over the course of the day such as during rush hour.

To fill in these gaps, Mark J. Nieuwenhuijsen and colleagues in Spain, The Netherlands, and the U.S. equipped 54 school children from from 29 different schools around Barcelona with smartphones that could track their location and physical activity. The children also received sensors that continuously measured the ambient levels of black carbon, a component of soot. Although most children spent less than 4 percent of their day traveling to and from school, this exposure contributed 13 percent of their total potential black carbon exposure.

The study was associated with BREATHE, an epidemiological study of the relation between air pollution and brain development.

The researchers conclude that mobile technologies could contribute valuable new insights into air pollution exposure….

More: Mark J. Nieuwenhuijsen, David Donaire-Gonzalez, Ioar Rivas, Montserrat de Castro, Marta Cirach, Gerard Hoek, Edmund Seto, Michael Jerrett, Jordi Sunyer. Variability in and Agreement between Modeled and Personal Continuously Measured Black Carbon Levels Using Novel Smartphone and Sensor Technologies. Environmental Science & Technology, 2015; 150209104136008 DOI: 10.1021/es505362x