Type: magazine article

The New Thing in Google Flu Trends Is Traditional Data

Curated on Posted on by Stefaan Verhulst

in the New York Times: “Google is giving its Flu Trends service an overhaul — “a brand new engine,” as it announced in a blog post on Friday.

The new thing is actually traditional data from the Centers for Disease Control and Prevention that is being integrated into the Google flu-tracking model. The goal is greater accuracy after the Google service had been criticized for consistently over-estimating flu outbreaks in recent years.

The main critique came in an analysis done by four quantitative social scientists, published earlier this year in an article in Science magazine, “The Parable of Google Flu: Traps in Big Data Analysis.” The researchers found that the most accurate flu predictor was a data mash-up that combined Google Flu Trends, which monitored flu-related search terms, with the official C.D.C. reports from doctors on influenza-like illness.

The Google Flu Trends team is heeding that advice. In the blog post, written by Christian Stefansen, a Google senior software engineer, wrote, “We’re launching a new Flu Trends model in the United States that — like many of the best performing methods in the literature — takes official CDC flu data into account as the flu season progresses.”

Google’s flu-tracking service has had its ups and downs. Its triumph came in 2009, when it gave an advance signal of the severity of the H1N1 outbreak, two weeks or so ahead of official statistics. In a 2009 article in Nature explaining how Google Flu Trends worked, the company’s researchers did, as the Friday post notes, say that the Google service was not intended to replace official flu surveillance methods and that it was susceptible to “false alerts” — anything that might prompt a surge in flu-related search queries.

Yet those caveats came a couple of pages into the Nature article. And Google Flu Trends became a symbol of the superiority of the new, big data approach — computer algorithms mining data trails for collective intelligence in real time. To enthusiasts, it seemed so superior to the antiquated method of collecting health data that involved doctors talking to patients, inspecting them and filing reports.

But Google’s flu service greatly overestimated the number of cases in the United States in the 2012-13 flu season — a well-known miss — and, according to the research published this year, has persistently overstated flu cases over the years. In the Science article, the social scientists called it “big data hubris.”

Smarter video games, thanks to crowdsourcing

Curated on Posted on by Stefaan Verhulst

AAAS –Science Magazine: “Despite the stereotypes, any serious gamer knows it’s way more fun to play with real people than against the computer. Video game artificial intelligence, or AI, just isn’t very good; it’s slow, predictable, and generally stupid. All that stands to change, however, if GiantOtter, a Massachusetts-based startup, has its way, New Scientist reports. By crowdsourcing the AI’s learning, GiantOtter hopes to build systems where the computer can learn based on player’s previous behaviors, decision-making, and even voice communication—yes, the computer is listening in as you strategize. The hope is that by abandoning the traditional scripted programming models, AIs can be taught to mimic human behaviors, leading to more dynamic and challenging scenarios even in incredibly complex games like Blizzard Entertainment Inc.’s professionally played StarCraft II.“

An Infographic That Maps 2,000 Years of Cultural History in 5 Minutes

Curated on Posted on by Stefaan Verhulst

in Wired:  “…Last week in the journal Science, the researchers (led by University of Texas art historian Maximilian Schich) published a study that looked at the cultural history of Europe and North America by mapping the birth and deaths of more than 150,000 notable figures—including everyone from Leonardo Da Vinci to Ernest Hemingway. That data was turned into an amazing animated infographic that looks strikingly similar to the illustrated flight paths you find in the back of your inflight magazine. Blue dots indicate a birth, red ones means death.

The researchers used data from Freebase, which touts itself as a “community curated database of people, places and things.” This gives the data a strong western-bent. You’ll notice that many parts of Asia and the Middle East (not to mention pre-colonized North America), are almost wholly ignored in this video. But to be fair, the abstract did acknowledge that the study was focused mainly on Europe and North America.
Still, mapping the geography of cultural migration does gives you some insight about how the kind of culture we value has shifted over the centuries. It’s also a novel lens through which to view our more general history, as those migration trends likely illuminate bigger historical happenings like wars and the building of cross-country infrastructure.

'Big Data' Will Change How You Play, See the Doctor, Even Eat

Curated on Posted on by Stefaan Verhulst

We’re entering an age of personal big data, and its impact on our lives will surpass that of the Internet. Data will answer questions we could never before answer with certainty—everyday questions like whether that dress actually makes you look fat, or profound questions about precisely how long you will live.

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Every 20 years or so, a powerful technology moves from the realm of backroom expertise and into the hands of the masses. In the late-1970s, computing made that transition—from mainframes in glass-enclosed rooms to personal computers on desks. In the late 1990s, the first web browsers made networks, which had been for science labs and the military, accessible to any of us, giving birth to the modern Internet.

Each transition touched off an explosion of innovation and reshaped work and leisure. In 1975, 50,000 PCs were in use worldwide. Twenty years later: 225 million. The number of Internet users in 1995 hit 16 million. Today it’s more than 3 billion. In much of the world, it’s hard to imagine life without constant access to both computing and networks.

The 2010s will be the coming-out party for data. Gathering, accessing and gleaning insights from vast and deep data has been a capability locked inside enterprises long enough. Cloud computing and mobile devices now make it possible to stand in a bathroom line at a baseball game while tapping into massive computing power and databases. On the other end, connected devices such as the Nest thermostat or Fitbit health monitor and apps on smartphones increasingly collect new kinds of information about everyday personal actions and habits, turning it into data about ourselves.

More than 80 percent of data today is unstructured: tangles of YouTube videos, news stories, academic papers, social network comments. Unstructured data has been almost impossible to search for, analyze and mix with other data. A new generation of computers—cognitive computing systems that learn from data—will read tweets or e-books or watch video, and comprehend its content. Somewhat like brains, these systems can link diverse bits of data to come up with real answers, not just search results.

Such systems can work in natural language. The progenitor is the IBM Watson computer that won on Jeopardy in 2011. Next-generation Watsons will work like a super-powered Google. (Google today is a data-searching wimp compared with what’s coming.)

Sports offers a glimpse into the data age. Last season the NBA installed in every arena technology that can “watch” a game and record, in 48 minutes of action, more than 4 million data points about every movement and shot. That alone could yield new insights for NBA coaches, such as which group of five players most efficiently passes the ball around….

Think again about life before personal computing and the Internet. Even if someone told you that you’d eventually carry a computer in your pocket that was always connected to global networks, you would’ve had a hard time imagining what that meant—imagining WhatsApp, Siri, Pandora, Uber, Evernote, Tinder.

As data about everything becomes ubiquitous and democratized, layered on top of computing and networks, it will touch off the most spectacular technology explosion yet. We can see the early stages now. “Big data” doesn’t even begin to describe the enormity of what’s coming next.”

Urban Analytics (Updated and Expanded)

Curated on Posted on by Andrew Young

As part of an ongoing effort to build a knowledge base for the field of opening governance by organizing and disseminating its learnings, the GovLab Selected Readings series provides an annotated and curated collection of recommended works on key opening governance topics. In this edition, we explore the literature on Urban Analytics. To suggest additional readings on this or any other topic, please email biblio@thegovlab.org.

Data and its uses for Governance

Urban Analytics places better information in the hands of citizens as well as government officials to empower people to make more informed choices. Today, we are able to gather real-time information about traffic, pollution, noise, and environmental and safety conditions by culling data from a range of tools: from the low-cost sensors in mobile phones to more robust monitoring tools installed in our environment. With data collected and combined from the built, natural and human environments, we can develop more robust predictive models and use those models to make policy smarter.

With the computing power to transmit and store the data from these sensors, and the tools to translate raw data into meaningful visualizations, we can identify problems as they happen, design new strategies for city management, and target the application of scarce resources where they are most needed.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)
Amini, L., E. Bouillet, F. Calabrese, L. Gasparini, and O. Verscheure. “Challenges and Results in City-scale Sensing.” In IEEE Sensors, 59–61, 2011. http://bit.ly/1doodZm.

  • This paper examines “how city requirements map to research challenges in machine learning, optimization, control, visualization, and semantic analysis.”
  • The authors raises several research challenges including how to extract accurate information when the data is noisy and sparse; how to represent findings from digital pervasive technologies; and how people interact with one another and their environment.

Batty, M., K. W. Axhausen, F. Giannotti, A. Pozdnoukhov, A. Bazzani, M. Wachowicz, G. Ouzounis, and Y. Portugali. “Smart Cities of the Future.” The European Physical Journal Special Topics 214, no. 1 (November 1, 2012): 481–518. http://bit.ly/HefbjZ.

  • This paper explores the goals and research challenges involved in the development of smart cities that merge ICT with traditional infrastructures through digital technologies.
  • The authors put forth several research objectives, including: 1) to explore the notion of the city as a laboratory for innovation; 2) to develop technologies that ensure equity, fairness and realize a better quality of city life; and 3) to develop technologies that ensure informed participation and create shared knowledge for democratic city governance.
  • The paper also examines several contemporary smart city initiatives, expected paradigm shifts in the field, benefits, risks and impacts.

Budde, Paul. “Smart Cities of Tomorrow.” In Cities for Smart Environmental and Energy Futures, edited by Stamatina Th Rassia and Panos M. Pardalos, 9–20. Energy Systems. Springer Berlin Heidelberg, 2014. http://bit.ly/17MqPZW.

  • This paper examines the components and strategies involved in the creation of smart cities featuring “cohesive and open telecommunication and software architecture.”
  • In their study of smart cities, the authors examine smart and renewable energy; next-generation networks; smart buildings; smart transport; and smart government.
  • They conclude that for the development of smart cities, information and communication technology (ICT) is needed to build more horizontal collaborative structures, useful data must be analyzed in real time and people and/or machines must be able to make instant decisions related to social and urban life.

Cardone, G., L. Foschini, P. Bellavista, A. Corradi, C. Borcea, M. Talasila, and R. Curtmola. “Fostering Participaction in Smart Cities: a Geo-social Crowdsensing Platform.” IEEE Communications
Magazine 51, no. 6 (2013): 112–119. http://bit.ly/17iJ0vZ.

  • This article examines “how and to what extent the power of collective although imprecise intelligence can be employed in smart cities.”
  • To tackle problems of managing the crowdsensing process, this article proposes a “crowdsensing platform with three main original technical aspects: an innovative geo-social model to profile users along different variables, such as time, location, social interaction, service usage, and human activities; a matching algorithm to autonomously choose people to involve in participActions and to quantify the performance of their sensing; and a new Android-based platform to collect sensing data from smart phones, automatically or with user help, and to deliver sensing/actuation tasks to users.”

Chen, Chien-Chu. “The Trend towards ‘Smart Cities.’” International Journal of Automation and Smart Technology. June 1, 2014. http://bit.ly/1jOOaAg.

  • In this study, Chen explores the ambitions, prevalence and outcomes of a variety of smart cities, organized into five categories:
    • Transportation-focused smart cities
    • Energy-focused smart cities
    • Building-focused smart cities
    • Water-resources-focused smart cities
    • Governance-focused smart cities
  • The study finds that the “Asia Pacific region accounts for the largest share of all smart city development plans worldwide, with 51% of the global total. Smart city development plans in the Asia Pacific region tend to be energy-focused smart city initiatives, aimed at easing the pressure on energy resources that will be caused by continuing rapid urbanization in the future.”
  • North America, on the other hand is generally more geared toward energy-focused smart city development plans. “In North America, there has been a major drive to introduce smart meters and smart electric power grids, integrating the electric power sector with information and communications technology (ICT) and replacing obsolete electric power infrastructure, so as to make cities’ electric power systems more reliable (which in turn can help to boost private-sector investment, stimulate the growth of the ‘green energy’ industry, and create more job opportunities).”
  • Looking to Taiwan as an example, Chen argues that, “Cities in different parts of the world face different problems and challenges when it comes to urban development, making it necessary to utilize technology applications from different fields to solve the unique problems that each individual city has to overcome; the emphasis here is on the development of customized solutions for smart city development.”

Domingo, A., B. Bellalta, M. Palacin, M. Oliver and E. Almirall. “Public Open Sensor Data: Revolutionizing Smart Cities.” Technology and Society Magazine, IEEE 32, No. 4. Winter 2013. http://bit.ly/1iH6ekU.

  • In this article, the authors explore the “enormous amount of information collected by sensor devices” that allows for “the automation of several real-time services to improve city management by using intelligent traffic-light patterns during rush hour, reducing water consumption in parks, or efficiently routing garbage collection trucks throughout the city.”
  • They argue that, “To achieve the goal of sharing and open data to the public, some technical expertise on the part of citizens will be required. A real environment – or platform – will be needed to achieve this goal.” They go on to introduce a variety of “technical challenges and considerations involved in building an Open Sensor Data platform,” including:
    • Scalability
    • Reliability
    • Low latency
    • Standardized formats
    • Standardized connectivity
  • The authors conclude that, despite incredible advancements in urban analytics and open sensing in recent years, “Today, we can only imagine the revolution in Open Data as an introduction to a real-time world mashup with temperature, humidity, CO2 emission, transport, tourism attractions, events, water and gas consumption, politics decisions, emergencies, etc., and all of this interacting with us to help improve the future decisions we make in our public and private lives.”

Harrison, C., B. Eckman, R. Hamilton, P. Hartswick, J. Kalagnanam, J. Paraszczak, and P. Williams. “Foundations for Smarter Cities.” IBM Journal of Research and Development 54, no. 4 (2010): 1–16. http://bit.ly/1iha6CR.

  • This paper describes the information technology (IT) foundation and principles for Smarter Cities.
  • The authors introduce three foundational concepts of smarter cities: instrumented, interconnected and intelligent.
  • They also describe some of the major needs of contemporary cities, and concludes that Creating the Smarter City implies capturing and accelerating flows of information both vertically and horizontally.

Hernández-Muñoz, José M., Jesús Bernat Vercher, Luis Muñoz, José A. Galache, Mirko Presser, Luis A. Hernández Gómez, and Jan Pettersson. “Smart Cities at the Forefront of the Future Internet.” In The Future Internet, edited by John Domingue, Alex Galis, Anastasius Gavras, Theodore Zahariadis, Dave Lambert, Frances Cleary, Petros Daras, et al., 447–462. Lecture Notes in Computer Science 6656. Springer Berlin Heidelberg, 2011. http://bit.ly/HhNbMX.

  • This paper explores how the “Internet of Things (IoT) and Internet of Services (IoS), can become building blocks to progress towards a unified urban-scale ICT platform transforming a Smart City into an open innovation platform.”
  • The authors examine the SmartSantander project to argue that, “the different stakeholders involved in the smart city business is so big that many non-technical constraints must be considered (users, public administrations, vendors, etc.).”
  • The authors also discuss the need for infrastructures at the, for instance, European level for realistic large-scale experimentally-driven research.

Hoon-Lee, Jung, Marguerite Gong Hancock, Mei-Chih Hu. “Towards an effective framework for building smart cities: Lessons from Seoul and San Francisco.” Technological Forecasting and Social Change. Ocotober 3, 2013. http://bit.ly/1rzID5v.

  • In this study, the authors aim to “shed light on the process of building an effective smart city by integrating various practical perspectives with a consideration of smart city characteristics taken from the literature.”
  • They propose a conceptual framework based on case studies from Seoul and San Francisco built around the following dimensions:
    • Urban openness
    • Service innovation
    • Partnerships formation
    • Urban proactiveness
    • Smart city infrastructure integration
    • Smart city governance
  • The authors conclude with a summary of research findings featuring “8 stylized facts”:
    • Movement towards more interactive services engaging citizens;
    • Open data movement facilitates open innovation;
    • Diversifying service development: exploit or explore?
    • How to accelerate adoption: top-down public driven vs. bottom-up market driven partnerships;
    • Advanced intelligent technology supports new value-added smart city services;
    • Smart city services combined with robust incentive systems empower engagement;
    • Multiple device & network accessibility can create network effects for smart city services;
    • Centralized leadership implementing a comprehensive strategy boosts smart initiatives.

Kamel Boulos, Maged N. and Najeeb M. Al-Shorbaji. “On the Internet of Things, smart cities and the WHO Healthy Cities.” International Journal of Health Geographics 13, No. 10. 2014. http://bit.ly/Tkt9GA.

  • In this article, the authors give a “brief overview of the Internet of Things (IoT) for cities, offering examples of IoT-powered 21st century smart cities, including the experience of the Spanish city of Barcelona in implementing its own IoT-driven services to improve the quality of life of its people through measures that promote an eco-friendly, sustainable environment.”
  • The authors argue that one of the central needs for harnessing the power of the IoT and urban analytics is for cities to “involve and engage its stakeholders from a very early stage (city officials at all levels, as well as citizens), and to secure their support by raising awareness and educating them about smart city technologies, the associated benefits, and the likely challenges that will need to be overcome (such as privacy issues).”
  • They conclude that, “The Internet of Things is rapidly gaining a central place as key enabler of the smarter cities of today and the future. Such cities also stand better chances of becoming healthier cities.”

Keller, Sallie Ann, Steven E. Koonin, and Stephanie Shipp. “Big Data and City Living – What Can It Do for Us?” Significance 9, no. 4 (2012): 4–7. http://bit.ly/166W3NP.

  • This article provides a short introduction to Big Data, its importance, and the ways in which it is transforming cities. After an overview of the social benefits of big data in an urban context, the article examines its challenges, such as privacy concerns and institutional barriers.
  • The authors recommend that new approaches to making data available for research are needed that do not violate the privacy of entities included in the datasets. They believe that balancing privacy and accessibility issues will require new government regulations and incentives.

Kitchin, Rob. “The Real-Time City? Big Data and Smart Urbanism.” SSRN Scholarly Paper. Rochester, NY: Social Science Research Network, July 3, 2013. http://bit.ly/1aamZj2.

  • This paper focuses on “how cities are being instrumented with digital devices and infrastructure that produce ‘big data’ which enable real-time analysis of city life, new modes of technocratic urban governance, and a re-imagining of cities.”
  • The authors provide “a number of projects that seek to produce a real-time analysis of the city and provides a critical reflection on the implications of big data and smart urbanism.”

Mostashari, A., F. Arnold, M. Maurer, and J. Wade. “Citizens as Sensors: The Cognitive City Paradigm.” In 2011 8th International Conference Expo on Emerging Technologies for a Smarter World (CEWIT), 1–5, 2011. http://bit.ly/1fYe9an.

  • This paper argues that. “implementing sensor networks are a necessary but not sufficient approach to improving urban living.”
  • The authors introduce the concept of the “Cognitive City” – a city that can not only operate more efficiently due to networked architecture, but can also learn to improve its service conditions, by planning, deciding and acting on perceived conditions.
  • Based on this conceptualization of a smart city as a cognitive city, the authors propose “an architectural process approach that allows city decision-makers and service providers to integrate cognition into urban processes.”

Oliver, M., M. Palacin, A. Domingo, and V. Valls. “Sensor Information Fueling Open Data.” In Computer Software and Applications Conference Workshops (COMPSACW), 2012 IEEE 36th Annual, 116–121, 2012. http://bit.ly/HjV4jS.

  • This paper introduces the concept of sensor networks as a key component in the smart cities framework, and shows how real-time data provided by different city network sensors enrich Open Data portals and require a new architecture to deal with massive amounts of continuously flowing information.
  • The authors’ main conclusion is that by providing a framework to build new applications and services using public static and dynamic data that promote innovation, a real-time open sensor network data platform can have several positive effects for citizens.

Perera, Charith, Arkady Zaslavsky, Peter Christen and Dimitrios Georgakopoulos. “Sensing as a service model for smart cities supported by Internet of Things.” Transactions on Emerging Telecommunications Technologies 25, Issue 1. January 2014. http://bit.ly/1qJLDP9.

  • This paper looks into the “enormous pressure towards efficient city management” that has “triggered various Smart City initiatives by both government and private sector businesses to invest in information and communication technologies to find sustainable solutions to the growing issues.”
  • The authors explore the parallel advancement of the Internet of Things (IoT), which “envisions to connect billions of sensors to the Internet and expects to use them for efficient and effective resource management in Smart Cities.”
  • The paper proposes the sensing as a service model “as a solution based on IoT infrastructure.” The sensing as a service model consists of four conceptual layers: “(i) sensors and sensor owners; (ii) sensor publishers (SPs); (iii) extended service providers (ESPs); and (iv) sensor data consumers. They go on to describe how this model would work in the areas of waste management, smart agriculture and environmental management.

Privacy, Big Data, and the Public Good: Frameworks for Engagement. Edited by Julia Lane, Victoria Stodden, Stefan Bender, and Helen Nissenbaum; Cambridge University Press, 2014. http://bit.ly/UoGRca.

  • This book focuses on the legal, practical, and statistical approaches for maximizing the use of massive datasets while minimizing information risk.
  • “Big data” is more than a straightforward change in technology.  It poses deep challenges to our traditions of notice and consent as tools for managing privacy.  Because our new tools of data science can make it all but impossible to guarantee anonymity in the future, the authors question whether it possible to truly give informed consent, when we cannot, by definition, know what the risks are from revealing personal data either for individuals or for society as a whole.
  • Based on their experience building large data collections, authors discuss some of the best practical ways to provide access while protecting confidentiality.  What have we learned about effective engineered controls?  About effective access policies?  About designing data systems that reinforce – rather than counter – access policies?  They also explore the business, legal, and technical standards necessary for a new deal on data.
  • Since the data generating process or the data collection process is not necessarily well understood for big data streams, authors discuss what statistics can tell us about how to make greatest scientific use of this data. They also explore the shortcomings of current disclosure limitation approaches and whether we can quantify the extent of privacy loss.

Schaffers, Hans, Nicos Komninos, Marc Pallot, Brigitte Trousse, Michael Nilsson, and Alvaro Oliveira. “Smart Cities and the Future Internet: Towards Cooperation Frameworks for Open Innovation.” In The Future Internet, edited by John Domingue, Alex Galis, Anastasius Gavras, Theodore Zahariadis, Dave Lambert, Frances Cleary, Petros Daras, et al., 431–446. Lecture Notes in Computer Science 6656. Springer Berlin Heidelberg, 2011. http://bit.ly/16ytKoT.

  • This paper “explores ‘smart cities’ as environments of open and user-driven innovation for experimenting and validating Future Internet-enabled services.”
  • The authors examine several smart city projects to illustrate the central role of users in defining smart services and the importance of participation. They argue that, “Two different layers of collaboration can be distinguished. The first layer is collaboration within the innovation process. The second layer concerns collaboration at the territorial level, driven by urban and regional development policies aiming at strengthening the urban innovation systems through creating effective conditions for sustainable innovation.”

Suciu, G., A. Vulpe, S. Halunga, O. Fratu, G. Todoran, and V. Suciu. “Smart Cities Built on Resilient Cloud Computing and Secure Internet of Things.” In 2013 19th International Conference on Control Systems and Computer Science (CSCS), 513–518, 2013. http://bit.ly/16wfNgv.

  • This paper proposes “a new platform for using cloud computing capacities for provision and support of ubiquitous connectivity and real-time applications and services for smart cities’ needs.”
  • The authors present a “framework for data procured from highly distributed, heterogeneous, decentralized, real and virtual devices (sensors, actuators, smart devices) that can be automatically managed, analyzed and controlled by distributed cloud-based services.”

Townsend, Anthony. Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia. W. W. Norton & Company, 2013.

  • In this book, Townsend illustrates how “cities worldwide are deploying technology to address both the timeless challenges of government and the mounting problems posed by human settlements of previously unimaginable size and complexity.”
  • He also considers “the motivations, aspirations, and shortcomings” of the many stakeholders involved in the development of smart cities, and poses a new civics to guide these efforts.
  • He argues that smart cities are not made smart by various, soon-to-be-obsolete technologies built into its infrastructure, but how citizens use these ever-changing technologies to be “human-centered, inclusive and resilient.”

To stay current on recent writings and developments on Urban Analytics, please subscribe to the GovLab Digest.
Did we miss anything? Please submit reading recommendations to biblio@thegovlab.org or in the comments below.

Big Data, My Data

Curated on Posted on by Stefaan Verhulst

Jane Sarasohn-Kahn  at iHealthBeat: “The routine operation of modern health care systems produces an abundance of electronically stored data on an ongoing basis,” Sebastian Schneeweis writes in a recent New England Journal of Medicine Perspective.
Is this abundance of data a treasure trove for improving patient care and growing knowledge about effective treatments? Is that data trove a Pandora’s black box that can be mined by obscure third parties to benefit for-profit companies without rewarding those whose data are said to be the new currency of the economy? That is, patients themselves?
In this emerging world of data analytics in health care, there’s Big Data and there’s My Data (“small data”). Who most benefits from the use of My Data may not actually be the consumer.
Big focus on Big Data. Several reports published in the first half of 2014 talk about the promise and perils of Big Data in health care. The Federal Trade Commission’s study, titled “Data Brokers: A Call for Transparency and Accountability,” analyzed the business practices of nine “data brokers,” companies that buy and sell consumers’ personal information from a broad array of sources. Data brokers sell consumers’ information to buyers looking to use those data for marketing, managing financial risk or identifying people. There are health implications in all of these activities, and the use of such data generally is not covered by HIPAA. The report discusses the example of a data segment called “Smoker in Household,” which a company selling a new air filter for the home could use to target-market to an individual who might seek such a product. On the downside, without the consumers’ knowledge, the information could be used by a financial services company to identify the consumer as a bad health insurance risk.
“Big Data and Privacy: A Technological Perspective,” a report from the President’s Office of Science and Technology Policy, considers the growth of Big Data’s role in helping inform new ways to treat diseases and presents two scenarios of the “near future” of health care. The first, on personalized medicine, recognizes that not all patients are alike or respond identically to treatments. Data collected from a large number of similar patients (such as digital images, genomic information and granular responses to clinical trials) can be mined to develop a treatment with an optimal outcome for the patients. In this case, patients may have provided their data based on the promise of anonymity but would like to be informed if a useful treatment has been found. In the second scenario, detecting symptoms via mobile devices, people wishing to detect early signs of Alzheimer’s Disease in themselves use a mobile device connecting to a personal couch in the Internet cloud that supports and records activities of daily living: say, gait when walking, notes on conversations and physical navigation instructions. For both of these scenarios, the authors ask, “Can the information about individuals’ health be sold, without additional consent, to third parties? What if this is a stated condition of use of the app? Should information go to the individual’s personal physicians with their initial consent but not a subsequent confirmation?”
The World Privacy Foundation’s report, titled “The Scoring of America: How Secret Consumer Scores Threaten Your Privacy and Your Future,” describes the growing market for developing indices on consumer behavior, identifying over a dozen health-related scores. Health scores include the Affordable Care Act Individual Health Risk Score, the FICO Medication Adherence Score, various frailty scores, personal health scores (from WebMD and OneHealth, whose default sharing setting is based on the user’s sharing setting with the RunKeeper mobile health app), Medicaid Resource Utilization Group Scores, the SF-36 survey on physical and mental health and complexity scores (such as the Aristotle score for congenital heart surgery). WPF presents a history of consumer scoring beginning with the FICO score for personal creditworthiness and recommends regulatory scrutiny on the new consumer scores for fairness, transparency and accessibility to consumers.
At the same time these three reports went to press, scores of news stories emerged discussing the Big Opportunities Big Data present. The June issue of CFO Magazine published a piece called “Big Data: Where the Money Is.” InformationWeek published “Health Care Dives Into Big Data,” Motley Fool wrote about “Big Data’s Big Future in Health Care” and WIRED called “Cloud Computing, Big Data and Health Care” the “trifecta.”
Well-timed on June 5, the Office of the National Coordinator for Health IT’s Roadmap for Interoperability was detailed in a white paper, titled “Connecting Health and Care for the Nation: A 10-Year Vision to Achieve an Interoperable Health IT Infrastructure.” The document envisions the long view for the U.S. health IT ecosystem enabling people to share and access health information, ensuring quality and safety in care delivery, managing population health, and leveraging Big Data and analytics. Notably, “Building Block #3” in this vision is ensuring privacy and security protections for health information. ONC will “support developers creating health tools for consumers to encourage responsible privacy and security practices and greater transparency about how they use personal health information.” Looking forward, ONC notes the need for “scaling trust across communities.”
Consumer trust: going, going, gone? In the stakeholder community of U.S. consumers, there is declining trust between people and the companies and government agencies with whom people deal. Only 47% of U.S. adults trust companies with whom they regularly do business to keep their personal information secure, according to a June 6 Gallup poll. Furthermore, 37% of people say this trust has decreased in the past year. Who’s most trusted to keep information secure? Banks and credit card companies come in first place, trusted by 39% of people, and health insurance companies come in second, trusted by 26% of people.
Trust is a basic requirement for health engagement. Health researchers need patients to share personal data to drive insights, knowledge and treatments back to the people who need them. PatientsLikeMe, the online social network, launched the Data for Good project to inspire people to share personal health information imploring people to “Donate your data for You. For Others. For Good.” For 10 years, patients have been sharing personal health information on the PatientsLikeMe site, which has developed trusted relationships with more than 250,000 community members…”

#BringBackOurGirls: Can Hashtag Activism Spur Social Change?

Curated on Posted on by Stefaan Verhulst

Nancy Ngo at TechChange: “In our modern times of media cycles fighting for our short attention spans, it is easy to ride the momentum of a highly visible campaign that can quickly fizzle out once another competing story emerges. Since the kidnappings of approximately 300 Nigerian girls by militant Islamist group Boko Haram last month, the international community has embraced the hashtag, “#BringBackOurGirls”, in a very vocal and visible social media campaign demanding action to rescue the Chibok girls. But one month since the mass kidnapping without the rescue of the girls, do we need to take a different approach? Will #BringBackOurGirls be just another campaign we forget about once the next celebrity scandal becomes breaking news?

#BringBackOurGirls goes global starting in Nigeria

Most of the #BringBackOurGirls campaign activity has been highly visible on Twitter, Facebook, and international media outlets. In this fascinating Twitter heat map created using the tool, CartoDB, featured in TIME Magazine, we can see a time-lapsed digital map of how the hashtag, “#BringBackOurGirls” spread globally, starting organically from within Nigeria in mid April.

The #BringBackOurGirls hashtag has been embraced widely by many public figures and has garnered wide support across the world. Michelle Obama, David Cameron, and Malala Yusafzai have posted images with the hashtag, along with celebrities such as Ellen Degeneres, Angelina Jolie, and Dwayne Johnson. To date, nearly 1 million people signed the Change.org petition. Countries including the USA, UK, China, Israel have pledged to join the rescue efforts, and other human rights campaigns have joined the #BringBackOurGirls Twitter momentum, as seen on this Hashtagify map.

Is #BringBackOurGirls repeating the mistakes of #KONY2012?

Kony_2012_Poster_3

A great example of a past campaign where this happened was with the KONY2012 campaign, which brought some albeit short-lived urgency to addressing the child soldiers recruited by Joseph Kony, leader of the Lord’s Resistance Army (LRA). Michael Poffenberger, who worked on that campaign, will join us a guest expert in TC110: Social Media for Social Change online course in June 2013 and compare it the current #BringBackOurGirls campaign. Many have drawn parallels to both campaigns and warned of the false optimism that hyped social media messages can bring when context is not fully considered and understood.

According to Lauren Wolfe of Foreign Policy magazine, “Understanding what has happened to the Nigerian girls and how to rescue them means beginning to face what has happened to hundreds of thousands, if not millions, of girls over years in global armed conflict.” To some critics, this hashtag trivializes the weaknesses of Nigerian democracy that have been exposed. Critics of using social media in advocacy campaigns have used the term “slacktivism” to describe the passive, minimal effort needed to participate in these movements. Others have cited such media waves being exploited for individual gain, as opposed to genuinely benefiting the girls. Florida State University Political Science professor, Will H. Moore, argues that this hashtag activism is not only hurting the larger cause of rescuing the kidnapped girls, but actually helping Boko Haram. Jumoke Balogun, Co-Founder of CompareAfrique, also highlights the limits of the #BringBackOurGirls hashtag impact.

Hashtag activism, alone, is not enough

With all this social media activity and international press, what actual progress has been made in rescuing the kidnapped girls? If the objective is raising awareness of the issue, yes, the hashtag has been successful. If the objective is to rescue the girls, we still have a long way to go, even if the hashtag campaign has been part of a multi-pronged approach to galvanize resources into action.

The bottom line: social media can be a powerful tool to bring visibility and awareness to a cause, but a hashtag alone is not enough to bring about social change. There are a myriad of resources that must be coordinated to effectively implement this rescue mission, which will only become more difficult as more time passes. However, prioritizing and shining a sustained light on the problem, instead getting distracted by competing media cycles on celebrities getting into petty fights, is the first step toward a solution…”

How Cities Can Be Designed to Help—or Hinder—Sharing

Curated on Posted on by Stefaan Verhulst

Jay Walljasper in Yes!: Centuries before someone first uttered the words “sharing economy,” the steady rise of cities embodied both the principles and promise of that phrase. The reason more than half the people on earth now live in urban areas is the advantages that come from sharing resources, infrastructure, and lives with other people. Essential commons belonging to all of us, ranging from transportation systems to public health safeguards to plentiful social connections, are easier to create and maintain in a populated area.
Think about typical urban dwellers. They are more likely to reside in an apartment building, shared household, or compact living unit (saving on heating, utilities, original construction costs, and other expenses), walk or take transit (saving the environment as well as money), know a wide range of people (expanding their circle of friends and colleagues), and encounter new experiences (increasing their knowledge and skills).
Access to these opportunities for sharing offers economic, social, environmental, and educational rewards. But living in a populated area does not automatically mean more sharing. Indeed, the classic suburban lifestyle—a big, single-family house and a big yard isolated from everything else and reachable only by automobile—makes sharing extremely difficult….
“The suburbs were designed as a landscape to maximize consumption,” Fisher explains. “It worked against sharing of any kind. People had all this stuff in their houses and garages, which was going unused most of the time.”
Autos replaced streetcars. Kids rode school buses instead of walking to school.
Everyone bought their own lawn mower, shovels, tools, sports equipment, and grills.
Even the proverbial cup of sugar borrowed from a neighbor disappeared in favor of the 10-pound bag bought at the supermarket.
As our spending grew, our need for social connections shrank. “Mass consumption was good for the economy, but bad for our well-being,” Fisher notes. He now sees changes ahead for our communities as the economy evolves.
“The new economy is all about innovation, which depends on maximizing interaction, not consumption.”
This means redesigning our communities to bring people together by giving everyone more opportunities to “walk, live close together, and share.”
This shift can already be seen in farmers markets, co-working spaces, tool libraries, bike sharing systems, co-ops, credit unions, public spaces, and other sharing projects everywhere.
“Creative people in cities around the world are rising up…” declares Neal Gorenflo, co-founder of Shareable magazine. “We are not protesting, and we are not asking for permission, and we are not waiting—we are building a people-powered economy right under everyone’s noses.”
Excited by this emerging grassroots movement, Shareable recently launched the Sharing Cities Network to be an independent resource “for sharing innovators to discover together how to create as many sharing cities around the world as fast as possible.”
The aim is to help empower and connect local initiatives around the world through online forums, peer learning, and other ways to boost collaboration, share best practices, and catalyze new projects.”

This War of Mine – The Ultimate Serious Game

Curated on Posted on by Stefaan Verhulst

The Escapist Magazine “…there are not many games about the effect of war. Paweł Miechowski thinks that needs to be changed, and he’s doing it with a little game called This War of Mine from the Polish outfit 11 Bit Studio.
“We’re in the moment where we want to talk about important things via games,” Miechowski said. “We are used to the fact that important topics are covered by music, novels, movies, while games mostly about fun. Laughing ‘ha ha ha’ fun.”
In fact, he believes games are well-suited for showing harsh truths and realities, not by ham-fistedly repeating political phrases or mantras, but by allowing you to draw your own conclusions from the circumstances. “Games are perfect for this because they are interactive. Novels or movies are not,” he said. “Games can take you through the experience through your hands, by your eyes. You are not a spectator. You are part of the experience.”
What is the experience of This War of Mine then? 11 Bit Studios was inspired by the firsthand accounts of people who tried to survive within a modern city that had no law, no order or infrastructure due to an ongoing war between militaries. “Everything we did in this game, we did after extensive research. Any mechanics in the game are just a translation of our knowledge of situations in recent history,” he said. “Yugoslavia, Syria, Serbia. Anywhere civilians survived within a besieged city after war. They were all pretty similar, struggling for water, hygiene items, food, simple tools to make something, wood to heat the house up.”
Miechowski showed me an early build of This War of Mine and that’s exactly what it is. Your only goal, which is emblazoned on the screen when you start the game, is to “Survive for 30 days.” You begin inside a 2D representation of a bombed-out building with several floors. You have a few allies with names like Boris or Yvette, each of whom have traits such as “good cook” or “strong, but slow.” Orders can be given to your team, such as to build a bed or to scavenge the piles of junk within your stronghold for any useful items. You usually start out with nothing, but over time you’ll accumulate all sorts of items and materials. The game is in real time, the hours slowly tick by, but once you assign tasks it can be useful to advance the timeline by clicking the “Start Night” button.”

“Open-washing”: The difference between opening your data and simply making them available

Curated on Posted on by Stefaan Verhulst
Christian Villum at the Open Knowledge Foundation Blog:  “Last week, the Danish it-magazine Computerworld, in an article entitled “Check-list for digital innovation: These are the things you must know“, emphasised how more and more companies are discovering that giving your users access to your data is a good business strategy. Among other they wrote:

(Translation from Danish) According to Accenture it is becoming clear to many progressive businesses that their data should be treated as any other supply chain: It should flow easily and unhindered through the whole organisation and perhaps even out into the whole eco-system – for instance through fully open API’s.

They then use Google Maps as an example, which firstly isn’t entirely correct, as also pointed out by the Neogeografen, a geodata blogger, who explains how Google Maps isn’t offering raw data, but merely an image of the data. You are not allowed to download and manipulate the data – or run it off your own server.

But secondly I don’t think it’s very appropriate to highlight Google and their Maps project as a golden example of a business that lets its data flow unhindered to the public. It’s true that they are offering some data, but only in a very limited way – and definitely not as open data – and thereby not as progressively as the article suggests.

Surely it’s hard to accuse Google of not being progressive in general. The article states how Google Maps’ data are used by over 800,000 apps and businesses across the globe. So yes, Google has opened its silo a little bit, but only in a very controlled and limited way, which leaves these 800,000 businesses dependent on the continual flow of data from Google and thereby not allowing them to control the very commodities they’re basing their business on. This particular way of releasing data brings me to the problem that we’re facing: Knowing the difference between making data available and making them open.

Open data is characterized by not only being available, but being both legally open (released under an open license that allows full and free reuse conditioned at most to giving credit to it’s source and under same license) and technically available in bulk and in machine readable formats – contrary to the case of Google Maps. It may be that their data are available, but they’re not open. This – among other reasons – is why the global community around the 100% open alternative Open Street Map is growing rapidly and an increasing number of businesses choose to base their services on this open initiative instead.

But why is it important that data are open and not just available? Open data strengthens the society and builds a shared resource, where all users, citizens and businesses are enriched and empowered, not just the data collectors and publishers. “But why would businesses spend money on collecting data and then give them away?” you ask. Opening your data and making a profit are not mutually exclusive. Doing a quick Google search reveals many businesses that both offer open data and drives a business on them – and I believe these are the ones that should be highlighted as particularly progressive in articles such as the one from Computerworld….

We are seeing a rising trend of what can be termed “open-washing” (inspired by “greenwashing“) – meaning data publishers that are claiming their data is open, even when it’s not – but rather just available under limiting terms. If we – at this critical time in the formative period of the data driven society – aren’t critically aware of the difference, we’ll end up putting our vital data streams in siloed infrastructure built and owned by international corporations. But also to give our praise and support to the wrong kind of unsustainable technological development.”

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