Ebola: Can big data analytics help contain its spread?


at BBC News: “While emergency response teams, medical charities and non-governmental organisations struggle to contain the virus, could big data analytics help?
A growing number of data scientists believe so….
Mobile phones, widely owned in even the poorest countries in Africa, are proving to be a rich source of data in a region where other reliable sources are sorely lacking.
Orange Telecom in Senegal handed over anonymised voice and text data from 150,000 mobile phones to Flowminder, a Swedish non-profit organisation, which was then able to draw up detailed maps of typical population movements in the region.
Authorities could then see where the best places were to set up treatment centres, and more controversially, the most effective ways to restrict travel in an attempt to contain the disease.
The drawback with this data was that it was historic, when authorities really need to be able to map movements in real time. People’s movements tend to change during an epidemic.
This is why the US Centers for Disease Control and Prevention (CDC) is also collecting mobile phone mast activity data from mobile operators and mapping where calls to helplines are mostly coming from.

Population movement map of West AfricaMobile phone data from West Africa is being used to map population movements and predict how the Ebola virus might spread

A sharp increase in calls to a helpline from one particular area would suggest an outbreak and alert authorities to direct more resources there.
Mapping software company Esri is helping CDC to visualise this data and overlay other existing sources of data from censuses to build up a richer picture.
The level of activity at each mobile phone mast also gives a kind of heatmap of where people are and crucially, where and how far they are moving.

“We’ve never had this large-scale, anonymised mobile phone data before as a species,” says Nuria Oliver, a scientific director at mobile phone company Telefonica.

“The most positive impact we can have is to help emergency relief organisations and governments anticipate how a disease is likely to spread.
“Until now they had to rely on anecdotal information, on-the-ground surveys, police and hospital reports.”…

This Headline Is One of Many Experiments on You


Will Knight at MIT Technology Review: “On your way to this article, you probably took part in several experiments. You may have helped a search engine test a new way of displaying its results or an online retailer fine-tune an algorithm for recommending products. You may even have helped a news website decide which of two headlines readers are most likely to click on.
In other words, whether you realize it or not, the Web is already a gigantic, nonstop user-testing laboratory. Experimentation offers companies a powerful way to understand what customers want and how they are likely to behave, but it also seems that few people realize quite how much of it is going on.

This became clear in June, when Facebook experienced a backlash after publishing a study on the way negative emotions can spread across its network. The study, conducted by a team of internal researchers and academics, involved showing some people more negative posts than they would otherwise have seen, and then measuring how this affected their behavior. They in fact tended to post more negative content themselves, revealing a kind of “emotional contagion” (see “Facebook’s Emotion Study Is Just Its Latest Effort to Prod Users”).
Businesses have performed market research and other small experiments for years, but the practice has reached new levels of sophistication and complexity, largely because it is so easy to control the user experience on the Web, and then track how people’s behavior changes (see “What Facebook Knows”).
So companies with large numbers of users routinely tweak the information some of them see, and measure the resulting effect on their behavior—a practice known in the industry as A/B testing. Next time you see a credit card offer, for example, you might be one of a small group of users selected at random to see a new design. Or when you log onto Gmail, you may one of a chosen subset that gets to use a new feature developed by Google’s engineers.
“When doing things online, there’s a very large probability you’re going to be involved in multiple experiments every day,” Sinan Aral, a professor at MIT’s Sloan School of Management, said during a break at a conference for practitioners of large-scale user experiments last weekend in Cambridge, Massachusetts. “Look at Google, Amazon, eBay, Airbnb, Facebook—all of these businesses run hundreds of experiments, and they also account for a large proportion of Web traffic.”
At the Sloan conference, Ron Kohavi, general manager of the analysis and experimentation team at Microsoft, said each time someone uses the company’s search engine, Bing, he or she is probably involved in around 300 experiments. The insights that designers, engineers, and product managers can glean from these experiments can be worth millions of dollars in advertising revenue, Kohavi said…”

Re-imagining Cities


In cities around the world, digital platforms are bringing together citizens and service providers in innovative ways. In a recent post on Medium Stefaan Verhulst, Co-Founder and Chief of R&D and Julia Root, Adjunct Fellow at the GovLab write about the ways in which we observe cities re-imagining themselves. We point to four distinct ways that cities are redefining how they plan, build and invest in their futures. Each way deploys a different set of technologies and tools that when combined with urban thinking and design, is changing not just our urban environments, but the pace of change as well.
Read full article here.

Putting Government Data to Work


U.S. Department of Commerce Press Release: “The Governance Lab (GovLab) at New York University today released “Realizing The Potential of Open Government Data: A Roundtable with the U.S. Department of Commerce,” a report on findings and recommendations for ways the U.S. Commerce Department can improve its data management, dissemination and use. The report summarizes a June 2014 Open Data Roundtable, co-hosted by The GovLab and the White House Office of Science and Technology Policy with the Commerce Department, which brought together Commerce data providers and 25 representatives from the private sector and nonprofit organizations for an action-oriented dialogue on data issues and potential solutions. The GovLab is convening a series of other Open Data Roundtables in its mission to help make government more effective and connected to the public through technology.

“We were honored to work with the White House and the Department of Commerce to convene this event,” said Joel Gurin, senior advisor at The GovLab and project director of the Open Data 500 and the Roundtable Series. “The Department’s commitment to engaging with its data customers opens up great opportunities for public-private collaboration.”
Under Secretary of Commerce for Economic Affairs Mark Doms said, “At the Commerce Department, we are only at the beginning of our open data effort. We share the goals and objectives embodied by the call of the Open Data 500: to deliver data that is valuable to industry and that provides greater economic opportunity for millions of Americans.” …”

Big Thinkers. Big Data. Big Opportunity: Announcing The LinkedIn Economic Graph Challeng


at Linkedin Official Blog: “LinkedIn’s vision is to create economic opportunity for every member of the global workforce. Facilitating economic empowerment is a big task that will require bold thinking by smart, passionate individuals and groups. Today, we’re kicking off an initiative that aims to encourage this type of big thinking: the LinkedIn Economic Graph Challenge.
The LinkedIn Economic Graph Challenge is an idea that emerged from the development of the Economic Graph, a digital mapping of the global economy, comprised of a profile for every professional, company, job opportunity, the skills required to obtain those opportunities, every higher education organization, and all the professionally relevant knowledge associated with each of these entities. With these elements in place, we can connect talent with opportunity at massive scale.
We are launching the LinkedIn Economic Graph Challenge to encourage researchers, academics, and data-driven thinkers to propose how they would use data from LinkedIn to solve some of the most challenging economic problems of our times. We invite anyone who is interested to submit your most innovative, ambitious ideas. In return, we will recognize the three strongest proposals for using data from LinkedIn to generate a positive impact on the global economy, and present the team and/or individual with a $25,000 (USD) research award and the resources to complete their proposed research, with the potential to have it published….
We look forward to your submissions! For more information, please visit the LinkedIn Economic Graph Challenge website….”

CC Science → Sensored City


Citizen Sourced Data: “We routinely submit data to others and then worry about liberating the data from the silos. What if we could invert the model? What if collected data were first put into a completely free and open repository accessible to everyone so anyone could build applications with the data? What if the data itself were free so everyone could have an equal opportunity to create and even monetize their creativity? Funded by a generous grant from Robert Wood Johnson Foundation, we intend to do just that.
Partnering with Manylabs, a San Francisco-based sensor tools and education nonprofit, and Urban Matter, Inc., a Brooklyn-based design studio, and in collaboration with the City of Louisville, Kentucky, and Propeller Health, maker of a mobile platform for respiratory health management, we will design, develop and install a network of sensor-based hardware that will collect environmental information at high temporal and spatial scales and store it in a software platform designed explicitly for storing and retrieving such data.
Further, we will design, create and install a public data art installation that will be powered by the data we collect thereby communicating back to the public what has been collected about them.”

Atlas of Cities


New book edited by Paul Knox:  “More than half the world’s population lives in cities, and that proportion is expected to rise to three-quarters by 2050. Urbanization is a global phenomenon, but the way cities are developing, the experience of city life, and the prospects for the future of cities vary widely from region to region. The Atlas of Cities presents a unique taxonomy of cities that looks at different aspects of their physical, economic, social, and political structures; their interactions with each other and with their hinterlands; the challenges and opportunities they present; and where cities might be going in the future.
Each chapter explores a particular type of city—from the foundational cities of Greece and Rome and the networked cities of the Hanseatic League, through the nineteenth-century modernization of Paris and the industrialization of Manchester, to the green and “smart” cities of today. Expert contributors explore how the development of these cities reflects one or more of the common themes of urban development: the mobilizing function (transport, communication, and infrastructure); the generative function (innovation and technology); the decision-making capacity (governance, economics, and institutions); and the transformative capacity (society, lifestyle, and culture)….
Table of ContentsIntroduction[PDF] pdf-icon

The Problem-solving Capacity of the Modern State


New book edited by Martin Lodge and Kai Wegrich: “The early 21st century has presented considerable challenges to the problem-solving capacity of the contemporary state in the industrialised world. Among the many uncertainties, anxieties and tensions, it is, however, the cumulative challenge of fiscal austerity, demographic developments, and climate change that presents the key test for contemporary states. Debates abound regarding the state’s ability to address these and other problems given increasingly dispersed forms of governing and institutional vulnerabilities created by politico-administrative and economic decision-making structures. This volume advances these debates, first, by moving towards a cross-sectoral perspective that takes into account the cumulative nature of the contemporary challenge to governance focusing on the key governance areas of infrastructure, sustainability, social welfare, and social integration; second, by considering innovations that have sought to add problem-solving capacity; and third, by exploring the kind of administrative capacities (delivery, regulatory, coordination, and analytical) required to encourage and sustain innovative problem-solving. This edition introduces a framework for understanding the four administrative capacities that are central to any attempt at problem-solving and how they enable the policy instruments of the state to have their intended effect. It also features chapters that focus on the way in which these capacities have become stretched and how they have been adjusted, given the changing conditions; the way in which different states have addressed particular governance challenges, with particular attention paid to innovation at the level of policy instrument and the required administrative capacities; and, finally, types of governance capacities that lie outside the boundaries of the state.”

Innovation in Philanthropy is not a Hack-a-thon


Sam McAfee in Medium: “…Antiquated funding models and lack of a rapid data-driven evaluation process aren’t the only issues though. Most of the big ideas in the technology-for-social-impact space are focused either on incremental improvements to existing service models, maybe leveraging online services or mobile applications to improve cost-efficiency marginally. Or they solve only a very narrow niche problem for a small audience, often applying a technology that was already in development, and just happened to find a solution in the field.

Innovation Requires Disruption

When you look at innovation in the commercial world, like the Ubers and AirBnBs of the world, what you see is a clear and substantive break from previous modes of thinking about transportation and accommodation. And it’s not the technology itself that is all that impressive. There is nothing ground-breaking technically under the hood of either of those products that wasn’t already lying around for a decade. What makes them different is that they created business models that stepped completely out of the existing taxi and hotel verticals, and simply used technology to leverage existing frustrations with those antiquated models and harness latent demands, to produce a new, vibrant commercial ecosystem.

Now, let’s imagine the same framework in the social sector, where there are equivalent long-standing traditional modes of providing resources. To find new ways of meeting human needs that disrupt those models requires both safe-to-fail experimentation and rapid feedback and iteration in the field, with clear success criteria. Such rapid development can only be accomplished by a sharp, nimble and multifaceted team of thinkers and doers who are passionate about the problem, yes, but also empowered and enabled to break a few institutional eggs on the way to the creative omelet.

Agile and Lean are Proven Methods

It turns out that there are proven working models for cultivating and fostering this kind of innovative thinking and experimentation. As I mentioned above, agile and lean are probably the single greatest contribution to the world by the tech sector, far more impactful than any particular technology produced by it. Small, cross-functional teams working on tight, iterative timeframes, using an iterative data-informed methodology, can create new and disruptive solutions to big, difficult problems. They are able to do this precisely because they are unhindered by the hulking bureaucratic structures of the old guard. This is precisely why so many Fortune 500 companies are experimenting with innovation and R&D laboratories. Because they know their existing staff, structures, and processes cannot produce innovation within those constraints. Only the small, nimble teams can do it, and they can only do it if they are kept separate from, protected from even, the traditional production systems of the previous product cycle.

Yet big philanthropy still have barely experimented with this model, only trying it in a few isolated instances. Here at Neo, for example, we are working on a project for teachers funded by a forward-thinking foundation. What our client is trying to disrupt is no less than the entire US education system, and with goals and measurements developed by teachers for teachers, not by Silicon Valley hotshots who have no clue how to fix education.

Small, cross-functional teams working on tight, iterative timeframes, using an iterative data-informed methodology, can create new and disruptive solutions to big, difficult problems.

To start with, the project was funded in iterations of six-weeks at a time, each with a distinct and measurable goal. We built a small cross-functional team to tackle some of the tougher issues faced by teachers trying to raise the level of excellence in their classrooms. The team was empowered to talk directly to teachers, and incorporate their feedback into new versions of the project, released on almost a daily basis. We have iterated the design more than sixteen times in less then four months, and it’s starting to really take shape.

We have no idea whether this particular project will be successful in the long run. But what we do know is that the client and their funder have had the courage to step out of the traditional project funding models and apply agile and lean thinking to a very tough problem. And we’re proud to be invited along for the ride.

The vast majority of the social sector is still trying to tackle social problems with program and funding models that were pioneered early in the last century. Agile and lean methods hold the key to finally breaking the mold of the old, traditional model of resourcing social change initiatives. The philanthropic community should be interested in the agile and lean methods produced by the technology sector, not the money produced by it, and start reorganizing project teams and resource allocation strategies and timelines in line this proven innovation model.

Only then we will be in a position to really innovate for social change.”

Canada's Action Plan on Open Government 2014-2016


Draft action plan: “Canada’s second Action Plan on Open Government consists of twelve commitments that will advance open government principles in Canada over the next two years and beyond. The Directive on Open Government, new policy direction to federal departments and agencies on open government, will provide foundational support for each of the additional commitments which fall under three streams: Open Data, Open Information, and Open Dialogue.
Figure 1: Our Commitments
Open Government Directive Diagram

 

More:

Table of Contents