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Why our peer review system is a toothless watchdog

Curated on April 16, 2016August 15, 2018 by Stefaan Verhulst

Ivan Oransky and Adam Marcus at StatNews: “While some — namely, journal editors and publishers — would like us to consider it the opposable thumb of scientific publishing, the key to differentiating rigor from rubbish, some of those very same people seem to think it’s good for nothing. Here is a partial list of the things that editors, publishers, and others have told the world peer review is not designed to do:

1. Detect irresponsible practices

Don’t expect peer reviewers to figure out if authors are “using public data as if it were the author’s own, submitting papers with the same content to different journals, or submitting an article that has already been published in another language without reference to the original,” said the InterAcademy Partnership, a consortium of national scientific academies.

2. Detect fraud

“Journal editors will tell you that peer review is not designed to detect fraud — clever misinformation will sail right through no matter how scrupulous the reviews,” Dan Engber wrote in Slate in 2005.

3. Pick up plagiarism

Peer review “is not designed to pick up fraud or plagiarism, so unless those are really egregious it usually doesn’t,” according to the Rett Syndrome Research Trust.

4. Spot ethics issues

“It is not the role of the reviewer to spot ethics issues in papers,” said Jaap van Harten, executive publisher of Elsevier (the world’s largest academic imprint)in a recent interview. “It is the responsibility of the author to abide by the publishing ethics rules. Let’s look at it in a different way: If a person steals a pair of shoes from a shop, is this the fault of the shop for not protecting their goods or the shoplifter for stealing them? Of course the fault lies with the shoplifter who carried out the crime in the first place.”

5. Spot statistical flaccidity

“Peer reviewers do not check all the datasets, rerun calculations of p-values, and so forth, except in the cases where statistical reviewers are involved — and even in these cases, statistical reviewers often check the methodologies used, sample some data, and move on.” So wrote Kent Anderson, who has served as a publishing exec at several top journals, including Science and the New England Journal of Medicine, in a recent blog post.

6. Prevent really bad research from seeing the light of day

Again, Kent Anderson: “Even the most rigorous peer review at a journal cannot stop a study from being published somewhere. Peer reviewers can’t stop an author from self-promoting a published work later.”

But …

Even when you lower expectations for peer review, it appears to come up short. Richard Smith, former editor of the BMJ, reviewed research showing that the system may be worse than no review at all, at least in biomedicine. “Peer review is supposed to be the quality assurance system for science, weeding out the scientifically unreliable and reassuring readers of journals that they can trust what they are reading,” Smith wrote. “In reality, however, it is ineffective, largely a lottery, anti-innovatory, slow, expensive, wasteful of scientific time, inefficient, easily abused, prone to bias, unable to detect fraud and irrelevant.”

So … what’s left? And are whatever scraps that remain worth the veneration peer review receives? Don’t write about anything that isn’t peer-reviewed, editors frequently admonish us journalists, even creating rules that make researchers afraid to talk to reporters before they’ve published. There’s a good chance it will turn out to be wrong. Oh? Greater than 50 percent? Because that’s the risk of preclinical research in biomedicine being wrong after it’s been peer-reviewed.

With friends like these, who needs peer review? In fact, we do need it, but not just only in the black box that happens before publication. We need continual scrutiny of findings, at sites such as PubMed Commons and PubPeer, in what is known as post-publication peer review. That’s where the action is, and where the scientific record actually gets corrected….(More)”

E-Government Strategy, ICT and Innovation for Citizen Engagement

Curated on April 12, 2016August 3, 2018 by Stefaan Verhulst

Brief by Dennis Anderson, Robert Wu, Dr. June-Suh Cho, and Katja Schroeder: “This book discusses three levels of e-government and national strategies to reach a citizen-centric participatory e-government, and examines how disruptive technologies help shape the future of e-government. The authors examine how e-government can facilitate a symbiotic relationship between the government and its citizens. ICTs aid this relationship and promote transparencies so that citizens can place greater trust in the activities of their government. If a government can manage resources more effectively by better understanding the needs of its citizens, it can create a sustainable environment for citizens. Having a national strategy on ICT in government and e-government can significantly reduce government waste, corruption, and inefficiency. Businesses, CIOs and CTOs in the public sector interested in meeting sustainability requirements will find this book useful. …(More)”

Foundation Openness: A Critical Component of Foundation Effectiveness

Curated on April 11, 2016August 3, 2018 by Stefaan Verhulst

Lindsay Louie at PhilanthroFiles: “We created the Fund for Shared Insight—a funder collaborative with diverse support from 30 different funders—to increase foundation openness. We believe that if foundations are more open—which we define as how they share about their goals and strategies; make decisions and measure progress; listen and engage in dialogue with others; act on what they hear; and share what they themselves have learned—they will be more effective.

We were so pleased to support Exponent Philanthropy’s video series featuring philanthropists being more open about their work: Philanthropy Lessons. To date, Exponent Philanthropy has released 5 of the total 9 videos, including:

Future video releases include:

Who Knows More? (expected 4/27/16)
Being Transparent (expected 4/27/16)
Value Beyond Dollars (expected 5/25/16)
Getting Out of the Office (expected 6/22/16)

We would love to see many more foundations make videos like these; engage in conversation with each other about these philanthropy lessons online and in person; share their experiences live at regional grantmaker association meetings or a national conferences like those Exponent Philanthropy hosts; and find other ways to be more open.

Why is this so important?

Recent research from the Center for Effective Philanthropy (report on CEP’s website here, full disclosure we funded this research) found that foundation CEOs see grantees, nonprofits that are considering applying for a grant, and other foundations working on similar issues as the top three audiences who benefit from a foundation being open about its work. Further, 86% of foundation CEOs who responded to the survey said they believe transparency is necessary for building strong relationships with grantees.

It was great to learn from this research that many foundations are open about their criteria for nonprofits seeking funding, their programmatic goals, and their strategies; and share about who makes decisions about the grantee selection process. Yet the research also found that foundations are not as open about sharing what they are achieving, how they assess their work, and their experiences with what has and hasn’t worked—and that foundation CEOs believe it would be beneficial for foundations to share more in these specific areas….(More)”

Website Seeks to Make Government Data Easier to Sift Through

Curated on April 5, 2016August 3, 2018 by Stefaan Verhulst

Steve Lohr at the New York Times: “For years, the federal government, states and some cities have enthusiastically made vast troves of data open to the public. Acres of paper records on demographics, public health, traffic patterns, energy consumption, family incomes and many other topics have been digitized and posted on the web.

This abundance of data can be a gold mine for discovery and insights, but finding the nuggets can be arduous, requiring special skills.

A project coming out of the M.I.T. Media Lab on Monday seeks to ease that challenge and to make the value of government data available to a wider audience. The project, called Data U S A, bills itself as “the most comprehensive visualization of U.S. public data.” It is free, and its software code is open source, meaning that developers can build custom applications by adding other data.

Cesar A. Hidalgo, an assistant professor of media arts and sciences at the M.I.T. Media Lab who led the development of Data USA, said the website was devised to “transform data into stories.” Those stories are typically presented as graphics, charts and written summaries….Type “New York” into the Data USA search box, and a drop-down menu presents choices — the city, the metropolitan area, the state and other options. Select the city, and the page displays an aerial shot of Manhattan with three basic statistics: population (8.49 million), median household income ($52,996) and median age (35.8).

Lower on the page are six icons for related subject categories, including economy, demographics and education. If you click on demographics, one of the so-called data stories appears, based largely on data from the American Community Survey of the United States Census Bureau.

Using colorful graphics and short sentences, it shows the median age of foreign-born residents of New York (44.7) and of residents born in the United States (28.6); the most common countries of origin for immigrants (the Dominican Republic, China and Mexico); and the percentage of residents who are American citizens (82.8 percent, compared with a national average of 93 percent).

Data USA features a selection of data results on its home page. They include the g ender w age g ap in Connecticut; the r acial b reakdown of po verty in Flint, Mich.; the wages of p hysicians and s urgeons across the United States; and the institutions that award the most c omputer s cience degrees….(More)

Data to the Rescue: Smart Ways of Doing Good

Curated on April 5, 2016May 29, 2019 by Stefaan Verhulst

Nicole Wallace in the Chronicle of Philanthropy: “For a long time, data served one purpose in the nonprofit world: measuring program results. But a growing number of charities are rejecting the idea that data equals evaluation and only evaluation.

Of course, many nonprofits struggle even to build the simplest data system. They have too little money, too few analysts, and convoluted data pipelines. Yet some cutting-edge organizations are putting data to work in new and exciting ways that drive their missions. A prime example: The Polaris Project is identifying criminal networks in the human-trafficking underworld and devising strategies to fight back by analyzing its data storehouse along with public information.

Other charities dive deep into their data to improve services, make smarter decisions, and identify measures that predict success. Some have such an abundance of information that they’re even pruning their collection efforts to allow for more sophisticated analysis.

The groups highlighted here are among the best nationally. In their work, we get a sneak peek at how the data revolution might one day achieve its promise.

House Calls: Living Goods…

Living Goods launched in eastern Africa in 2007 with an innovative plan to tackle health issues in poor families and reduce deaths among children. The charity provides loans, training, and inventory to locals in Uganda and Kenya — mostly women — to start businesses selling vitamins, medicine, and other health products to friends and neighbors.

Founder Chuck Slaughter copied the Avon model and its army of housewives-turned-sales agents. But in recent years, Living Goods has embraced a 21st-century data system that makes its entrepreneurs better health practitioners. Armed with smartphones, they confidently diagnose and treat major illnesses. At the same time, they collect information that helps the charity track health across communities and plot strategy….

Unraveling Webs of Wickedness: Polaris Project…

Calls and texts to the Polaris Project’s national human-trafficking hotline are often heartbreaking, terrifying, or both.

Relatives fear that something terrible has happened to a missing loved one. Trafficking survivors suffering from their ordeal need support. The most harrowing calls are from victims in danger and pleading for help.

Last year more than 5,500 potential cases of exploitation for labor or commercial sex were reported to the hotline. Since it got its start in 2007, the total is more than 24,000.

As it helps victims and survivors get the assistance they need, the Polaris Project, a Washington nonprofit, is turning those phone calls and texts into an enormous storehouse of information about the shadowy world of trafficking. By analyzing this data and connecting it with public sources, the nonprofit is drawing detailed pictures of how trafficking networks operate. That knowledge, in turn, shapes the group’s prevention efforts, its policy work, and even law-enforcement investigations….

Too Much Information: Year Up…

Year Up has a problem that many nonprofits can’t begin to imagine: It collects too much data about its program. “Predictive analytics really start to stink it up when you put too much in,” says Garrett Yursza Warfield, the group’s director of evaluation.

What Mr. Warfield describes as the “everything and the kitchen sink” problem started soon after Year Up began gathering data. The group, which fights poverty by helping low-income young adults land entry-level professional jobs, first got serious about measuring its work nearly a decade ago. Though challenged at first to round up even basic information, the group over time began tracking virtually everything it could: the percentage of young people who finish the program, their satisfaction, their paths after graduation through college or work, and much more.

Now the nonprofit is diving deeper into its data to figure out which measures can predict whether a young person is likely to succeed in the program. And halfway through this review, it’s already identified and eliminated measures that it’s found matter little. A small example: Surveys of participants early in the program asked them to rate their proficiency at various office skills. Those self-evaluations, Mr. Warfield’s team concluded, were meaningless: How can novice professionals accurately judge their Excel spreadsheet skills until they’re out in the working world?…

On the Wild Side: Wildnerness Society…Without room to roam, wild animals and plants breed among themselves and risk losing genetic diversity. They also fall prey to disease. And that’s in the best of times. As wildlife adapt to climate change, the chance to migrate becomes vital even to survival.

National parks and other large protected areas are part of the answer, but they’re not enough if wildlife can’t move between them, says Travis Belote, lead ecologist at the Wilderness Society.

“Nature needs to be able to shuffle around,” he says.

Enter the organization’s Wildness Index. It’s a national map that shows the parts of the country most touched by human activity as well as wilderness areas best suited for wildlife. Mr. Belote and his colleagues created the index by combining data on land use, population density, road location and size, water flows, and many other factors. It’s an important tool to help the nonprofit prioritize the locations it fights to protect.

In Idaho, for example, the nonprofit compares the index with information about known wildlife corridors and federal lands that are unprotected but meet the criteria for conservation designation. The project’s goal: determine which areas in the High Divide — a wild stretch that connects Greater Yellowstone with other protected areas — the charity should advocate to legally protect….(More)”

Selected Readings on Data and Humanitarian Response

Curated on April 3, 2016May 29, 2019 by Stefaan Verhulst

By Prianka Srinivasan and Stefaan G. Verhulst *

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of data and humanitarian response was originally published in 2016.

Data, when used well in a trusted manner, allows humanitarian organizations to innovate how to respond to emergency events, including better coordination of post-disaster relief efforts, the ability to harness local knowledge to create more targeted relief strategies, and tools to predict and monitor disasters in real time. Consequently, in recent years both multinational groups and community-based advocates have begun to integrate data collection and evaluation strategies into their humanitarian operations, to better and more quickly respond to emergencies. However, this movement poses a number of challenges. Compared to the private sector, humanitarian organizations are often less equipped to successfully analyze and manage big data, which pose a number of risks related to the security of victims’ data. Furthermore, complex power dynamics which exist within humanitarian spaces may be further exacerbated through the introduction of new technologies and big data collection mechanisms. In the below we share:

Selected Reading List (summaries and hyperlinks)
Annotated Selected Reading List
Additional Readings

Selected Reading List (summaries in alphabetical order)

Data and Humanitarian Response

John Karlsrud – Peacekeeping 4.0: Harnessing the Potential of Big Data, Social Media, and Cyber Technologies – Recommends that UN peacekeeping initiatives should better integrate big data and new technologies into their operations, adopting a “Peacekeeping 4.0” for the modern world.
Fancesco Mancini, International Peace Institute – New Technology and the prevention of Violence and Conflict – Explores the ways in which new tools available in communications technology can assist humanitarian workers in preventing violence and conflict.
Patrick Meier – Digital Humanitarians- How Big Data is changing the face of humanitarian response – Profiles the emergence of ‘Digital Humanitarians’—humanitarian workers who are using big data, crowdsourcing and new technologies to transform the way societies respond to humanitarian disasters.
Andrew Robertson and Steve Olson (USIP) – Using Data Sharing to Improve Coordination in Peacebuilding – Summarises the findings of a United States Institute of Peace workshop which investigated the use of data-sharing systems between government and non-government actors in conflict zones. It identifies some of the challenges and benefits of data-sharing in peacebuilding efforts.
United Nations Independent Expert Advisory Group on a Data Revolution for Sustainable Development – A World That Counts, Mobilizing the Data Revolution – Compiled by a group of 20 international experts, this report proposes ways to improve data management and monitoring, whilst mitigating some of the risks data poses.
Katie Whipkey and Andrej Verity – Guidance for Incorporating Big Data into Humanitarian Operations – Created as part of the Digital Humanitarian Network with the support of UN-OCHA, this is a manual for humanitarian organizations looking to strategically incorporate Big Data into their work.

Risks of Using Big Data in Humanitarian Context

Kate Crawford and Megan Finn – The limits of crisis data: analytical and ethical challenges of using social and mobile data to understand disasters – Analyzes the use of big data techniques following a crisis event, arguing that a reliance of social and mobile data can lead to significant oversights and ethical concerns in the wake of humanitarian disasters.
Katja Lindskov Jacobsen – Making design safe for citizens: A hidden history of humanitarian experimentation – Argues that the UNHCR’s use of iris recognition technology in 2002 and 2007 during the repatriation of Afghan refugees from Pakistan constitutes a case of “humanitarian experimentation.” It questions this sort of experimentation which compromises the security of refugees in the pursuit of safer technologies for the rest of the world.
Responsible Data Forum – Responsible Data Reflection Stories: an Overview – compiles various stories sourced by the Responsible Data Forum blog relating to data challenges faced by advocacy organizations, and draws recommendations based on these cases.
Kristin Bergtora Sandvik – The humanitarian cyberspace: shrinking space or an expanding frontier? – Provides a detailed account of the development of a “humanitarian cyberspace” and how information and communication technologies have been further integrated into humanitarian operations since the mid-1990s.

Annotated Selected Reading List (in alphabetical order)

Karlsrud, John. “Peacekeeping 4.0: Harnessing the Potential of Big Data, Social Media, and Cyber Technologies.” Cyberspace and International Relations, 2013. http://bit.ly/235Qb3e

This chapter from the book “Cyberspace and International Relations” suggests that advances in big data give humanitarian organizations unprecedented opportunities to prevent and mitigate natural disasters and humanitarian crises. However, the sheer amount of unstructured data necessitates effective “data mining” strategies for multinational organizations to make the most use of this data.
By profiling some civil-society organizations who use big data in their peacekeeping efforts, Karlsrud suggests that these community-focused initiatives are leading the movement toward analyzing and using big data in countries vulnerable to crisis.
The chapter concludes by offering ten recommendations to UN peacekeeping forces to best realize the potential of big data and new technology in supporting their operations.

Mancini, Fancesco. “New Technology and the prevention of Violence and Conflict.” International Peace Institute, 2013. http://bit.ly/1ltLfNV

This report from the International Peace Institute looks at five case studies to assess how information and communications technologies (ICTs) can help prevent humanitarian conflicts and violence. Their findings suggest that context has a significant impact on the ability for these ICTs for conflict prevention, and any strategies must take into account the specific contingencies of the region to be successful.
The report suggests seven lessons gleaned from the five case studies:
- New technologies are just one in a variety of tools to combat violence. Consequently, organizations must investigate a variety of complementary strategies to prevent conflicts, and not simply rely on ICTs.
- Not every community or social group will have the same relationship to technology, and their ability to adopt new technologies are similarly influenced by their context. Therefore, a detailed needs assessment must take place before any new technologies are implemented.
- New technologies may be co-opted by violent groups seeking to maintain conflict in the region. Consequently, humanitarian groups must be sensitive to existing political actors and be aware of possible negative consequences these new technologies may spark.
- Local input is integral to support conflict prevention measures, and there exists need for collaboration and awareness-raising with communities to ensure new technologies are sustainable and effective.
- Information shared between civil-society has more potential to develop early-warning systems. This horizontal distribution of information can also allow communities to maintain the accountability of local leaders.

Meier, Patrick. “Digital humanitarians: how big data is changing the face of humanitarian response.” Crc Press, 2015. http://amzn.to/1RQ4ozc

This book traces the emergence of “Digital Humanitarians”—people who harness new digital tools and technologies to support humanitarian action. Meier suggests that this has created a “nervous system” to connect people from disparate parts of the world, revolutionizing the way we respond to humanitarian crises.
Meier argues that such technology is reconfiguring the structure of the humanitarian space, where victims are not simply passive recipients of aid but can contribute with other global citizens. This in turn makes us more humane and engaged people.

Robertson, Andrew and Olson, Steve. “Using Data Sharing to Improve Coordination in Peacebuilding.” United States Institute for Peace, 2012. http://bit.ly/235QuLm

This report functions as an overview of a roundtable workshop on Technology, Science and Peace Building held at the United States Institute of Peace. The workshop aimed to investigate how data-sharing techniques can be developed for use in peace building or conflict management.
Four main themes emerged from discussions during the workshop:
- “Data sharing requires working across a technology-culture divide”—Data sharing needs the foundation of a strong relationship, which can depend on sociocultural, rather than technological, factors.
- “Information sharing requires building and maintaining trust”—These relationships are often built on trust, which can include both technological and social perspectives.
- “Information sharing requires linking civilian-military policy discussions to technology”—Even when sophisticated data-sharing technologies exist, continuous engagement between different stakeholders is necessary. Therefore, procedures used to maintain civil-military engagement should be broadened to include technology.
- “Collaboration software needs to be aligned with user needs”—technology providers need to keep in mind the needs of its users, in this case peacebuilders, in order to ensure sustainability.

United Nations Independent Expert Advisory Group on a Data Revolution for Sustainable Development. “A World That Counts, Mobilizing the Data Revolution.” 2014. https://bit.ly/2Cb3lXq

This report focuses on the potential benefits and risks data holds for sustainable development. Included in this is a strategic framework for using and managing data for humanitarian purposes. It describes a need for a multinational consensus to be developed to ensure data is shared effectively and efficiently.
It suggests that “people who are counted”—i.e., those who are included in data collection processes—have better development outcomes and a better chance for humanitarian response in emergency or conflict situations.

Katie Whipkey and Andrej Verity. “Guidance for Incorporating Big Data into Humanitarian Operations.” Digital Humanitarian Network, 2015. http://bit.ly/1Y2BMkQ

This report produced by the Digital Humanitarian Network provides an overview of big data, and how humanitarian organizations can integrate this technology into their humanitarian response. It primarily functions as a guide for organizations, and provides concise, brief outlines of what big data is, and how it can benefit humanitarian groups.
The report puts forward four main benefits acquired through the use of big data by humanitarian organizations: 1) the ability to leverage real-time information; 2) the ability to make more informed decisions; 3) the ability to learn new insights; 4) the ability for organizations to be more prepared.
It goes on to assess seven challenges big data poses for humanitarian organizations: 1) geography, and the unequal access to technology across regions; 2) the potential for user error when processing data; 3) limited technology; 4) questionable validity of data; 5) underdeveloped policies and ethics relating to data management; 6) limitations relating to staff knowledge.

Risks of Using Big Data in Humanitarian Context
Crawford, Kate, and Megan Finn. “The limits of crisis data: analytical and ethical challenges of using social and mobile data to understand disasters.” GeoJournal 80.4, 2015. http://bit.ly/1X0F7AI

Crawford & Finn present a critical analysis of the use of big data in disaster management, taking a more skeptical tone to the data revolution facing humanitarian response.
They argue that though social and mobile data analysis can yield important insights and tools in crisis events, it also presents a number of limitations which can lead to oversights being made by researchers or humanitarian response teams.
Crawford & Finn explore the ethical concerns the use of big data in disaster events introduces, including issues of power, privacy, and consent.
The paper concludes by recommending that critical data studies, such as those presented in the paper, be integrated into crisis event research in order to analyze some of the assumptions which underlie mobile and social data.

Jacobsen, Katja Lindskov (2010) Making design safe for citizens: A hidden history of humanitarian experimentation. Citizenship Studies 14.1: 89-103. http://bit.ly/1YaRTwG

This paper explores the phenomenon of “humanitarian experimentation,” where victims of disaster or conflict are the subjects of experiments to test the application of technologies before they are administered in greater civilian populations.
By analyzing the particular use of iris recognition technology during the repatriation of Afghan refugees to Pakistan in 2002 to 2007, Jacobsen suggests that this “humanitarian experimentation” compromises the security of already vulnerable refugees in order to better deliver biometric product to the rest of the world.

Responsible Data Forum. “Responsible Data Reflection Stories: An Overview.” http://bit.ly/1Rszrz1

This piece from the Responsible Data forum is primarily a compilation of “war stories” which follow some of the challenges in using big data for social good. By drawing on these crowdsourced cases, the Forum also presents an overview which makes key recommendations to overcome some of the challenges associated with big data in humanitarian organizations.
It finds that most of these challenges occur when organizations are ill-equipped to manage data and new technologies, or are unaware about how different groups interact in digital spaces in different ways.

Sandvik, Kristin Bergtora. “The humanitarian cyberspace: shrinking space or an expanding frontier?” Third World Quarterly 37:1, 17-32, 2016. http://bit.ly/1PIiACK

This paper analyzes the shift toward more technology-driven humanitarian work, where humanitarian work increasingly takes place online in cyberspace, reshaping the definition and application of aid. This has occurred along with what many suggest is a shrinking of the humanitarian space.
Sandvik provides three interpretations of this phenomena:
- First, traditional threats remain in the humanitarian space, which are both modified and reinforced by technology.
- Second, new threats are introduced by the increasing use of technology in humanitarianism, and consequently the humanitarian space may be broadening, not shrinking.
- Finally, if the shrinking humanitarian space theory holds, cyberspace offers one example of this, where the increasing use of digital technology to manage disasters leads to a contraction of space through the proliferation of remote services.

Additional Readings on Data and Humanitarian Response

Kristin Bergtora Sandvik, et al. – Humanitarian technology: a critical research agenda. – Takes a critical look at the field of humanitarian technology, analyzing what challenges this poses to post-disaster and conflict environment.
Kristin Bergtora Sandvik – “The Risks of Technological Innovation.” – Suggests that despite the evident benefits such technology presents, it can also undermine humanitarian action and lead to “catastrophic events” themselves needing a new type of humanitarian response.
Ryan Burns – Rethinking big data in digital humanitarianism: practices, epistemologies, and social relations – Takes a critical look at the use of big data in humanitarian spaces, arguing that the advent of digital humanitarianism has profound political and social implications, and can in fact limit information available following a humanitarian crisis.
Kate Crawford – Is Data a Danger to the Developing World? – Argues that it is not simply risks to privacy that data poses to developing countries, but suggests that “data discrimination” can affect even the basic human rights of individuals, and introduce problematic power hierarchies between those who can access data and those who cannot.
Paul Currion – Eyes Wide Shut: The challenge of humanitarian biometrics – Examines the use of biometrics by humanitarian organizations and national governments, and suggests stronger accountability is needed to ensure data from marginalized groups remain protected.
Yves-Alexandre de Montjoye, Jake Kendall and Cameron F. Kerry – Enabling Humanitarian Use of Mobile Phone Data – Analyzes how data from mobile communication can provide insights into the spread of infectious disease, and how such data can also compromise individual privacy.
Michael F. Goodchild and Alan Glennon – Crowdsourcing geographic information for disaster response: a research frontier – Explores how though volunteered geographic data may be messy and unreliable, it can provide many benefits in emergency situations.
Raphael Horler – Crowdsourcing in the Humanitarian Network – An Analysis of the Literature – A Bachelor thesis which explores the increasing use of crowdsourced data by organizations involved in disaster response, investigating some of the challenges such use of crowdsourcing poses.
Gus Hosein and Carly Nyst – Aiding Surveillance – Suggests that the unregulated use of technologies and surveillance systems by humanitarian organizations create systems which pose serious threats to individuals’ rights, particularly their right to privacy.
L. Jacobsen – The Politics of Humanitarian Technology: Good Intentions, Unintended Consequences and Insecurity – Raises concerns about the rise of data collection and digital technology in humanitarian aid organizations, arguing that its unquestioned prominence creates new structures of power and control, which remain hidden under the rubric of liberal humanitarianism.
Mirca Madianou – Digital Inequality and Second-Order Disasters: Social Media in the Typhoon Haiyan Recovery – Taking the effects of Typhoon Haiyan as a key case study, this paper investigates how digital inequalities and an unequal access to data can exacerbate existing social inequalities in a post-disaster environment.
Sean Martin McDonald – Ebola: A Big Data Disaster. Privacy, Property, and the Law of Disaster Experimentation – Analyzes the challenges and privacy risks of using unregulated data in public health coordination by taking the use of Call Detail Record (CDR) data during the Ebola crisis as a key case study.
National Academy of Engineering – Sensing and Shaping Emerging Conflicts: Report of a Joint Workshop of the National Academy of Engineering and the United States Institute of Peace: Roundtable on Technology, Science, and Peacebuilding – Building on the overview report of the United States Institute of Peace workshop examines what opportunities new technologies and data sharing provides for humanitarian groups.
Mary K.Pratt – Big Data’s role in humanitarian aid – A Computer World article which provides an overview of Big Data, and how it is improving the efficiency and efficacy of humanitarian response, especially in conflict zones.
Bertrand Taithe Róisínand and Roger Mac Ginty – Data hubris? Humanitarian information systems and the mirage of technology – Specifically looks at visual technology and crisis mapping, and big data, and suggests that there exists an over-enthusiasm in these claims made on behalf of technologically advanced humanitarian information systems.
Linnet Taylor – No place to hide? The ethics and analytics of tracking mobility using mobile phone data – Examines the ethical problems associated with the tracking of mobile phone data, especially in low or middle-income countries.
UN Office for the Coordination of Humanitarian Affairs (UN-OCHA) – Big data and humanitarianism: 5 things you need to know – Briefly outlines five issues that face humanitarian organizations as they integrate big data into their operations.
United Nations Global Pulse – Mapping the Risk-Utility Landscape of Mobile Data for Sustainable Development and Humanitarian Action – Reports on a Global Pulse project (done in partnership with Massachusetts Institute of Technology) which aimed to find how aggregated mobile data can be maximized to protect privacy and provide effective support to crisis response.
The Wilson Center – Connecting Grassroots to Government for Disaster Management: Workshop Summary – Summarizes the key points drawn from a two day Wilson Center workshop, which investigated how new technologies could engage whole communities in disaster management.

* Thanks to: Kristen B. Sandvik; Zara Rahman; Jennifer Schulte; Sean McDonald; Paul Currion; Dinorah Cantú-Pedraza and the Responsible Data Listserve for valuable input.

The Bottom of the Data Pyramid: Big Data and the Global South

Curated on April 1, 2016August 3, 2018 by Stefaan Verhulst

Payal Arora at the International Journal of Communication: “To date, little attention has been given to the impact of big data in the Global South, about 60% of whose residents are below the poverty line. Big data manifests in novel and unprecedented ways in these neglected contexts. For instance, India has created biometric national identities for her 1.2 billion people, linking them to welfare schemes, and social entrepreneurial initiatives like the Ushahidi project that leveraged crowdsourcing to provide real-time crisis maps for humanitarian relief.

While these projects are indeed inspirational, this article argues that in the context of the Global South there is a bias in the framing of big data as an instrument of empowerment. Here, the poor, or the “bottom of the pyramid” populace are the new consumer base, agents of social change instead of passive beneficiaries. This neoliberal outlook of big data facilitating inclusive capitalism for the common good sidelines critical perspectives urgently needed if we are to channel big data as a positive social force in emerging economies. This article proposes to assess these new technological developments through the lens of databased democracies, databased identities, and databased geographies to make evident normative assumptions and perspectives in this under-examined context….(More)”.

Your Data Footprint Is Affecting Your Life In Ways You Can’t Even Imagine

Curated on March 27, 2016November 14, 2018 by Stefaan Verhulst

Jessica Leber at Fast Co-Exist: “Cities have long seen the potential in big data to improve the government and the lives of citizens, and this is now being put into action in ways where governments touch citizens’ lives in very sensitive areas. New York City’s Department of Homelessness Services is mining apartment eviction filings, to see if they can understand who is at risk of becoming homeless and intervene early. And police departments all over the country have adopted predictive policing software that guides where officers should deploy, and at what time, leading to reduced crime in some cities.

In one study in Los Angeles, police officers deployed to certain neighborhoods by predictive policing software prevented 4.3 crimes per week, compared to 2 crimes per week when assigned to patrol a specific area by human crime analysts. Surely, a reduction in crime is a good thing. But community activists in places such as Bellingham, Washington, have grave doubts. They worry that outsiders can’t examine how the algorithms work, since the software is usually proprietary, and so citizens have no way of knowing what data the government is using to target them. They also worry that predictive policing is just exacerbating existing patterns of racial profiling. If the underlying crime data being used is the result of years of over-policing minority communities for minor offenses, then the predictions based on this biased data could create a feedback loop and lead to yet more over-policing.

At a smaller and more limited scale is the even more sensitive area of child protection services. Though the data isn’t really as “big” as in other examples, a few agencies are carefully exploring using statistical models to make decisions in several areas, such as which children in the system are most in danger of violence, which children are most in need of a trauma screening, and which are at risk of entering the criminal justice system.

In Hillsborough County, Florida, where a series of child homicides occurred, a private provider selected to manage the county’s child welfare system in 2012 came in and analyzed the data. Cases with the highest probability of serious injury or death had a few factors in common, they found: a child under the age of three, a “paramour” in the home, a substance abuse or domestic violence history, and a parent previously in the foster care system. They identified nine practices to use in these cases and hired a software provider to create a dashboard that allowed real-time feedback and dashboards. Their success has led to the program being implemented statewide….

“I think the opportunity is a rich one. At the same time, the ethical considerations need to be guiding us,” says Jesse Russell, chief program officer at the National Council on Crime and Delinquency, who has followed the use of predictive analytics in child protective services. Officials, he says, are treading carefully before using data to make decisions about individuals, especially when the consequences of being wrong—such as taking a child out of his or her home unnecessarily—are huge. And while caseworker decision-making can be flawed or biased, so can the programs that humans design. When you rely too much on data—if the data is flawed or incomplete, as could be the case in predictive policing—you risk further validating bad decisions or existing biases….

On the other hand, big data does have the potential to vastly expand our understanding of who we are and why we do what we do. A decade ago, serious scientists would have laughed someone out of the room who proposed a study of “the human condition.” It is a topic so broad and lacking in measurability. But perhaps the most important manifestation of big data in people’s lives could come from the ability for scientists to study huge, unwieldy questions they couldn’t before.

A massive scientific undertaking to study the human condition is set to launch in January of 2017. The Kavli Human Project, funded by the Kavli Foundation, plans to recruit 10,000 New Yorkers from all walks of life to be measured for 10 years. And by measured, they mean everything: all financial transactions, tax returns, GPS coordinates, genomes, chemical exposure, IQ, bluetooth sensors around the house, who subjects text and call—and that’s just the beginning. In all, the large team of academics expect to collect about a billion data points per person per year at an unprecedented low cost for each data point compared to other large research surveys.

The hope is with so much continuous data, researchers can for the first time start to disentangle the complex, seemingly unanswerable questions that have plagued our society, from what is causing the obesity epidemic to how to disrupt the poverty to prison cycle….(More)

The Social Intranet: Insights on Managing and Sharing Knowledge Internally

Curated on March 23, 2016November 14, 2018 by Stefaan Verhulst

Paper by Ines Mergel for IBM Center for the Business of Government: “While much of the federal government lags behind, some agencies are pioneers in the internal use of social media tools. What lessons and effective practices do they have to offer other agencies?

“Social intranets,” Dr. Mergel writes, “are in-house social networks that use technologies – such as automated newsfeeds, wikis, chats, or blogs – to create engagement opportunities among employees.” They also include the use of internal profile pages that help people identify expertise and interest (similar to Facebook or LinkedIn profiles), and that are used in combination with other social Intranet tools such as on-line communities or newsfeeds.

The report documents four case studies of government use of social intranets – two federal government agencies (the Department of State and the National Aeronautics and Space Administration) and two cross-agency networks (the U.S. Intelligence Community and the Government of Canada).

The author observes: “Most enterprise social networking platforms fail,” but identifies what causes these failures and how successful social intranet initiatives can avoid that fate and thrive. She offers a series of insights for successfully implementing social intranets in the public sector, based on her observations and case studies. …(More)”

Political Behavior and Big Data

Curated on March 15, 2016August 3, 2018 by Stefaan Verhulst

Special issue of the International Journal of Sociology: “Interest in the use of “big data” in the social sciences is growing dramatically. Yet, adequate methodological research on what constitutes such data, and about their validity, is lacking. Scholars face both opportunities and challenges inherent in this new era of unprecedented quantification of information, including that related to political actions and attitudes. This special issue of the International Journal of Sociology addresses recent uses of “big data,” its multiple meanings, and the potential that this may have in building a stronger understanding of political behavior. We present a working definition of “big data” and summarize the major issues involved in their use. While the papers in this volume deal with various problems – how to integrate “big data” sources with cross-national survey research, the methodological challenges involved in building cross-national longitudinal network data of country memberships in international nongovernmental organizations, methods of detecting and correcting for source selection bias in event data derived from news and other online sources, the challenges and solutions to ex post harmonization of international social survey data – they share a common viewpoint. To make good on the substantive promise of “big data,” scholars need to engage with their inherent methodological problems. At this date, scholars are only beginning to identify and solve them….(More)”