Homero Gil de Zúñiga at Social Science Computer Review: “This special issue of the Social Science Computer Review provides a sample of the latest strategies employing large data sets in social media and political communication research. The proliferation of information communication technologies, social media, and the Internet, alongside the ubiquity of high-performance computing and storage technologies, has ushered in the era of computational social science. However, in no way does the use of “big data” represent a standardized area of inquiry in any field. This article briefly summarizes pressing issues when employing big data for political communication research. Major challenges remain to ensure the validity and generalizability of findings. Strong theoretical arguments are still a central part of conducting meaningful research. In addition, ethical practices concerning how data are collected remain an area of open discussion. The article surveys studies that offer unique and creative ways to combine methods and introduce new tools while at the same time address some solutions to ethical questions….(More)”
What Privacy Papers Should Policymakers be Reading in 2016?
Stacy Gray at the Future of Privacy Forum: “Each year, FPF invites privacy scholars and authors to submit articles and papers to be considered by members of our Advisory Board, with an aim toward showcasing those articles that should inform any conversation about privacy among policymakers in Congress, as well as at the Federal Trade Commission and in other government agencies. For our sixth annual Privacy Papers for Policymakers, we received submissions on topics ranging from mobile app privacy, to location tracking, to drone policy.
Our Advisory Board selected papers that describe the challenges and best practices of designing privacy notices, ways to minimize the risks of re-identification of data by focusing on process-based data release policy and taking a precautionary approach to data release, the relationship between privacy and markets, and bringing the concept of trust more strongly into privacy principles.
Our top privacy papers for 2015 are, in alphabetical order:
Florian Schaub, Rebecca Balebako, Adam L. Durity, and Lorrie Faith CranorIra S. Rubinstein and Woodrow HartzogArvind Narayanan, Joanna Huey, and Edward W. Felten
Our two papers selected for Notable Mention are:
Peter Swire (Testimony, Senate Judiciary Committee Hearing, July 8, 2015)Joel R. Reidenberg….(More)”
Big Data as Governmentality – Digital Traces, Algorithms, and the Reconfiguration of Data in International Development
Paper by Flyverbom, Mikkel and Madsen, Anders Klinkby and Rasche, Andreas: “This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects of international development agendas to algorithms that synthesize large-scale data, (3) novel ways of rationalizing knowledge claims that underlie development efforts, and (4) shifts in professional and organizational identities of those concerned with producing and processing data for development. Our discussion shows that big data problematizes selected aspects of traditional ways to collect and analyze data for development (e.g. via household surveys). We also demonstrate that using big data analyses to address development challenges raises a number of questions that can deteriorate its impact….(More)
Tech and Innovation to Re-engage Civic Life
Hollie Russon Gilman at the Stanford Social Innovation Review: “Sometimes even the best-intentioned policymakers overlook the power of people. And even the best-intentioned discussions on social impact and leveraging big data for the social sector can obscure the power of every-day people in their communities.
But time and time again, I’ve seen the transformative power of civic engagement when initiatives are structured well. For example, the other year I witnessed a high school student walk into a school auditorium one evening during Boston’s first-ever youth-driven participatory budgeting project. Participatory budgeting gives residents a structured opportunity to work together to identify neighborhood priorities, work in tandem with government officials to draft viable projects, and prioritize projects to fund. Elected officials in turn pledge to implement these projects and are held accountable to their constituents. Initially intrigued by an experiment in democracy (and maybe the free pizza), this student remained engaged over several months, because she met new members of her community; got to interact with elected officials; and felt like she was working on a concrete objective that could have a tangible, positive impact on her neighborhood.
For many of the young participants, ages 12-25, being part of a participatory budgeting initiative is the first time they are involved in civic life. Many were excited that the City of Boston, in collaboration with the nonprofit Participatory Budgeting Project, empowered young people with the opportunity to allocate $1 million in public funds. Through participating, young people gain invaluable civic skills, and sometimes even a passion that can fuel other engagements in civic and communal life.
This is just one example of a broader civic and social innovation trend. Across the globe, people are working together with their communities to solve seemingly intractable problems, but as diverse as those efforts are, there are also commonalities. Well-structured civic engagement creates the space and provides the tools for people to exert agency over policies. When citizens have concrete objectives, access to necessary technology (whether it’s postcards, trucks, or open data portals), and an eye toward outcomes, social change happens.
Using Technology to Distribute Expertise
Technology is allowing citizens around the world to participate in solving local, national, and global problems. When it comes to large, public bureaucracies, expertise is largely top-down and concentrated. Leveraging technology creates opportunities for people to work together in new ways to solve public problems. One way is through civic crowdfunding platforms like Citizinvestor.com, which cities can use to develop public sector projects for citizen support; several cities in Rhode Island, Oregon, and Philadelphia have successfully pooled citizen resources to fund new public works. Another way is through citizen science. Old Weather, a crowdsourcing project from the National Archives and Zooniverse, enrolls people to transcribe old British ship logs to identify climate change patterns. Platforms like these allow anyone to devote a small amount of time or resources toward a broader public good. And because they have a degree of transparency, people can see the progress and impact of their efforts. ….(More)”
Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life
Paper by Edward L. Glaeser et al: “New, “big” data sources allow measurement of city characteristics and outcome variables higher frequencies and finer geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big data has the most value for the study of cities when it allows measurement of the previously opaque, or when it can be coupled with exogenous shocks to people or place. We describe a number of new urban data sources and illustrate how they can be used to improve the study and function of cities. We first show how Google Street View images can be used to predict income in New York City, suggesting that similar image data can be used to map wealth and poverty in previously unmeasured areas of the developing world. We then discuss how survey techniques can be improved to better measure willingness to pay for urban amenities. Finally, we explain how Internet data is being used to improve the quality of city services….(More)”
Meeting the Challenges of Big Data
Opinion by the European Data Protection Supervisor: “Big data, if done responsibly, can deliver significant benefits and efficiencies for society and individuals not only in health, scientific research, the environment and other specific areas. But there are serious concerns with the actual and potential impact of processing of huge amounts of data on the rights and freedoms of individuals, including their right to privacy. The challenges and risks of big data therefore call for more effective data protection.
Technology should not dictate our values and rights, but neither should promoting innovation and preserving fundamental rights be perceived as incompatible. New business models exploiting new capabilities for the massive collection, instantaneous transmission, combination and reuse of personal information for unforeseen purposes have placed the principles of data protection under new strains, which calls for thorough consideration on how they are applied.
European data protection law has been developed to protect our fundamental rights and values, including our right to privacy. The question is not whether to apply data protection law to big data, but rather how to apply it innovatively in new environments. Our current data protection principles, including transparency, proportionality and purpose limitation, provide the base line we will need to protect more dynamically our fundamental rights in the world of big data. They must, however, be complemented by ‘new’ principles which have developed over the years such as accountability and privacy by design and by default. The EU data protection reform package is expected to strengthen and modernise the regulatory framework .
The EU intends to maximise growth and competitiveness by exploiting big data. But the Digital Single Market cannot uncritically import the data-driven technologies and business models which have become economic mainstream in other areas of the world. Instead it needs to show leadership in developing accountable personal data processing. The internet has evolved in a way that surveillance – tracking people’s behaviour – is considered as the indispensable revenue model for some of the most successful companies. This development calls for critical assessment and search for other options.
In any event, and irrespective of the business models chosen, organisations that process large volumes of personal information must comply with applicable data protection law. The European Data Protection Supervisor (EDPS) believes that responsible and sustainable development of big data must rely on four essential elements:
- organisations must be much more transparent about how they process personal data;
- afford users a higher degree of control over how their data is used;
- design user friendly data protection into their products and services; and;
- become more accountable for what they do….(More)
Open Government: Missing Questions
Vadym Pyrozhenko at Administration & Society: “This article places the Obama administration’s open government initiative within the context of evolution of the U.S. information society. It examines the concept of openness along the three dimensions of Daniel Bell’s social analysis of the postindustrial society: structure, polity, and culture. Four “missing questions” raise the challenge of the compatibility of public service values with the culture of openness, address the right balance between postindustrial information management practices and the capacity of public organizations to accomplish their missions, and ask to reconsider the idea that greater structural openness of public organizations will necessarily increase their democratic legitimacy….(More)”
Big Data and Privacy: Emerging Issues
O’Leary, Daniel E. at Intelligent Systems, IEEE : “The goals of big data and privacy are fundamentally opposed to each other. Big data and knowledge discovery are aimed reducing information asymmetries between organizations and the data sources, whereas privacy is aimed at maintaining information asymmetries of data sources. A number of different definitions of privacy are used to investigate some of the tensions between different characteristics of big data and potential privacy concerns. Specifically, the author examines the consequences of unevenness in big data, digital data going from local controlled settings to uncontrolled global settings, privacy effects of reputation monitoring systems, and inferring knowledge from social media. In addition, the author briefly analyzes two other emerging sources of big data: police cameras and stingray for location information….(More)”
Tackling quality concerns around (volunteered) big data
University of Twente: “… Improvements in online information communication and mobile location-aware technologies have led to a dramatic increase in the amount of volunteered geographic information (VGI) in recent years. The collection of volunteered data on geographic phenomena has a rich history worldwide. For example, the Christmas Bird Count has studied the impacts of climate change on spatial distribution and population trends of selected bird species in North America since 1900. Nowadays, several citizen observatories collect information about our environment. This information is complementary or, in some cases, essential to tackle a wide range of geographic problems.
Despite the wide applicability and acceptability of VGI in science, many studies argue that the quality of the observations remains a concern. Data collected by volunteers does not often follow scientific principles of sampling design, and levels of expertise vary among volunteers. This makes it hard for scientists to integrate VGI in their research.
Low quality, inconsistent, observations can bias analysis and modelling results because they are not representative for the variable studied, or because they decrease the ratio of signal to noise. Hence, the identification of inconsistent observations clearly benefits VGI-based applications and provide more robust datasets to the scientific community.
In their paper the researchers describe a novel automated workflow to identify inconsistencies in VGI. “Leveraging a digital control mechanism means we can give value to the millions of observations collected by volunteers” and “it allows a new kind of science where citizens can directly contribute to the analysis of global challenges like climate change” say Hamed Mehdipoor and Dr. Raul Zurita-Milla, who work at the Geo-Information Processing department of ITC….
While some inconsistent observations may reflect real, unusual events, the researchers demonstrated that these observations also bias the trends (advancement rates), in this case of the date of lilac flowering onset. This shows that identifying inconsistent observations is a pre-requisite for studying and interpreting the impact of climate change on the timing of life cycle events….(More)”
How Big Data is Helping to Tackle Climate Change
Bernard Marr at DataInformed: “Climate scientists have been gathering a great deal of data for a long time, but analytics technology’s catching up is comparatively recent. Now that cloud, distributed storage, and massive amounts of processing power are affordable for almost everyone, those data sets are being put to use. On top of that, the growing number of Internet of Things devices we are carrying around are adding to the amount of data we are collecting. And the rise of social media means more and more people are reporting environmental data and uploading photos and videos of their environment, which also can be analyzed for clues.
Perhaps one of the most ambitious projects that employ big data to study the environment is Microsoft’s Madingley, which is being developed with the intention of creating a simulation of all life on Earth. The project already provides a working simulation of the global carbon cycle, and it is hoped that, eventually, everything from deforestation to animal migration, pollution, and overfishing will be modeled in a real-time “virtual biosphere.” Just a few years ago, the idea of a simulation of the entire planet’s ecosphere would have seemed like ridiculous, pie-in-the-sky thinking. But today it’s something into which one of the world’s biggest companies is pouring serious money. Microsoft is doing this because it believes that analytical technology has finally caught up with the ability to collect and store data.
Another data giant that is developing tools to facilitate analysis of climate and ecological data is EMC. Working with scientists at Acadia National Park in Maine, the company has developed platforms to pull in crowd-sourced data from citizen science portals such as eBird and iNaturalist. This allows park administrators to monitor the impact of climate change on wildlife populations as well as to plan and implement conservation strategies.
Last year, the United Nations, under its Global Pulse data analytics initiative, launched the Big Data Climate Challenge, a competition aimed to promote innovate data-driven climate change projects. Among the first to receive recognition under the program is Global Forest Watch, which combines satellite imagery, crowd-sourced witness accounts, and public datasets to track deforestation around the world, which is believed to be a leading man-made cause of climate change. The project has been promoted as a way for ethical businesses to ensure that their supply chain is not complicit in deforestation.
Other initiatives are targeted at a more personal level, for example by analyzing transit routes that could be used for individual journeys, using Google Maps, and making recommendations based on carbon emissions for each route.
The idea of “smart cities” is central to the concept of the Internet of Things – the idea that everyday objects and tools are becoming increasingly connected, interactive, and intelligent, and capable of communicating with each other independently of humans. Many of the ideas put forward by smart-city pioneers are grounded in climate awareness, such as reducing carbon dioxide emissions and energy waste across urban areas. Smart metering allows utility companies to increase or restrict the flow of electricity, gas, or water to reduce waste and ensure adequate supply at peak periods. Public transport can be efficiently planned to avoid wasted journeys and provide a reliable service that will encourage citizens to leave their cars at home.
These examples raise an important point: It’s apparent that data – big or small – can tell us if, how, and why climate change is happening. But, of course, this is only really valuable to us if it also can tell us what we can do about it. Some projects, such as Weathersafe, which helps coffee growers adapt to changing weather patterns and soil conditions, are designed to help humans deal with climate change. Others are designed to tackle the problem at the root, by highlighting the factors that cause it in the first place and showing us how we can change our behavior to minimize damage….(More)”