blog post

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.

Accountable machines: bureaucratic cybernetics?

Curated on March 28, 2016November 14, 2018 by Stefaan Verhulst

Alison Powell at LSE Media Policy Project Blog: “Algorithms are everywhere, or so we are told, and the black boxes of algorithmic decision-making make oversight of processes that regulators and activists argue ought to be transparent more difficult than in the past. But when, and where, and which machines do we wish to make accountable, and for what purpose? In this post I discuss how algorithms discussed by scholars are most commonly those at work on media platforms whose main products are the social networks and attention of individuals. Algorithms, in this case, construct individual identities through patterns of behaviour, and provide the opportunity for finely targeted products and services. While there are serious concerns about, for instance, price discrimination, algorithmic systems for communicating and consuming are, in my view, less inherently problematic than processes that impact on our collective participation and belonging as citizenship. In this second sphere, algorithmic processes – especially machine learning – combine with processes of governance that focus on individual identity performance to profoundly transform how citizenship is understood and undertaken.

Communicating and consuming

In the communications sphere, algorithms are what makes it possible to make money from the web for example through advertising brokerage platforms that help companies bid for ads on major newspaper websites. IP address monitoring, which tracks clicks and web activity, creates detailed consumer profiles and transform the everyday experience of communication into a constantly-updated production of consumer information. This process of personal profiling is at the heart of many of the concerns about algorithmic accountability. The consequence of perpetual production of data by individuals and the increasing capacity to analyse it even when it doesn’t appear to relate has certainly revolutionalised advertising by allowing more precise targeting, but what has it done for areas of public interest?

John Cheney-Lippold identifies how the categories of identity are now developed algorithmically, since a category like gender is not based on self-discloure, but instead on patterns of behaviour that fit with expectations set by previous alignment to a norm. In assessing ‘algorithmic identities’, he notes that these produce identity profiles which are narrower and more behaviour-based than the identities that we perform. This is a result of the fact that many of the systems that inspired the design of algorithmic systems were based on using behaviour and other markers to optimise consumption. Algorithmic identity construction has spread from the world of marketing to the broader world of citizenship – as evidenced by the Citizen Ex experiment shown at the Web We Want Festival in 2015.

Individual consumer-citizens

What’s really at stake is that the expansion of algorithmic assessment of commercially derived big data has extended the frame of the individual consumer into all kinds of other areas of experience. In a supposed ‘age of austerity’ when governments believe it’s important to cut costs, this connects with the view of citizens as primarily consumers of services, and furthermore, with the idea that a citizen is an individual subject whose relation to a state can be disintermediated given enough technology. So, with sensors on your garbage bins you don’t need to even remember to take them out. With pothole reporting platforms like FixMyStreet, a city government can be responsive to an aggregate of individual reports. But what aspects of our citizenship are collective? When, in the algorithmic state, can we expect to be together?

Put another way, is there any algorithmic process to value the long term education, inclusion, and sustenance of a whole community for example through library services?…

Seeing algorithms – machine learning in particular – as supporting decision-making for broad collective benefit rather than as part of ever more specific individual targeting and segmentation might make them more accountable. But more importantly, this would help algorithms support society – not just individual consumers….(More)”

Visualizing Potential Outbreaks of the Zika Virus

Curated on March 7, 2016May 29, 2019 by Stefaan Verhulst

Google’s Official Blog: “The recent Zika virus outbreak has caused concern around the world. We’ve seen more than a 3,000 percent increase in global search interest since November, and last month, the World Health Organization (WHO) declared a Public Health Emergency. The possible correlation with Zika, microcephaly and other birth defects is particularly alarming.

But unlike many other global pandemics, the spread of Zika has been harder to identify, map and contain. It’s believed that 4 in 5 people with the virus don’t show any symptoms, and the primary transmitter for the disease, the Aedes mosquito species, is both widespread and challenging to eliminate. That means that fighting Zika requires raising awareness on how people can protect themselves, as well as supporting organizations who can help drive the development of rapid diagnostics and vaccines. We also have to find better ways to visualize the threat so that public health officials and NGO’s can support communities at risk….

A volunteer team of Google engineers, designers, and data scientists is helping UNICEF build a platform to process data from different sources (i.e., weather and travel patterns) in order to visualize potential outbreaks. Ultimately, the goal of this open source platform is to identify the risk of Zika transmission for different regions and help UNICEF, governments and NGO’s decide how and where to focus their time and resources. This set of tools is being prototyped for the Zika response, but will also be applicable to future emergencies….

We already include robust information for 900+ health conditions directly on Search for people in the U.S. We’ve now also added extensive information about Zika globally in 16 languages, with an overview of the virus, symptom information, and Public Health Alerts from that can be updated with new information as it becomes available.

We’re also working with popular YouTube creators across Latin America, including Sesame Street and Brazilian physician Drauzio Varella, to raise awareness about Zika prevention via their channels.

We hope these efforts are helpful in fighting this new public health emergency, and we will continue to do our part to help combat this outbreak.

And if you’re curious about what that 3,000 percent search increase looks like, take a look:….(More)

Value public information so we can trust it, rely on it and use it

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

Speech by David Fricker, the director general of the National Archives of Australia: “No-one can deny that we are in an age of information abundance. More and more we rely on information from a variety of sources and channels. Digital information is seductive, because it’s immediate, available and easy to move around. But digital information can be used for nefarious purposes. Social issues can be at odds with processes of government in this digital age. There is a tension between what is the information, where it comes from and how it’s going to be used.

How do we know if the information has reached us without being changed, whether that’s intentional or not?

How do we know that government digital information will be the authoritative source when the pace of information exchange is so rapid? In short, how do we know what to trust?

“It’s everyone’s responsibly to contribute to a transparent government, and that means changes in our thinking and in our actions.”

These are big questions, because there is a complexity about digital information that we don’t have with paper. Information has never been more complicated, but also never more important. There’s no going back — nor would we want to — but it means that time is ticking, because valuable government information is being lost — as I speak. I want you to share my sense of urgency about digital information, and act on what I’m going to say today.

Consider the challenges and risks that come with the digital age: what does it really mean to have transparency and integrity of government in today’s digital environment?…

What does the digital age mean for government? Government should be delivering services online, which means thinking about location, timeliness and information accessibility. It’s about getting public-sector data out there, into the public, making it available to fuel the digital economy. And it’s about a process of change across government to make sure that we’re breaking down all of those silos, and the duplication and fragmentation which exist across government agencies in the application of information, communications, and technology…..

The digital age is about the digital economy, it’s about rethinking the economy of the nation through the lens of information that enables it. It’s understanding that a nation will be enriched, in terms of culture life, prosperity and rights, if we embrace the digital economy. And that’s a weighty responsibility. But the responsibility is not mine alone. It’s a responsibility of everyone in the government who makes records in their daily work. It’s everyone’s responsibly to contribute to a transparent government. And that means changes in our thinking and in our actions….

What has changed about democracy in the digital age? Once upon a time if you wanted to express your anger about something, you might write a letter to the editor of the paper, to the government department, or to your local member and then expect some sort of an argument or discussion as a response. Now, you can bypass all of that. You might post an inflammatory tweet or blog, your comment gathers momentum, you pick the right hashtag, and off we go. It’s all happening: you’re trending on Twitter…..

If I turn to transparency now, at the top of the list is the basic recognition that government information is public information. The information of the government belongs to the people who elected that government. It’s a fundamental of democratic values. It also means that there’s got to be more public participation in the development of public policy, which means if you’re going to have evidence-based, informed, policy development; government information has to be available, anywhere, anytime….

Good information governance is at the heart of managing digital information to provide access to that information into the future — ready access to government information is vital for transparency. Only when information is digital and managed well can government share it effectively with the Australian community, to the benefit of society and the economy.

There are many examples where poor information management, or poor information governance, has led to failures — both in the private and public sectors. Professor Peter Shergold’s recent report, Learning from Failure, why large government policy initiatives have gone so badly wrong in the past and how the chances of success in the future can be improved, highlights examples such as the Home Insulation Program, the NBN and Building the Education Revolution….(Full Speech)

Data Collaboratives: Matching Demand with Supply of (Corporate) Data to solve Public Problems

Curated on February 24, 2016August 3, 2018 by Stefaan Verhulst

Blog by Stefaan G. Verhulst, IrynaSusha and Alexander Kostura: “Data Collaboratives refer to a new form of collaboration, beyond the public-private partnership model, in which participants from different sectors (private companies, research institutions, and government agencies) share data to help solve public problems. Several of society’s greatest challenges — from climate change to poverty — require greater access to big (but not always open) data sets, more cross-sector collaboration, and increased capacity for data analysis. Participants at the workshop and breakout session explored the various ways in which data collaborative can help meet these needs.

Matching supply and demand of data emerged as one of the most important and overarching issues facing the big and open data communities. Participants agreed that more experimentation is needed so that new, innovative and more successful models of data sharing can be identified.

How to discover and enable such models? When asked how the international community might foster greater experimentation, participants indicated the need to develop the following:

· A responsible data framework that serves to build trust in sharing data would be based upon existing frameworks but also accommodates emerging technologies and practices. It would also need to be sensitive to public opinion and perception.

· Increased insight into different business models that may facilitate the sharing of data. As experimentation continues, the data community should map emerging practices and models of sharing so that successful cases can be replicated.

· Capacity to tap into the potential value of data. On the demand side,capacity refers to the ability to pose good questions, understand current data limitations, and seek new data sets responsibly. On the supply side, this means seeking shared value in collaboration, thinking creatively about public use of private data, and establishing norms of responsibility around security, privacy, and anonymity.

· Transparent stock of available data supply, including an inventory of what corporate data exist that can match multiple demands and that is shared through established networks and new collaborative institutional structures.

· Mapping emerging practices and models of sharing. Corporate data offers value not only for humanitarian action (which was a particular focus at the conference) but also for a variety of other domains, including science,agriculture, health care, urban development, environment, media and arts,and others. Gaining insight in the practices that emerge across sectors could broaden the spectrum of what is feasible and how.

In general, it was felt that understanding the business models underlying data collaboratives is of utmost importance in order to achieve win-win outcomes for both private and public sector players. Moreover, issues of public perception and trust were raised as important concerns of government organizations participating in data collaboratives….(More)”

Designing a toolkit for policy makers

Curated on February 3, 2016October 23, 2018 by Stefaan Verhulst

Laurence Grinyer at UK’s Open Policy Making Blog: “At the end of the last parliament, the Cabinet Office Open Policy Making team launched the Open Policy Making toolkit. This was about giving policy makers the actual tools that will enable them to develop policy that is well informed, creative, tested, and works. The starting point was addressing their needs and giving them what they had told us they needed to develop policy in an ever changing, fast paced and digital world. In a way, it was the culmination of the open policy journey we have been on with departments for the past 2 years. In the first couple of months we saw thousands of unique visits….

Our first version toolkit has been used by 20,000 policy makers. This gave us a huge audience to talk to to make sure that we continue to meet the needs of policy makers and keep the toolkit relevant and useful. Although people have really enjoyed using the toolkit, user testing quickly showed us a few problems…

We knew what we needed to do. Help people understand what Open Policy Making was, how it impacted their policy making, and then to make it as simple as possible for them to know exactly what to do next.

So we came up with some quick ideas on pen and paper and tested them with people. We quickly discovered what not to do. People didn’t want a philosophy— they wanted to know exactly what to do, practical answers, and when to do it. They wanted a sort of design manual for policy….

How do we make user-centered design and open policy making as understood as agile?

We decided to organise the tools around the journey of a policy maker. What might a policy maker need to understand their users? How could they co-design ideas? How could they test policy? We looked at what tools and techniques they could use at the beginning, middle and end of a project, and organised tools accordingly.

We also added sections to remove confusion and hesitation. Our opening section ‘Getting started with Open Policy Making’ provides people with a clear understanding of what open policy making might mean to them, but also some practical considerations. Sections for limited timeframes and budgets help people realise that open policy can be done in almost any situation.

And finally we’ve created a much cleaner and simpler design that lets people show as much or little of the information as they need….

So go and check out the new toolkit and make more open policy yourselves….(More)”

Open Data Is Changing the World in Four Ways…

Curated on January 28, 2016August 3, 2018 by Stefaan Verhulst

Stefaan Verhulst at The GovLab Blog: “New repository of case studies documents the impact of open data globally: odimpact.org.

Despite global commitments to and increasing enthusiasm for open data, little is actually known about its use and impact. What kinds of social and economic transformation has open data brought about, and what is its future potential? How—and under what circumstances—has it been most effective? How have open data practitioners mitigated risks and maximized social good?

Even as proponents of open data extol its virtues, the field continues to suffer from a paucity of empiricalevidence. This limits our understanding of open data and its impact.

Over the last few months, The GovLab (@thegovlab), in collaboration with Omidyar Network(@OmidyarNetwork), has worked to address these shortcomings by developing 19 detailed open data case studies from around the world. The case studies have been selected for their sectoral and geographic representativeness. They are built in part from secondary sources (“desk research”), and also from more than60 first-hand interviews with important players and key stakeholders. In a related collaboration withOmidyar Network, Becky Hogge(@barefoot_techie), an independent researcher, has developed an additional six open data case studies, all focused on the United Kingdom. Together, these case studies, seek to provide a more nuanced understanding of the various processes and factors underlying the demand, supply, release, use and impact of open data.

Today, after receiving and integrating comments from dozens of peer reviewers through a unique open process, we are delighted to share an initial batch of 10 case studies, as well three of Hogge’s UK-based stories. These are being made available at a new custom-built repository, Open Data’s Impact (http://odimpact.org), that will eventually house all the case studies, key findings across the studies, and additional resources related to the impact of open data. All this information will be stored in machine-readable HTML and PDF format, and will be searchable by area of impact, sector and region….(More)

Data Science ethics

Curated on December 13, 2015August 3, 2018 by Stefaan Verhulst

Gov.uk blog: “If Tesco knows day-to-day how poorly the nation is, how can Government access similar insights so it can better plan health services? If Airbnb can give you a tailored service depending on your tastes, how can Government provide people with the right support to help them back into work in a way that is right for them? If companies are routinely using social media data to get feedback from their customers to improve their services, how can Government also use publicly available data to do the same?

Data science allows us to use new types of data and powerful tools to analyse this more quickly and more objectively than any human could. It can put us in the vanguard of policymaking – revealing new insights that leads to better and more tailored interventions. And it can help reduce costs, freeing up resource to spend on more serious cases.

But some of these data uses and machine-learning techniques are new and still relatively untested in Government. Of course, we operate within legal frameworks such as the Data Protection Act and Intellectual Property law. These are flexible but don’t always talk explicitly about the new challenges data science throws up. For example, how are you to explain the decision making process of a deep learning black box algorithm? And if you were able to, how would you do so in plain English and not a row of 0s and 1s?

We want data scientists to feel confident to innovate with data, alongside the policy makers and operational staff who make daily decisions on the data that the analysts provide –. That’s why we are creating an ethical framework which brings together the relevant parts of the law and ethical considerations into a simple document that helps Government officials decide what it can do and what it should do. We have a moral responsibility to maximise the use of data – which is never more apparent than after incidents of abuse or crime are left undetected – as well as to pay heed to the potential risks of these new tools. The guidelines are draft and not formal government policy, but we want to share them more widely in order to help iterate and improve them further….

So what’s in the framework? There is more detail in the fuller document, but it is based around six key principles:

Start with a clear user need and public benefit: this will help you justify the level of data sensitivity and method you use
Use the minimum level of data necessary to fulfill the public benefit: there are many techniques for doing so, such as de-identification, aggregation or querying against data
Build robust data science models: the model is only as good as the data it contains and while machines are less biased than humans they can get it wrong. It’s critical to be clear about the confidence of the model and think through unintended consequences and biases contained within the data
Be alert to public perceptions: put simply, what would a normal person on the street think about the project?
Be as open and accountable as possible: Transparency is the antiseptic for unethical behavior. Aim to be as open as possible (with explanations in plain English), although in certain public protection cases the ability to be transparent will be constrained.
Keep data safe and secure: this is not restricted to data science projects but we know that the public are most concerned about losing control of their data….(More)”

Controlling the crowd? Government and citizen interaction on emergency-response platforms

Curated on December 12, 2015August 3, 2018 by Stefaan Verhulst

Gregory Asmolov at the Policy and Internet Blog: “My interest in the role of crowdsourcing tools and practices in emergency situations was triggered by my personal experience. In 2010 I was one of the co-founders of the Russian “Help Map” project, which facilitated volunteer-based response to wildfires in central Russia. When I was working on this project, I realized that a crowdsourcing platform can bring the participation of the citizen to a new level and transform sporadic initiatives by single citizens and groups into large-scale, relatively well coordinated operations. What was also important was that both the needs and the forms of participation required in order to address these needs be defined by the users themselves.

To some extent the citizen-based response filled the gap left by the lack of a sufficient response from the traditional institutions.[1] This suggests that the role of ICTs in disaster response should be examined within the political context of the power relationship between members of the public who use digital tools and the traditional institutions. My experience in 2010 was the first time I was able to see that, while we would expect that in a case of natural disaster both the authorities and the citizens would be mostly concerned about the emergency, the actual situation might be different.

Apparently the emergence of independent, citizen-based collective action in response to a disaster was considered as some type of threat by the institutional actors. First, it was a threat to the image of these institutions, which didn’t want citizens to be portrayed as the leading responding actors. Second, any type of citizen-based collective action, even if not purely political, may be an issue of concern in authoritarian countries in particular. Accordingly, one can argue that, while citizens are struggling against a disaster, in some cases the traditional institutions may make substantial efforts to restrain and contain the action of citizens. In this light, the role of information technologies can include not only enhancing citizen engagement and increasing the efficiency of the response, but also controlling the digital crowd of potential volunteers.

The purpose of this paper was to conceptualize the tension between the role of ICTs in the engagement of the crowd and its resources, and the role of ICTs in controlling the resources of the crowd. The research suggests a theoretical and methodological framework that allows us to explore this tension. The paper focuses on an analysis of specific platforms and suggests empirical data about the structure of the platforms, and interviews with developers and administrators of the platforms. This data is used in order to identify how tools of engagement are transformed into tools of control, and what major differences there are between platforms that seek to achieve these two goals. That said, obviously any platform can have properties of control and properties of engagement at the same time; however the proportion of these two types of elements can differ significantly.

One of the core issues for my research is how traditional actors respond to fast, bottom-up innovation by citizens.[2]. On the one hand, the authorities try to restrict the empowerment of citizens by the new tools. On the other hand, the institutional actors also seek to innovate and develop new tools that can restore the balance of power that has been challenged by citizen-based innovation. The tension between using digital tools for the engagement of the crowd and for control of the crowd can be considered as one of the aspects of this dynamic.

That doesn’t mean that all state-backed platforms are created solely for the purpose of control. One can argue, however, that the development of digital tools that offer a mechanism of command and control over the resources of the crowd is prevalent among the projects that are supported by the authorities. This can also be approached as a means of using information technologies in order to include the digital crowd within the “vertical of power”, which is a top-down strategy of governance. That is why this paper seeks to conceptualize this phenomenon as “vertical crowdsourcing”.

The question of whether using a digital tool as a mechanism of control is intentional is to some extent secondary. What is important is that the analysis of platform structures relying on activity theory identifies a number of properties that allow us to argue that these tools are primarily tools of control. The conceptual framework introduced in the paper is used in order to follow the transformation of tools for the engagement of the crowd into tools of control over the crowd. That said, some of the interviews with the developers and administrators of the platforms may suggest the intentional nature of the development of tools of control, while crowd engagement is secondary….Read the full article: Asmolov, G. (2015) Vertical Crowdsourcing in Russia: Balancing Governance of Crowds and State–Citizen Partnership in Emergency Situations.”

Data enriched research, data enhanced impact: the importance of UK data infrastructure.

Curated on November 23, 2015August 3, 2018 by Stefaan Verhulst

Matthew Woollard at LSE Impact Blog: “…Data made available for reuse, such as those in the UK Data Service collection have huge potential. They can unlock new discoveries in research, provide evidence for policy decisions and help promote core data skills in the next generation of researchers. By being part of a single infrastructure, data owners and data creators can work together with the UK Data Service – rather than duplicating efforts – to engage with the people who can drive the impact of their research further to provide real benefit to society. As a service we are also identifying new ways to understand and promote our impact, and our Impact Fellow and Director of Impact and Communications, Victoria Moody, is focusing on raising the visibility of the UK Data Service holdings and developing and promoting the use and impact of the data and resources in policy-relevant research, especially to new audiences such as policymakers, government sectors, charities, the private sector and the media…..

We are improving how we demonstrate the impact of both the Service and the data which we hold, by focusing on generating more and more authentic user corroboration. Our emphasis is on drawing together evidence about the reach and significance of the impact of our data and resources, and of the Service as a whole through our infrastructure and expertise. Headline impact indicators through which we will better understand our impact cover a range of areas (outlined above) where the Service brings efficiency to data access and re-use, benefit to its users and a financial and social return on investment.

We are working to understand more about how Service data contributes to impact by tracking the use of Service data in a range of initiatives focused on developing impact from research and by developing our insight into usage of our data by our users. Data in the collection have featured in a range of impact case studies in the Research Excellence Framework 2014. We are also developing a focus on understanding the specific beneficial effect, rather than simply that data were used in an output, that is – as it appears in policy, debate or the evidential process (although important). Early thoughts in developing this process are where (ideally) cited data can be tracked through the specific beneficial outcome and on to an evidenced effect, corroborated by the end user.

Our impact case studies demonstrate how the data have supported research which has led to policy change in a range of areas including; the development of mathematical models for Practice based Commissioning budgets for adult mental health in the UK and informing public policy on obesity; both using the Health Survey for England. Service data have also informed the development of impact around understanding public attitudes towards the police and other legal institutions using the Crime Survey for England and Wales and research to support the development of the national minimum wage using the Labour Force Survey. The cutting-edge new Demos Integration Hub maps the changing face of Britain’s diversity, revealing a mixed picture in the integration and upward mobility of ethnic minority communities and uses 2011 Census aggregate data (England and Wales) and Understanding Society….(More)”