From Paint to Pixels


Jacoba Urist at the Atlantic: “A growing number of artists are using data from self-tracking apps in their pieces, showing that creative work is as much a product of its technology as of its time….A growing community of “data artists” is creating conceptual works using information collected by mobile apps, GPS trackers, scientists, and more.

Data artists generally fall into two groups: those who work with large bodies of scientific data and those who are influenced by self-tracking. The Boston-based artist Nathalie Miebach falls into the former category: She transforms weather patterns into complex sculptures and musical scores. Similarly, David McCandless, who believes the world suffers from a “data glut,” turns military spending budgets into simple, striking diagrams. On one level, the genre aims to translate large amounts of information into some kind of aesthetic form. But a number of artists, scholars, and curators also believe that working with this data isn’t just a matter of reducing human beings to numbers, but also of achieving greater awareness of complex matters in a modern world….

Current tools make self-tracking more efficient than ever, but data artists are hardly the first to express themselves through their daily activities—or to try to find meaning within life’s monotony. The Italian Mannerist painter Jacopo Pontormo kept records of his daily life from January 1554 to October 1556. In it, he detailed the amount of food he ate, the weather, symptoms of illness, friends he visited, even his bowel movements. In the 1970s, the Japanese conceptualistOn Kawara produced his self-observation series, I Got Up, I Went, and I Met(recently shown at the Guggenheim), in which he painstakingly records the rhythms of his day. Kawara stamped postcards with the time he awoke, traced his daily trips onto photocopied maps, and listed the names of people he encountered for nearly 12 years….(More)

Chicago uses new technology to solve this very old urban problem


 at Fortune: “Chicago has spent 12 years collecting data on resident complaints. Now the city is harnessing that data to control the rat population, stopping infestations before residents spot rats in the first place.

For the past three years, Chicago police have been analyzing 911 calls to better predict crime patterns across the city and, in one case, actually forecasted a shootout minutes before it occurred.

Now, the city government is turning its big data weapons on the city’s rat population.

The city has 12 years of data on the resident complaints, ranging from calls about rodent sitting to graffiti. Those clusters of data lead the engineers to where the rats can potentially breed. The report is shared with the city’s sanitation team, which later cleans up the rat-infested areas.

“We discovered really interesting relationship that led to developing an algorithm about rodent prediction,” says Brenna Berman, Chicago’s chief information officer. “It involved 31 variables related to calls about overflowing trash bins and food poisoning in restaurants.”

The results, Berman says, are 20% more efficient versus the old responsive model.

Governing cities in the 21st century is a difficult task. It needs a political and economic support. In America, it was only in the early 1990s—when young adults started moving from the suburbs back to the cities—that the academic and policy consensus shifted back toward urban centers. Since then, cities are facing an influx of new residents, overwhelming the service providing agencies. To meet that demand amid the recent budget sequestration, cities like New York, San Francisco, Philadelphia, and Chicago are constantly elevating the art of governance through innovative policies.

Due to this new model, in Chicago, you might not even spot a rat. The city’s Department of Innovation and Technology analyzes big chunks of data to an extent where the likelihood of a rodent infestation is thwarted seven days ahead of resident rat-sightings…(More)”

How to use mobile phone data for good without invading anyone’s privacy


Leo Mirani in Quartz: “In 2014, when the West African Ebola outbreak was at its peak, some academics argued that the epidemic could have been slowed by using mobile phone data.

Their premise was simple: call-data records show the true nature of social networks and human movement. Understanding social networks and how people really move—as seen from phone movements and calls—could give health officials the ability to predict how a disease will move and where a disease will strike next, and prepare accordingly.

The problem is that call-data records are very hard to get a hold of. The files themselves are huge, there are enormous privacy risks, and the process of making the records safe for distribution is long.
First, the technical basics

Every time you make a phone call from your mobile phone to another mobile phone, the network records the following information (note: this is not a complete list):

  • The number from which the call originated
  • The number at which the call terminated
  • Start time of the call
  • Duration of the call
  • The ID number of the phone making the call
  • The ID number of the SIM card used to make the call
  • The code for the antenna used to make the call

On their own, these records are not creepy. Indeed, without them, networks would be unable to connect calls or bill customers. But it is easy to see why operators aren’t rushing to share this information. Even though the data includes none of the actual content of a phone call in the data, simply knowing which number is calling which, and from where and when, is usually more than enough to identify people.
So how can network operators use this valuable data for good while also protecting their own interests and those of their customers? A good example can be found in Africa, where Orange, a French mobile phone network with interests across several African countries, has for the second year run its “Data for Development” (D4D) program, which offers researchers a chance to mine call data for clues on development problems.

Steps to safe sharing

After a successful first year in Ivory Coast, Orange this year ran the D4D program in Senegal. The aim of the program is to give researchers and scientists at universities and other research labs access to data in order to find novel ways to aid development in health, agriculture, transport or urban planning, energy, and national statistics….(More)”

An Unexpected Value Coming From the Happy Meal


Gregory Ferenstein in Pacific Standard: “Improbable as it sounds, McDonald’s may hold the key to getting America’s youth to eat healthier.

A team of medical researchers led by Dr. Robert Siegel took a strategy from the Happy Meal playbook, pairing healthy lunch options at public schools with smiley faces and a toy. The result were extraordinary: voluntary healthy meal purchases quadrupled.

“A two-tiered approach of Emoticons followed by small prizes as an incentive for healthful food selections is very effective in increasing plain white milk, fruit and vegetable selection,” the researchers write in a study presented this week at the annual Pediatric Academic Societies meeting, in San Diego.

Indeed, the popularization of emoticons has been co-opted by researchers lately to see if the colorful balls of happiness can be utilized for socially beneficial ends. One 2014 study found that “emolabeling” could be a major factor in health choice selection by both pre-literate and young children….

This latest research delves further into the power of emoticons in two significant ways. First, the study was tested in some of the most troubled school neighborhoods. (Siegel estimates that a significant portion of the families were either poor or homeless.) Second, knowing that smiling faces alone may not be enough to change behavior, after three months of using emoticons, the team added in a toy to further entice healthy meals.

With emoticons alone, the team found that chocolate milk sales at the school took a noticeable dip, from 87 percent of total milk sales to 78 percent. Later, entire meals known as “Power Plates” were added and paired with a toy. These healthy lunches (with whole grains and vegetables) spiked from less than 10 percent to 42 percent with the introduction of emoticons and a toy.

Interestingly enough, after the toys were taken away, the children continued to select healthy meals. That’s because external rewards can have odd effects on behavior….(More)

Preparing for Responsible Sharing of Clinical Trial Data


Paper by Michelle M. Mello et al in the New England Journal of Medicine: “Data from clinical trials, including participant-level data, are being shared by sponsors and investigators more widely than ever before. Some sponsors have voluntarily offered data to researchers, some journals now require authors to agree to share the data underlying the studies they publish, the Office of Science and Technology Policy has directed federal agencies to expand public access to data from federally funded projects, and the European Medicines Agency (EMA) and U.S. Food and Drug Administration (FDA) have proposed the expansion of access to data submitted in regulatory applications. Sharing participant-level data may bring exciting benefits for scientific research and public health but may also have unintended consequences. Thus, expanded data sharing must be pursued thoughtfully.

We provide a suggested framework for broad sharing of participant-level data from clinical trials and related technical documents. After reviewing current data-sharing initiatives, potential benefits and risks, and legal and regulatory implications, we propose potential governing principles and key features for a system of expanded access to participant-level data and evaluate several governance structures….(More)”

What, Exactly, Do You Want?


Cass Sunstein at the New York Times: “Suppose that you value freedom of choice. Are you committed to the mere opportunity to choose, or will you also insist that people actually exercise that opportunity? Is it enough if the government, or a private institution, gives people the option of going their own way? Or is it particularly important to get people to say precisely what they want? In coming decades, these seemingly abstract questions will grow in importance, because they will decide central features of our lives.

Here’s an example. Until last month, all 50 states had a simple policy for voter registration: If you want to become a voter, you have the opportunity to register. Oregon is now the first state to adopt a radically different approach: If the relevant state officials know that you live in Oregon and are 18 or older, you’re automatically registered as a voter. If you don’t want to be one, you have the opportunity to opt out.

We could easily imagine a third approach. A state might decide that if you want some kind of benefit — say, a driver’s license — you have to say whether you want to register to vote. Under this approach, the state would require you to make an active choice about whether to be a voter. You would have to indicate your desires explicitly.

In countless contexts, the government, or some private institution, must decide among three possible approaches: Give people the opportunity to opt in; give people the opportunity to opt out; or require people to make some kind of active choice. For example, an employer may say that employees will be enrolled in a pension plan only if they opt in. Alternatively, it may automatically enroll employees in a pension plan (while allowing them the opportunity to opt out). Or it may instead tell employees that they can’t start work unless they say whether they want to participate in a pension plan.

You may think that while the decision raises philosophical puzzles, the stakes are small. If so, you would be wrong; the decision can have huge consequences. By itself, the opportunity to choose is not all that matters, because many people will not exercise that opportunity. Inertia has tremendous force, and people tend to procrastinate. If a state or a private company switches from a system of opt-out to one of opt-in, or vice versa, it can have major effects on people’s lives.

For example, Oregon expects that its new policy will produce up to 300,000 new registered voters. In 2004, Congress authorized the Department of Agriculture to allow states and localities to automatically enroll eligible poor children in school meal programs, rather than requiring their parents to sign them up. As a result, millions of such children now have access to school meals. In many nations, including the United States, Britain and Denmark, automatic enrollment in pension plans has significantly increased the number of employees who participate in pension plans. The Affordable Care Act builds on this practice with a provision that will require large employers to enroll employees automatically in health insurance plans.

In light of findings of this kind (and there are many more), a lot of people have argued that people would be much better off if many institutions switched, today or tomorrow, from “opt in” designs to “opt out.” Often they’re right; “opt out” can be a lot better. But from the standpoint of both welfare and personal freedom, opt out raises problems of its own, precisely because it does not involve an actual exercise of the power to choose….(More)

Solving the obesity crisis: knowledge, nudge or nanny?


BioMedCentral Blog: ” The 5th Annual Oxford London Lecture (17 March 2015) was delivered by Professor Susan Jebb from Oxford University. The presentation was titled: ‘Knowledge, nudge and nanny: Opportunities to improve the nation’s diet’. In this guest blog Dr Helen Walls, Research Fellow at the London School of Hygiene and Tropical Medicine, covers key themes from this presentation.

“Obesity and related non-communicable disease such as diabetes, heart disease and cancer poses a significant health, social and economic burden in countries worldwide, including the United Kingdom. Whilst the need for action is clear, the nutrition policy response is a highly controversial topic. Professor Jebb raised the question of how best to achieve dietary change: through ‘knowledge, nudge or nanny’?

Education regarding healthy nutrition is an important strategy, but insufficient. People are notoriously bad at putting their knowledge to work. The inclination to overemphasise the importance of knowledge, whilst ignoring the influence of environmental factors on human behaviours, is termed the ‘fundamental attribution error’. Education may also contribute to widening inequities.

Our choices are strongly shaped by the environments in which we live. So if ‘knowledge’ is not enough, what sort of interventions are appropriate? This raises questions regarding individual choice and the role of government. Here, Professor Jebb introduced the Nuffield Intervention Ladder.

 

Nuffield Intervention Ladder
Nuffield Intervention Ladder
Nuffield Council on Bioethics. Public health ethical issues. London: Nuffield Council on Bioethics. 2007.

The Nuffield Intervention Ladder or what I will refer to as ‘the ladder’ describes intervention types from least to most intrusive on personal choice. With addressing diets and obesity, Professor Jebb believes we need a range of policy types, across the range of rungs on the ladder.

Less intrusive measures on the ladder could include provision of information about healthy and unhealthy foods, and provision of nutritional information on products (which helps knowledge be put into action). More effective than labelling is the signposting of healthier choices.

Taking a few steps up the ladder brings in ‘nudge’, a concept from behavioural economics. A nudge is any aspect of the choice architecture that alters people’s behaviour in a predictable way without forbidding options or significantly changing economic incentives. Nudges are not mandates. Putting fruit at eye level counts as a nudge. Banning junk food does not.

Nudges are not mandates. Putting fruit at eye level counts as a nudge. Banning junk food does not.

The in-store environment has a huge influence over our choices, and many nudge options would fit here. For example, gondalar-end (end of aisle) promotions create a huge up-lift in sales. Removing unhealthy products from this position could make a considerable difference to the contents of supermarket baskets.

Nudge could be used to assist people make better nutritional choices, but it’s also unlikely to be enough. We celebrate the achievement we have made with tobacco control policies and smoking reduction. Here, we use a range of intervention types, including many legislative measures – the ‘nanny’ aspect of the title of this presentation….(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)”

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)”