Open Data for Developing Economies

Curated on Posted on by Andrew Young

By Andrew Young, Stefaan Verhulst, and Juliet McMurren
This edition of the GovLab Selected Readings was developed as part of the Open Data for Developing Economies research project (in collaboration with WebFoundation, USAID and fhi360). Special thanks to Maurice McNaughton, Francois van Schalkwyk, Fernando Perini, Michael Canares and David Opoku for their input on an early draft. Please contact Stefaan Verhulst (stefaan@thegovlab.org) for any additional input or suggestions.
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Open data is increasingly seen as a tool for economic and social development. Across sectors and regions, policymakers, NGOs, researchers and practitioners are exploring the potential of open data to improve government effectiveness, create new economic opportunity, empower citizens and solve public problems in developing economies. Open data for development does not exist in a vacuum – rather it is a phenomenon that is relevant to and studied from different vantage points including Data4Development (D4D), Open Government, the United Nations’ Sustainable Development Goals (SDGs), and Open Development. The below selected readings provide a view of the current research and practice on the use of open data for development and its relationship to related interventions.
Selected Reading List (in alphabetical order)

Annotated Selected Readings List (in alphabetical order)

Open Data and Open Government for Development

Benjamin, Solomon, R. Bhuvaneswari, P. Rajan, Manjunatha, “Bhoomi: ‘E-Governance’, or, An Anti-Politics Machine Necessary to Globalize Bangalore?” CASUM-m Working Paper, January 2007, http://bit.ly/2aD3vZe. 

  • This paper explores the digitization of land titles and their effect on governance in Bangalore. The paper takes a critical view of digitization and transparency efforts, particularly as best practices that should be replicated in many contexts.
  • The authors point to the potential of centralized open data and land records databases as a means for further entrenching existing power structures. They found that the digitization of land records in Bangalore “led to increased corruption, much more bribes and substantially increased time taken for land transactions,” as well allowing “very large players in the land markets to capture vast quantities of land when Bangalore experiences a boom in the land market.”
  • They argue for the need “to replace politically neutered concepts like ‘transparency’, ‘efficiency’, ‘governance’, and ‘best practice’ conceptually more rigorous terms that reflect the uneven terrain of power and control that governance embodies.

McGee, Rosie and Duncan Edwards, “Introduction: Opening Governance – Change, Continuity and Conceptual Ambiguity,” IDS Bulletin, January 24, 2016. http://bit.ly/2aJn1pq.  

  • This introduction to a special issue of the IDS Bulletin frames the research and practice of leveraging opening governance as part of a development agenda.
  • The piece primarily focuses on a number of “critical debates” that “have begun to lay bare how imprecise and overblown the expectations are in the transparency, accountability and openness ‘buzzfield’, and the problems this poses.”
  • A key finding on opening governance’s uptake and impact in the development space relates to political buy-in:
    • “Political will is generally a necessary but insu cient condition for governance processes and relationships to become more open, and is certainly a necessary but insu cient condition for tech-based approaches to open them up. In short, where there is a will, tech-for-T&A may be able to provide a way; where there isn’t a will, it won’t.”

Open Data and Data 4 Development

3rd International Open Data Conference (IODC), “Enabling the Data Revolution: An International Open Data Roadmap,” Conference Report, 2015, http://bit.ly/2asb2ei. 

  • This report, prepared by Open Data for Development, summarizes the proceedings of the third IODC in Ottawa, ON. It sets out an action plan for “harnessing open data for sustainable development”, with the following five priorities:
    1. Deliver shared principles for open data
    2. Develop and adopt good practices and open standards for data publication
    3. Build capacity to produce and use open data effectively
    4. Strengthen open data innovation networks
    5. Adopt common measurement and evaluation tools
  • The report draws on 70 impact accounts to present cross-sector evidence of “the promise and reality of open data,” and emphasizes the utility of open data in monitoring development goals, and the importance of “joined-up open data infrastructures,” ensuring wide accessibility, and grounding measurement in a clear understanding of citizen need, in order to realize the greatest benefits from open data.
  • Finally, the report sets out a draft International Open Data Charter and Action Plan for International Collaboration.

Hilbert, Martin, “Big Data for Development: A Review of Promises and Challenges,” Development Policy Review, December 13, 2015, http://bit.ly/2aoPtxL.

  • This article presents a conceptual framework based on the analysis of 180 articles on the opportunities and threats of big data for international development.
  • Open data, Hilbert argues, can be an incentive for those outside of government to leverage big data analytics: “If data from the public sector were to be openly available, around a quarter of existing data resources could be liberated for Big Data Analytics.”
  • Hilbert explores the misalignment between “the level of economic well-being and perceived transparency of a country” and the existence of an overarching open data policy. He points to low-income countries that are active in the open data effort, like Kenya, Russia and Brazil, in comparison to “other countries with traditionally high perceived transparency,” which are less active in releasing data, like Chile, Belgium and Sweden.

International Development Research Centre, World Wide Web Foundation, and Berkman Center at Harvard University, “Fostering a Critical Development Perspective on Open Government Data,” Workshop Report, 2012, http://bit.ly/2aJpyQq. 

  • This paper considers the need for a critical perspective on whether the expectations raised by open data programmes worldwide — as “a suitable remedy for challenges of good governance, economic growth, social inclusion, innovation, and participation” — have been met, and if so, under what circumstances.
  • Given the lack of empirical evidence underlying the implementation of Open Data initiative to guide practice and policy formulation, particularly in developing countries, the paper discusses the implementation of a policy-oriented research agenda to ensure open data initiatives in the Global South “challenge democratic deficits, create economic value and foster inclusion.”
  • The report considers theories of the relationship between open data and impact, and the mediating factors affecting whether that impact is achieved. It takes a broad view of impact, including both demand- and supply-side economic impacts, social and environmental impact, and political impact.

Open Data for Development, “Open Data for Development: Building an Inclusive Data Revolution,” Annual Report, 2015, http://bit.ly/2aGbkz5. 

  • This report — the inaugural annual report for the Open Data for Development program — gives an overview of outcomes from the program for each of OD4D’s five program objectives:
    1. Setting a global open data for sustainable development agenda;
    2. Supporting governments in their open data initiatives;
    3. Scaling data solutions for sustainable development;
    4. Monitoring the availability, use and impact of open data around the world; and
    5. Building the institutional capacity and long-term sustainability of the Open Data for Development network.
  • The report identifies four barriers to impact in developing countries: the lack of capacity and leadership; the lack of evidence of what works; the lack of coordination between actors; and the lack of quality data.

Stuart, Elizabeth, Emma Samman, William Avis, Tom Berliner, “The Data Revolution: Finding the Missing Millions,” Open Data Institute Research Report, April 2015, http://bit.ly/2acnZtE.

  • This report examines the challenge of implementing successful development initiatives when many citizens are not known to their governments as they do not exist in official databases.
  • The authors argue that “good quality, relevant, accessible and timely data will allow willing governments to extend services into communities which until now have been blank spaces in planning processes, and to implement policies more efficiently.”
  • In addition to improvements to national statistical offices, the authors argue that “making better use of the data we already have” by increasing openness to certain datasets held by governments and international organizations could help to improve the situation.
  • They examine a number of open data efforts in developing countries, including Kenya and Mexico.
  • Finally, they argue that “the data revolution could play a role in changing the power dynamic between citizens, governments and the private sector, building on open data and freedom of information movements around the world. It has the potential to enable people to produce, access and understand information about their lives and to use this information to make changes.”

United Nations Independent Expert Advisory Group on a Data Revolution for Sustainable Development. “A World That Counts, Mobilizing the Data Revolution,” 2014, http://bit.ly/2am5K28.

  • 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.
  • In particular, “better and more open data” is described as having the potential to “save money and create economic, social and environmental value” toward sustainable development ends.

The World Bank, “Digital Dividends: World Development Report 2016.” http://bit.ly/2aG9Kx5. 

  • This report examines “digital dividends” or the development benefits of using digital technologies in the space.
  • The authors argue that: “To get the most out of the digital revolution, countries also need to work on the “analog complements”—by strengthening regulations that ensure competition among businesses, by adapting workers’ skills to the demands of the new economy, and by ensuring that institutions are accountable.”
  • The “data revolution,” which includes both big data and open data is listed as one of four “digital enablers.”
  • Open data’s impacts are explored across a number of cases and developing countries and regions, including: Nepal, Mexico, Southern Africa, Kenya, Moldova and the Philippines.
  • Despite a number of success stories, the authors argue that: “sustained, impactful, scaled-up examples of big and open data in the developing world are still relatively rare,” and, in particular, “Open data has far to go.” They point to the high correlation between readiness, implementation and impact of open data to GDP per capita as evidence of the room for improvement.

Open Data and Open Development

Reilly, Katherine and Juan P. Alperin, “Intermediation in Open Development: A Knowledge Stewardship Approach,” Global Media Journal (Canadian Edition), 2016, http://bit.ly/2atWyI8. 

  • This paper examines the intermediaries that “have emerged to facilitate open data and related knowledge production activities in development processes.”
  • In particular, they study the concept of “knowledge stewardship,” which “demands careful consideration of how—through what arrangements—open resources can best be provided, and how best to maximize the quality, sustainability, buy-in, and uptake of those resources.”
  • The authors describe five models of open data intermediation:
    • Decentralized
    • Arterial
    • Ecosystem
    • Bridging
    • Communities of practice

Reilly, Katherine and Rob McMahon, “Quality of openness: Evaluating the contributions of IDRC’s Information and Networks Program to open development.” International Development Research Centre, January 2015, http://bit.ly/2aD6h0U. 

  • This reports describes the outcomes of IRDC’s Information and Networks (I&N) programme, focusing, in particular, those related to “quality of openness” of initiatives as well as their outcomes.
  • The research program explores “mechanisms that link open initiatives to human activities in ways that generate social innovations of significance to development. These include push factors such as data holders’ understanding of data usage, the preparedness or acceptance of user communities, institutional policies, and wider policies and regulations; as well as pull factors including the awareness, capacity and attitude of users. In other words, openly networked social processes rely on not just quality openness, but also on supportive environments that link open resources and the people who might leverage them to create improvements, whether in governance, education or knowledge production.”

Smith, M. and L. Elder, “Open ICT Ecosystems Transforming the Developing World,” Information Technologies and International Development, 2010, http://bit.ly/2au0qsW.

  • The paper seeks to examine the hypothesis that “open social arrangements, enabled by ICTs, can help to catalyze the development impacts of ICTs. In other words, open ICT ecosystems provide the space for the amplification and transformation of social activities that can be powerful drivers of development.”
  • While the focus is placed on a number of ICT interventions – with open data only directly referenced as it relates to the science community – the lessons learned and overarching framework are applicable to the open data for development space.
  • The authors argue for a new research focus on “the new social activities enabled by different configurations of ICT ecosystems and their connections with particular social outcomes.” They point in particular to “modules of social practices that can be applied to solve similar problems across different development domains,” including “massive participation, collaborative production of content, collaborative innovation, collective information validation, new ‘open’ organizational models, and standards and knowledge transfer.”

Smith, Matthew and Katherine M. A. Reilly (eds), “Open Development: Networked Innovations in International Development,” MIT Press, 2013, http://bit.ly/2atX2hu.

  • This edited volume considers the implications of the emergence of open networked models predicated on digital network technologies for development. In their introduction, the editors emphasize that openness is a means to support development, not an end, which is layered upon existing technological and social structures. While openness is often disruptive, it depends upon some measure of closedness and structure in order to function effectively.
  • Subsequent, separately authored chapters provide case studies of open development drawn from health, biotechnology, and education, and explore some of the political and structural barriers faced by open models.  

van den Broek, Tijs, Marijn Rijken, Sander van Oort, “Towards Open Development Data: A review of open development data from a NGO perspective,” 2012, http://bit.ly/2ap5E8a. 

  • In this paper, the authors seek to answer the question: “What is the status, potential and required next steps of open development data from the perspective of the NGOs?”
  • They argue that “the take-up of open development data by NGOs has shown limited progress in the last few years,” and, offer “several steps to be taken before implementation” to increase the effectiveness of open data’s use by NGOs to improve development efforts:
    • Develop a vision on open development and open data
    • Develop a clear business case
    • Research the benefits and risks of open development data and raise organizational and political awareness and support
    • Develop an appealing business model for data intermediaries and end-users
    • Balance data quality and timeliness
    • Dealing with the data obesity
    • Enrich quantitative data to overcome a quantitative bias
    • Monitor implementation and share best practices.

Open Data and Development Goals

Berdou, Evangelia, “Mediating Voices and Communicating Realities: Using Information Crowdsourcing Tools, Open Data Initiatives and Digital Media to Support and Protect the Vulnerable and Marginalised,” Institute of Development Studies, 2011, http://bit.ly/2aqbycg.

  • This report examines the potential of “open source information crowdsourcing platforms like Ushahidi, and open mapping and data initiatives like OpenStreetMap, are enabling citizens in developing countries to generate and disseminate information critical for their lives and livelihoods.”
  • The authors focus in particular on:
    • “the role of the open source social entrepreneur as a new development actor
    • the complexity of the architectures of participation supported by these platforms and the need to consider them in relation to the decision-making processes that they aim to support and the roles in which they cast citizens
    • the possibilities for cross-fertilisation of ideas and the development of new practices between development practitioners and technology actors committed to working with communities to improve lives and livelihoods.”
  • While the use of ICTs and open data pose numerous potential benefits for supporting and protecting the vulnerable and marginalised, the authors call for greater attention to:
    • challenges emerging from efforts to sustain participation and govern the new information commons in under-resourced and politically contested spaces
    • complications and risks emerging from the desire to share information freely in such contexts
    • gaps between information provision, transparency and accountability, and the slow materialisation of projects’ wider social benefits

Canares, Michael, Satyarupa Shekhar, “Open Data and Sub-national Governments: Lessons from Developing Countries,”  2015, http://bit.ly/2au2gu2. 

  • This synthesis paper seeks to gain a greater understanding of open data’s effects on local contexts – ”where data is collected and stored, where there is strong feasibility that data will be published, and where data can generate the most use and impact” – through the examination of nine papers developed as part of the Open Data in Developing Countries research project.
  • The authors point to three central findings:
    • “There is substantial effort on the part of sub-national governments to proactively disclose data, however, the design delimits citizen participation, and eventually, use.”
    • Context demands different roles for intermediaries and different types of initiatives to create an enabling environment for open data.”
    • “Data quality will remain a critical challenge for sub-national governments in developing countries and it will temper potential impact that open data will be able to generate.

Davies, Tim, “Open Data in Developing Countries – Emerging Insights from Phase I,” ODDC, 2014, http://bit.ly/2aX55UW. 

  • This report synthesizes findings from the Exploring the Emerging Impacts of Open Data in Developing Countries (ODDC) research network and its study of open data initiatives in 13 countries.
  • Davies provides 15 initial insights across the supply, mediation, and use of open data, including:
    • Open data initiatives can create new spaces for civil society to pursue government accountability and effectiveness;
    • Intermediaries are vital to both the supply and the use of open data; and
    • Digital divides create data divides in both the supply and use of data.

Davies, Tim, Duncan Edwards, “Emerging Implications of Open and Linked Data for Knowledge Sharing Development,” IDS Bulletin, 2012, http://bit.ly/2aLKFyI. 

  • This article explores “issues that development sector knowledge intermediaries may need to engage with to ensure the socio-technical innovations of open and linked data work in the interests of greater diversity and better development practice.”
  • The authors explore a number of case studies where open and linked data was used in a development context, including:
    • Open research: IDS and R4D meta-data
    • Open aid: International Aid Transparency Initiative
    • Open linked statistics: Young Lives
  • Based on lessons learned from these cases, the authors argue that “openness must serve the interests of marginalised and poor people. This is pertinent at three levels:
    • practices in the publication and communication of data
    • capacities for, and approaches to, the use of data
    • development and emergent structuring of open data ecosystems.

Davies, Tim, Fernando Perini, and Jose Alonso, “Researching the Emerging Impacts of Open Data,” ODDC, 2013, http://bit.ly/2aqb6uP. 

  • This research report offers a conceptual framework for open data, with a particular focus on open data in developing countries.
  • The conceptual framework comprises three central elements:
    • Open Data
      • About government
      • About companies & markets
      • About citizens
    • Domains of governance
      • Political domains
      • Economic domains
      • Social domains
    • Emerging Outcomes
      • Transparency & accountability
      • Innovation & economic growth
      • Inclusion & empowerment
  • The authors describe three central theories of change related to open data’s impacts:
    • Open data will bring about greater transparency in government, which in turn brings about greater accountability of key actors to make decisions and apply rules in the public interest;
    • Open data will enable non-state innovators to improve public services or build innovative products and services with social and economic value; open data will shift certain decision making from the state into the market, making it more efficient;
    • Open data will remove power imbalances that resulted from asymmetric information, and will bring new stakeholders into policy debates, giving marginalised groups a greater say in the creation and application of rules and policy.

Montano, Elise and Diogo Silva, “Exploring the Emerging Impacts of Open Data in Developing Countries (ODDC): ODDC1 Follow-up Outcome Evaluation Report,” ODDC, 2016, http://bit.ly/2au65z7.

  • This report summarizes the findings of a two and a half year research-driven project sponsored by the World Wide Web Foundation to explore how open data improves governance in developing countries, and build capacity in these countries to engage with open data. The research was conducted through 17 subgrants to partners from 12 countries.
  • Upon evaluation in 2014, partners reported increased capacity and expertise in dealing with open data; empowerment in influencing local and regional open data trends, particularly among CSOs; and increased understanding of open data among policy makers with whom the partners were in contact.

Smith, Fiona, William Gerry, Emma Truswell, “Supporting Sustainable Development with Open Data,” Open Data Institute, 2015, http://bit.ly/2aJwxsF. 

  • This report describes the potential benefits, challenges and next steps for leveraging open data to advance the Sustainable Development Goals.
  • The authors argue that the greatest potential impacts of open data on development are:
    • More effectively target aid money and improve development programmes
    • Track development progress and prevent corruption
    • Contribute to innovation, job creation and economic growth.
  • They note, however, that many challenges to such impact exist, including:
    • A weak enabling environment for open data publishing
    • Poor data quality
    • A mismatch between the demand for open data and the supply of appropriate datasets
    • A ‘digital divide’ between rich and poor, affecting both the supply and use of data
    • A general lack of quantifiable data and metrics.
  • The report articulates a number of ways that “governments, donors and (international) NGOs – with the support of researchers, civil society and industry – can apply open data to help make the SDGs a reality:
    • Reach global consensus around principles and standards, namely being ‘open by default’, using the Open Government Partnership’s Open Data Working Group as a global forum for discussion.
    • Embed open data into funding agreements, ensuring that relevant, high-quality data is collected to report against the SDGs. Funders should mandate that data relating to performance of services, and data produced as a result of funded activity, be released as open data.
    • Build a global partnership for sustainable open data, so that groups across the public and private sectors can work together to build sustainable supply and demand for data in the developing world.”

The World Bank, “Open Data for Sustainable Development,” Policy Note, August 2015, http://bit.ly/2aGjaJ4. 

  • This report from the World Bank seeks to describe open data’s potential for achieving the Sustainable Development Goals, and makes a number of recommendations toward that end.
  • The authors describe four key benefits of open data use for developing countries:
    • Foster economic growth and job creation
    • Improve efficiency, effectiveness and coverage of public services
    • Increase transparency, accountability, and citizen participation
    • Facilitate better information sharing within government
  • The paper concludes with a number of recommendations for improving open data programs, including:
    • Support Open Data use through legal and licensing frameworks.
    • Make data available for free online.
    • Publish data inventories for the government’s data resources.
    • Create feedback channels to government from current and potential data users.
    • Prioritize the datasets that users want.

Open Data and Developing Countries (National Case Studies)

Beghin, Nathalie and Carmela Zigoni, “Measuring Open Data’s Impact on Brazilian National and Sub-National Budget Transparency Websites and Its Impacts on People’s Rights,” 2014, http://bit.ly/2au3LaQ.

  • This report examines the impact of a Brazilian law requiring government entities to “provide real-time information on their budgets and spending through electronic means.” The authors explore “whether the national and state capitals are in fact using principles and practices of open data in their disclosures, and has evaluated the emerging impacts of open budget data disclosed through the national transparency portal.”
  • The report leveraged a “quantitative survey of budget and financial disclosures, and qualitative research with key stakeholders” to explore the “role of technical platforms and intermediaries in supporting the use of budget data by groups working in pursuit of social change and human rights.”
  • The survey found that:
    • The information provided is complete
    • In general, the data are not primary
    • Most governments do not provide timely information
    • Access to information is not ensured to all individuals
    • Advances were observed in terms of the availability of machine-processable data
    • Access is free, without discriminating users
    • The minority presents data in non-proprietary format
    • It is not known whether the data are under license

Boyera, S., C. Iglesias, “Open Data in Developing Countries: State of the Art,” Partnership for Open Data, 2014, http://bit.ly/2acBMR7. 

  • This report provides a summary of the State-of-the-Art study developed by SBC4D for the Partnership for Open Data (POD).
  • A series of interviews and responses to an online questionnaire yielded a number of findings, including:
    • “The number of actors interested in Open Data in Developing Countries is growing quickly. The study has identified 160+ organizations. It is important to note that a majority of them are just engaging in the domain and have little past experience. Most of these actors are focused on OD as an objective not a tool or means to increase impact or outcome.
    • Local actors are strong advocates of public data release. Lots of them are also promoting the re-use of existing data (through e.g. the organization of training, hackathons and alike). However, the study has not identified many actors practically using OD in their work or engaged in releasing their own data.
    • Traditional development sectors (health, education, agriculture, energy, transport) are not yet the target of many initiatives, and are clearly underdeveloped in terms of use-cases.
    • There is very little connection between horizontal (e.g. national OD initiatives) and vertical (sector-specific initiatives on e.g. extractive industry, or disaster management) activities”

Canares, M.P., J. de Guia, M. Narca, J. Arawiran, “Opening the Gates: Will Open Data Initiatives Make Local Governments in the Philippines More Transparent?” Open LGU Research Project, 2014, http://bit.ly/2au3Ond. 

  • This paper seeks to determine the impacts of the Department of Interior and Local Government of the Philippines’ Full Disclosure Policy, affecting financial and procurement data, on both data providers and data users.
  • The paper uncovered two key findings:
    • “On the supply side, incentivising openness is a critical aspect in ensuring that local governments have the interest to disclose financial data. While at this stage, local governments are still on compliance behaviour, it encourages the once reluctant LGUs to disclose financial information in the use of public funds, especially when technology and institutional arrangements are in place. However, LGUs do not make an effort to inform the public that information is available online and has not made data accessible in such a way that it can allow the public to perform computations and analysis. Currently, no data standards have been made yet by the Philippine national government in terms of format and level of detail.”
    • “On the demand side, there is limited awareness on the part of the public, and more particularly the intermediaries (e.g. business groups, civil society organizations, research institutions), on the availability of data, and thus, its limited use. As most of these data are financial in nature, it requires a certain degree of competence and expertise so that they will be able to make use of the data in demanding from government better services and accountability.”
  • The authors argue that “openness is not just about governments putting meaningful government data out into the public domain, but also about making the public meaningfully engage with governments through the use of open government data.” In order to do that, policies should “require observance of open government data standards and a capacity building process of ensuring that the public, to whom the data is intended, are aware and able to use the data in ensuring more transparent and accountable governance.”

Canares, M., M. Narca, and D. Marcial, “Enhancing Citizen Engagement Through Open Government Data,” ODDC, 2015, http://bit.ly/2aJMhfS. 

  • This research paper seeks to gain a greater understanding of how civil society organizations can increase or initiate their use of open data. The study is based on research conducted in “two provinces in the Philippines where civil society organizations in Negros Oriental province were trained, and in the Bohol province were mentored on accessing and using open data.
  • The authors seek to answer three central research questions:
    • What do CSOs know about open government data? What do they know about government data that their local governments are publishing in the web?
    • What do CSOs have in terms of skills that would enable them to engage meaningfully with open government data?
    • How best can capacity building be delivered to civil society organizations to ensure that they learn to access and use open government data to improve governance?
  • They provide a number of key lessons, including:
    • Baseline condition should inform capacity building approach
    • Data use is dependent on data supply
    • Open data requires accessible and stable internet connection
    • Open data skills are important but insufficient
    • Outcomes, and not just outputs, prove capacity improvements

Chattapadhyay, Sumandro, “Opening Government Data through Mediation: Exploring the Roles, Practices and Strategies of Data Intermediary Organisations in India,” ODDC, 2014, http://bit.ly/2au3F37. 

  • This report seeks to gain a greater understanding of the current practice following the Government of India’s 2012 National Data Sharing and Accessibility Policy.
  • Cattapadhyay examines the open government data practices of “various (non-governmental) ‘data intermediary organisations’ on the one hand, and implementation challenges faced by managers of the Open Government Data Platform of India on the other.
  • The report’s objectives are:
    • To undertake a provisional mapping of government data related activities across different sectors to understand the nature of the “open data community” in India,
    • To enrich government data/information policy discussion in India by gathering evidence and experience of (non­governmental) data intermediaries regarding their actual practices of accessing and sharing government data, and their utilisation of the provisions of NDSAP and RTI act, and
    • To critically reflect on the nature of open data practices in India.

Chiliswa, Zacharia, “Open Government Data for Effective Public Participation: Findings of a Case Study Research Investigating The Kenya’s Open Data Initiative in Urban Slums and Rural Settlements,” ODDC, April 2014, http://bit.ly/2au8E4s. 

  • This research report is the product of a study of two urban slums and a rural settlement in Nairobi, Mobasa and Isiolo County, respectively, aimed at gaining a better understanding of the awareness and use of Kenya’s open data.
  • The study had four organizing objectives:
    • “Investigate the impact of the Kenyan Government’s open data initiative and to see whether, and if so how, it is assisting marginalized communities and groups in accessing key social services and information such as health and education;
    • Understand the way people use the information provided by the Open Data Initiative;
    • Identify people’s trust in the information and how it can assist their day-to-day lives;
    • Examine ways in which the public wish for the open data initiative to improve, particularly in relation to governance and service delivery.”
  • The study uncovered four central findings about Kenya’s open data initiative:
    • “There is a mismatch between the data citizens want to have and the data the Kenya portal and other intermediaries have provided.
    • Most people go to local information intermediaries instead of going directly to the government data portals and that there are few connections between these intermediaries and the wider open data sources.
    • Currently the rural communities are much less likely to seek out government information.
    • The kinds of data needed to support service delivery in Kenya may be different from those needed in other places in the world.”

Lwanga-Ntale, Charles, Beatrice Mugambe, Bernard Sabiti, Peace Nganwa, “Understanding how open data could impact resource allocation for poverty eradication in Kenya and Uganda,” ODDC, 2014, http://bit.ly/2aHqYKi. 

  • This paper explores case studies from Uganda and Kenya to explore an open data movement seeking to address “age-old” issues including “transparency, accountability, equity, and the relevance, effectiveness and efficiency of governance.”
  • The authors focus both on the role “emerging open data processes in the two countries may be playing in promoting citizen/public engagement and the allocation of resources,” and the “possible negative impacts that may emerge due to the ‘digital divide’ between those who have access to data (and technology) and those who do not.
  • They offer a number of recommendations to the government of Uganda and Kenya that could be more broadly applicable, including:
    • Promote sector and cross sector specific initiatives that enable collaboration and transparency through different e-transformation strategies across government sectors and agencies.
    • Develop and champion the capacity to drive transformation across government and to advance skills in its institutions and civil service.

Sapkota, Krishna, “Exploring the emerging impacts of open aid data and budget data in Nepal,” Freedom Forum, August 2014, http://bit.ly/2ap0z5G. 

  • This research report seeks to answer a five key questions regarding the opening of aid and budget data in Nepal:
    • What is the context for open aid and budget data in Nepal?
    • What sorts of budget and aid information is being made available in Nepal?
    • What is the governance of open aid and budget data in Nepal?
    • How are relevant stakeholders making use of open aid and budget data in Nepal?
    • What are the emerging impacts of open aid and budget data in Nepal?
  • The study uncovered a number of findings, including
    • “Information and data can play an important role in addressing key social issues, and that whilst some aid and budget data is increasingly available, including in open data formats, there is not yet a sustainable supply of open data direct from official sources that meet the needs of the different stakeholders we consulted.”
    • “Expectations amongst government, civil society, media and private sector actors that open data could be a useful resource in improving governance, and we found some evidence of media making use of data to drive stories more when they had the right skills, incentives and support.”
    • “The context of Nepal also highlights that a more critical perspective may be needed on the introduction of open data, understanding the specific opportunities and challenges for open data supply and use in a country that is currently undergoing a period of constitutional development, institution building and deepening democracy.”

Srivastava, Nidhi, Veena Agarwal, Anmol Soni, Souvik Bhattacharjya, Bibhu P. Nayak, Harsha Meenawat, Tarun Gopalakrishnan, “Open government data for regulation of energy resources in India,”ODDC, 2014, http://bit.ly/2au9oXf. 

  • This research paper examines “the availability, accessibility and use of open data in the extractive energy industries sector in India.”
  • The authors describe a number of challenges being faced by:
    • Data suppliers and intermediaries:
      • Lack of clarity on mandate
      • Agency specific issues
      • Resource challenges
      • Privacy issues of commercial data and contractual constraints
      • Formats for data collection
      • Challenges in providing timely data
      • Recovery of costs and pricing of data
    • Data users
      • Data available but inaccessible
      • Data accessible but not usable
      • Timeliness of data
  • They make a number of recommendations for addressing these challenges focusing on:
    • Policy measures
    • Improving data quality
    • Improving effectiveness of data portal

van Schalkwyk, François, Michael Caňares, Sumandro Chattapadhyay and Alexander Andrason “Open Data Intermediaries in Developing Countries,” ODDC, 2015, http://bit.ly/2aJztWi. 

  • This paper seeks to provide “a more socially nuanced approach to open data intermediaries,” moving beyond the traditional approach wherein data intermediaries are “presented as single and simple linkages between open data supply and use.”
  • The study’s analysis draws on cases from the Emerging Impacts of Open Data in Developing Countries (ODDC) project.
  • The authors provide a working definition of open data intermediaries: An open data intermediary is an agent:
    • positioned at some point in a data supply chain that incorporates an open dataset,
    • positioned between two agents in the supply chain, and
    • facilitates the use of open data that may otherwise not have been the case.
  • One of the studies key findings is that, “Intermediation does not only consist of a single agent facilitating the flow of data in an open data supply chain; multiple intermediaries may operate in an open data supply chain, and the presence of multiple intermediaries may increase the probability of use (and impact) because no single intermediary is likely to possess all the types of capital required to unlock the full value of the transaction between the provider and the user in each of the fields in play.”

van Schalkwyk, François, Michelle Willmers and Tobias Schonwetter, “Embedding Open Data Practice,” ODDC, 2015, http://bit.ly/2aHt5xu. 

  • This research paper was developed as part of the ODDC Phase 2 project and seeks to address the “insufficient attention paid to the institutional dynamics within governments and how these may be impeding open data practice.”
  • The study focuses in particular on open data initiatives in South Africa and Kenya, leveraging a conceptual framework to allow for meaningful comparison between the two countries.
  • Focusing on South Africa and Kenya, as well as Africa as a whole, the authors seek to address four central research questions:
    • Is open data practice being embedded in African governments?
    • What are the possible indicators of open data practice being embedded?
    • What do the indicators reveal about resistance to or compliance with pressures to adopt open data practice?
    • What are different effects of multiple institutional domains that may be at play in government as an organisation?

van Schalkwyk, Francois, Michelle Willmers, and Laura Czerniewicz, “Case Study: Open Data in the Governance of South African Higher Education,” ODDC, 2014, http://bit.ly/2amgIFb. 

  • This research report uses the South African Centre for Higher Education Transformation (CHET) open data platform as a case study to examine “the supply of and demand for open data as well as the roles of intermediaries in the South African higher education governance ecosystem.
  • The report’s findings include:
    • “There are concerns at both government and university levels about how data will be used and (mis)interpreted, and this may constrain future data supply. Education both at the level of supply (DHET) and at the level of use by the media in particular on how to improve the interpretability of data could go some way in countering current levels of mistrust. Similar initiatives may be necessary to address uneven levels of data use and trust apparent across university executives and councils.”
    • “Open data intermediaries increase the accessibility and utility of data. While there is a rich publicly-funded dataset on South African higher education, the data remains largely inaccessible and unusable to universities and researchers in higher education studies. Despite these constraints, the findings show that intermediaries in the ecosystem are playing a valuable role in making the data both available and useable.”
    • “Open data intermediaries provide both supply-side as well as demand-side value. CHET’s work on higher education performance indicators was intended not only to contribute to government’s steering mechanisms, but also to contribute to the governance capacity of South African universities. The findings support the use of CHET’s open data to build capacity within universities. Further research is required to confirm the use of CHET data in state-steering of the South African higher education system, although there is some evidence of CHET’s data being referenced in national policy documents.”

Verhulst, Stefaan and Andrew Young, “Open Data Impact: When Demand Supply Meet,” The GovLab, 2016, http://bit.ly/1LHkQPO. 

  • This report provides a taxonomy of the impacts open data is having on a number of countries around the world, comprising:
    • Improving Government
    • Empowering Citizens
    • Creating Opportunity
    • Solving Public Problems
  • The authors describe four key enabling conditions for creating impactful open data initiatives:
    • Partnerships
    • Public Infrastructure
    • Policies and Performance Metrics
    • Problem Definition

Additional Resource:
World Bank Readiness Assessment Tool

  • To aid in the assessment “of the readiness of a government or individual agency to evaluate, design and implement an Open Data initiative,” the World Bank’s Open Government Data Working Group developed an openly accessible Open Data Readiness Assessment (ODRA) tool.

Soft Data and Public Policy: Can Social Media Offer Alternatives to Official Statistics in Urban Policymaking?

Curated on Posted on by Stefaan Verhulst

Marta Severo, Amel Feredj and Alberto Romele in Policy & Internet: “In recent years, decision makers have reported difficulties in the use of official statistics in public policy: excessively long publication delays, insufficient coverage of topics of interest, and the top-down process of data creation. The deluge of data available online represents a potential answer to these problems, with social media data in particular as a possible alternative to traditional data. In this article, we propose a definition of “Soft Data” to indicate data that are freely available on the Internet, and that are not controlled by a public administration but rather by public or private actors. The term Soft Data is not intended to replace those of “Big Data” and “Open Data,” but rather to highlight specific properties and research methods required to convert them into information of interest for decision makers. The analysis is based on a case study of Twitter data for urban policymaking carried out for a European research program aimed at enhancing the effectiveness of European cohesion policy. The article explores methodological issues and the possible impact of “Soft Data” on public policy, reporting on semistructured interviews carried out with nine European policymakers….(More)”

Data as a Means, Not an End: A Brief Case Study

Curated on Posted on by Stefaan Verhulst

Tracie Neuhaus & Jarasa Kanok  in the Stanford Social Innovation Review: “In 2014, City Year—the well-known national education nonprofit that leverages young adults in national service to help students and schools succeed—was outgrowing the methods it used for collecting, managing, and using performance data. As the organization established its strategy for long-term impact, leaders identified a business problem: The current system for data collection and use would need to evolve to address the more-complex challenges the organization was undertaking. Staff throughout the organization were citing pain points one might expect, including onerous manual data collection, and long lag times to get much-needed data and reports on student attendance, grades, and academic and social-emotional assessments. After digging deeper, leaders realized they couldn’t fix the organization’s challenges with technology or improved methods without first addressing more fundamental issues. They saw City Year lacked a common “language” for the data it collected and used. Staff varied widely in their levels of data literacy, as did the scope of data-sharing agreements with the 27 urban school districts where City Year was working at the time. What’s more, its evaluation group had gradually become a default clearinghouse for a wide variety of service requests from across the organization that the group was neither designed nor staffed to address. The situation was much more complex than it appeared.

With significant technology roadmap decisions looming, City Year engaged with us to help it develop its data strategy. Together we came to realize that these symptoms were reflective of a single issue, one that exists in many organizations: City Year’s focus on data wasn’t targeted to address the very different kinds of decisions that each staff member—from the front office to the front lines—needed to make. …

Many of us in the social sector have probably seen elements of this dynamic. Many organizations create impact reports designed to satisfy external demands from donors, but these reports have little relevance to the operational or strategic choices the organizations face every day, much less address harder-to-measure, system-level outcomes. As a result, over time and in the face of constrained resources, measurement is relegated to a compliance activity, disconnected from identifying and collecting the information that directly enables individuals within the organization to drive impact. Gathering data becomes an end in itself, rather than a means of enabling ground-level work and learning how to improve the organization’s impact.

Overcoming this all-too-common “measurement drift” requires that we challenge the underlying orthodoxies that drive it and reorient measurement activities around one simple premise: Data should support better decision-making. This enables organizations to not only shed a significant burden of unproductive activity, but also drive themselves to new heights of performance.

In the case of City Year, leaders realized that to really take advantage of existing technology platforms, they needed a broader mindset shift….(More)”

Research in the Crowdsourcing Age, a Case Study

Curated on Posted on by Stefaan Verhulst

Report by  (Pew): “How scholars, companies and workers are using Mechanical Turk, a ‘gig economy’ platform, for tasks computers can’t handle

How Mechanical Turk WorksDigital age platforms are providing researchers the ability to outsource portions of their work – not just to increasingly intelligent machines, but also to a relatively low-cost online labor force comprised of humans. These so-called “online outsourcing” services help employers connect with a global pool of free-agent workers who are willing to complete a variety of specialized or repetitive tasks.

Because it provides access to large numbers of workers at relatively low cost, online outsourcing holds a particular appeal for academics and nonprofit research organizations – many of whom have limited resources compared with corporate America. For instance, Pew Research Center has experimented with using these services to perform tasks such as classifying documents and collecting website URLs. And a Google search of scholarly academic literature shows that more than 800 studies – ranging from medical research to social science – were published using data from one such platform, Amazon’s Mechanical Turk, in 2015 alone.1

The rise of these platforms has also generated considerable commentary about the so-called “gig economy” and the possible impact it will have on traditional notions about the nature of work, the structure of compensation and the “social contract” between firms and workers. Pew Research Center recently explored some of the policy and employment implications of these new platforms in a national survey of Americans.

Proponents say this technology-driven innovation can offer employers – whether companies or academics – the ability to control costs by relying on a global workforce that is available 24 hours a day to perform relatively inexpensive tasks. They also argue that these arrangements offer workers the flexibility to work when and where they want to. On the other hand, some critics worry this type of arrangement does not give employees the same type of protections offered in more traditional work environments – while others have raised concerns about the quality and consistency of data collected in this manner.

A recent report from the World Bank found that the online outsourcing industry generated roughly $2 billion in 2013 and involved 48 million registered workers (though only 10% of them were considered “active”). By 2020, the report predicted, the industry will generate between $15 billion and $25 billion.

Amazon’s Mechanical Turk is one of the largest outsourcing platforms in the United States and has become particularly popular in the social science research community as a way to conduct inexpensive surveys and experiments. The platform has also become an emblem of the way that the internet enables new businesses and social structures to arise.

In light of its widespread use by the research community and overall prominence within the emerging world of online outsourcing, Pew Research Center conducted a detailed case study examining the Mechanical Turk platform in late 2015 and early 2016. The study utilizes three different research methodologies to examine various aspects of the Mechanical Turk ecosystem. These include human content analysis of the platform, a canvassing of Mechanical Turk workers and an analysis of third party data.

The first goal of this research was to understand who uses the Mechanical Turk platform for research or business purposes, why they use it and who completes the work assignments posted there. To evaluate these issues, Pew Research Center performed a content analysis of the tasks posted on the site during the week of Dec. 7-11, 2015.

A second goal was to examine the demographics and experiences of the workers who complete the tasks appearing on the site. This is relevant not just to fellow researchers that might be interested in using the platform, but as a snapshot of one set of “gig economy” workers. To address these questions, Pew Research Center administered a nonprobability online survey of Turkers from Feb. 9-25, 2016, by posting a task on Mechanical Turk that rewarded workers for answering questions about their demographics and work habits. The sample of 3,370 workers contains any number of interesting findings, but it has its limits. This canvassing emerges from an opt-in sample of those who were active on MTurk during this particular period, who saw our survey and who had the time and interest to respond. It does not represent all active Turkers in this period or, more broadly, all workers on MTurk.

Finally, this report uses data collected by the online tool mturk-tracker, which is run by Dr. Panagiotis G. Ipeirotis of the New York University Stern School of Business, to examine the amount of activity occurring on the site. The mturk-tracker data are publically available online, though the insights presented here have not been previously published elsewhere….(More)”

Smart Cities – International Case Studies

Curated on Posted on by Stefaan Verhulst

“These case studies were developed by the Inter-American Development Bank (IDB), in association with the Korea Research Institute for Human Settlements (KRIHS).

Anyang, Korea Anyang, a 600,000 population city near Seoul is developing international recognition on its smart city project that has been implemented incrementally since 2003. This initiative began with the Bus Information System to enhance citizen’s convenience at first, and has been expanding its domain into wider Intelligent Transport System as well as crime and disaster prevention in an integrated manner. Anyang is considered a benchmark for smart city with a 2012 Presidential Award in Korea and receives large number of international visits. Anyang’s Integrated Operation and Control Center (IOCC) acts as the platform that gathers, analyzes and distributes information for mobility, disasters management and crime. Anyang is currently utilizing big data for policy development and is continuing its endeavor to expand its smart city services into areas such as waste and air quality management. Download Anyang case study

Medellín, Colombia Medellin is a city that went from being known for its security problems to being an international referent of technological and social innovation, urban transformation, equity, and citizen participation. This report shows how Medellin has implemented a series of strategies that have made it a smart city that is developing capacity and organic structure in the entities that control mobility, the environment, and security. In addition, these initiatives have created mechanisms to communicate and interact with citizens in order to promote continuous improvement of smart services.

Through the Program “MDE: Medellin Smart City,” Medellin is implementing projects to create free Internet access zones, community centers, a Mi-Medellin co-creation portal, open data, online transactions, and other services. Another strategy is the creation of the Smart Mobility System which, through the use of technology, has achieved a reduction in the number of accidents, improvement in mobility, and a reduction in incident response time. Download Medellin case study

Namyangju, Korea…

Orlando, U.S.…

Pangyo, Korea…

Rio de Janeiro, Brazil… 

Santander, España…

Singapore…

Songdo, Korea…

Tel Aviv, Israel… (More)”

Selected Readings on Data Collaboratives

Curated on Posted on by Andrew Young

By Neil Britto, David Sangokoya, Iryna Susha, Stefaan Verhulst and Andrew Young

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 collaboratives was originally published in 2017.

The term data collaborative refers to a new form of collaboration, beyond the public-private partnership model, in which participants from different sectors (including private companies, research institutions, and government agencies ) can exchange data to help solve public problems. Several of society’s greatest challenges — from addressing climate change to public health to job creation to improving the lives of children — require greater access to data, more collaboration between public – and private-sector entities, and an increased ability to analyze datasets. In the coming months and years, data collaboratives will be essential vehicles for harnessing the vast stores of privately held data toward the public good.

Selected Reading List (in alphabetical order)

Annotated Selected Readings List (in alphabetical order)

Agaba, G., Akindès, F., Bengtsson, L., Cowls, J., Ganesh, M., Hoffman, N., . . . Meissner, F. “Big Data and Positive Social Change in the Developing World: A White Paper for Practitioners and Researchers.” 2014. http://bit.ly/25RRC6N.

  • This white paper, produced by “a group of activists, researchers and data experts” explores the potential of big data to improve development outcomes and spur positive social change in low- and middle-income countries. Using examples, the authors discuss four areas in which the use of big data can impact development efforts:
    • Advocating and facilitating by “opening[ing] up new public spaces for discussion and awareness building;
    • Describing and predicting through the detection of “new correlations and the surfac[ing] of new questions;
    • Facilitating information exchange through “multiple feedback loops which feed into both research and action,” and
    • Promoting accountability and transparency, especially as a byproduct of crowdsourcing efforts aimed at “aggregat[ing] and analyz[ing] information in real time.
  • The authors argue that in order to maximize the potential of big data’s use in development, “there is a case to be made for building a data commons for private/public data, and for setting up new and more appropriate ethical guidelines.”
  • They also identify a number of challenges, especially when leveraging data made accessible from a number of sources, including private sector entities, such as:
    • Lack of general data literacy;
    • Lack of open learning environments and repositories;
    • Lack of resources, capacity and access;
    • Challenges of sensitivity and risk perception with regard to using data;
    • Storage and computing capacity; and
    • Externally validating data sources for comparison and verification.

Ansell, C. and Gash, A. “Collaborative Governance in Theory and Practice.” Journal of Public Administration Research and  Theory 18 (4), 2008. http://bit.ly/1RZgsI5.

  • This article describes collaborative arrangements that include public and private organizations working together and proposes a model for understanding an emergent form of public-private interaction informed by 137 diverse cases of collaborative governance.
  • The article suggests factors significant to successful partnering processes and outcomes include:
    • Shared understanding of challenges,
    • Trust building processes,
    • The importance of recognizing seemingly modest progress, and
    • Strong indicators of commitment to the partnership’s aspirations and process.
  • The authors provide a ‘’contingency theory model’’ that specifies relationships between different variables that influence outcomes of collaborative governance initiatives. Three “core contingencies’’ for successful collaborative governance initiatives identified by the authors are:
    • Time (e.g., decision making time afforded to the collaboration);
    • Interdependence (e.g., a high degree of interdependence can mitigate negative effects of low trust); and
    • Trust (e.g. a higher level of trust indicates a higher probability of success).

Ballivian A, Hoffman W. “Public-Private Partnerships for Data: Issues Paper for Data Revolution Consultation.” World Bank, 2015. Available from: http://bit.ly/1ENvmRJ

  • This World Bank report provides a background document on forming public-prviate partnerships for data with the private sector in order to inform the UN’s Independent Expert Advisory Group (IEAG) on sustaining a “data revolution” in sustainable development.
  • The report highlights the critical position of private companies within the data value chain and reflects on key elements of a sustainable data PPP: “common objectives across all impacted stakeholders, alignment of incentives, and sharing of risks.” In addition, the report describes the risks and incentives of public and private actors, and the principles needed to “build[ing] the legal, cultural, technological and economic infrastructures to enable the balancing of competing interests.” These principles include understanding; experimentation; adaptability; balance; persuasion and compulsion; risk management; and governance.
  • Examples of data collaboratives cited in the report include HP Earth Insights, Orange Data for Development Challenges, Amazon Web Services, IBM Smart Cities Initiative, and the Governance Lab’s Open Data 500.

Brack, Matthew, and Tito Castillo. “Data Sharing for Public Health: Key Lessons from Other Sectors.” Chatham House, Centre on Global Health Security. April 2015. Available from: http://bit.ly/1DHFGVl

  • The Chatham House report provides an overview on public health surveillance data sharing, highlighting the benefits and challenges of shared health data and the complexity in adapting technical solutions from other sectors for public health.
  • The report describes data sharing processes from several perspectives, including in-depth case studies of actual data sharing in practice at the individual, organizational and sector levels. Among the key lessons for public health data sharing, the report strongly highlights the need to harness momentum for action and maintain collaborative engagement: “Successful data sharing communities are highly collaborative. Collaboration holds the key to producing and abiding by community standards, and building and maintaining productive networks, and is by definition the essence of data sharing itself. Time should be invested in establishing and sustaining collaboration with all stakeholders concerned with public health surveillance data sharing.”
  • Examples of data collaboratives include H3Africa (a collaboration between NIH and Wellcome Trust) and NHS England’s care.data programme.

de Montjoye, Yves-Alexandre, Jake Kendall, and Cameron F. Kerry. “Enabling Humanitarian Use of Mobile Phone Data.” The Brookings Institution, Issues in Technology Innovation. November 2014. Available from: http://brook.gs/1JxVpxp

  • Using Ebola as a case study, the authors describe the value of using private telecom data for uncovering “valuable insights into understanding the spread of infectious diseases as well as strategies into micro-target outreach and driving update of health-seeking behavior.”
  • The authors highlight the absence of a common legal and standards framework for “sharing mobile phone data in privacy-conscientious ways” and recommend “engaging companies, NGOs, researchers, privacy experts, and governments to agree on a set of best practices for new privacy-conscientious metadata sharing models.”

Eckartz, Silja M., Hofman, Wout J., Van Veenstra, Anne Fleur. “A decision model for data sharing.” Vol. 8653 LNCS. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2014. http://bit.ly/21cGWfw.

  • This paper proposes a decision model for data sharing of public and private data based on literature review and three case studies in the logistics sector.
  • The authors identify five categories of the barriers to data sharing and offer a decision model for identifying potential interventions to overcome each barrier:
    • Ownership. Possible interventions likely require improving trust among those who own the data through, for example, involvement and support from higher management
    • Privacy. Interventions include “anonymization by filtering of sensitive information and aggregation of data,” and access control mechanisms built around identity management and regulated access.  
    • Economic. Interventions include a model where data is shared only with a few trusted organizations, and yield management mechanisms to ensure negative financial consequences are avoided.
    • Data quality. Interventions include identifying additional data sources that could improve the completeness of datasets, and efforts to improve metadata.
    • Technical. Interventions include making data available in structured formats and publishing data according to widely agreed upon data standards.

Hoffman, Sharona and Podgurski, Andy. “The Use and Misuse of Biomedical Data: Is Bigger Really Better?” American Journal of Law & Medicine 497, 2013. http://bit.ly/1syMS7J.

  • This journal articles explores the benefits and, in particular, the risks related to large-scale biomedical databases bringing together health information from a diversity of sources across sectors. Some data collaboratives examined in the piece include:
    • MedMining – a company that extracts EHR data, de-identifies it, and offers it to researchers. The data sets that MedMining delivers to its customers include ‘lab results, vital signs, medications, procedures, diagnoses, lifestyle data, and detailed costs’ from inpatient and outpatient facilities.
    • Explorys has formed a large healthcare database derived from financial, administrative, and medical records. It has partnered with major healthcare organizations such as the Cleveland Clinic Foundation and Summa Health System to aggregate and standardize health information from ten million patients and over thirty billion clinical events.
  • Hoffman and Podgurski note that biomedical databases populated have many potential uses, with those likely to benefit including: “researchers, regulators, public health officials, commercial entities, lawyers,” as well as “healthcare providers who conduct quality assessment and improvement activities,” regulatory monitoring entities like the FDA, and “litigants in tort cases to develop evidence concerning causation and harm.”
  • They argue, however, that risks arise based on:
    • The data contained in biomedical databases is surprisingly likely to be incorrect or incomplete;
    • Systemic biases, arising from both the nature of the data and the preconceptions of investigators are serious threats the validity of research results, especially in answering causal questions;
  • Data mining of biomedical databases makes it easier for individuals with political, social, or economic agendas to generate ostensibly scientific but misleading research findings for the purpose of manipulating public opinion and swaying policymakers.

Krumholz, Harlan M., et al. “Sea Change in Open Science and Data Sharing Leadership by Industry.” Circulation: Cardiovascular Quality and Outcomes 7.4. 2014. 499-504. http://1.usa.gov/1J6q7KJ

  • This article provides a comprehensive overview of industry-led efforts and cross-sector collaborations in data sharing by pharmaceutical companies to inform clinical practice.
  • The article details the types of data being shared and the early activities of GlaxoSmithKline (“in coordination with other companies such as Roche and ViiV”); Medtronic and the Yale University Open Data Access Project; and Janssen Pharmaceuticals (Johnson & Johnson). The article also describes the range of involvement in data sharing among pharmaceutical companies including Pfizer, Novartis, Bayer, AbbVie, Eli Llly, AstraZeneca, and Bristol-Myers Squibb.

Mann, Gideon. “Private Data and the Public Good.” Medium. May 17, 2016. http://bit.ly/1OgOY68.

    • This Medium post from Gideon Mann, the Head of Data Science at Bloomberg, shares his prepared remarks given at a lecture at the City College of New York. Mann argues for the potential benefits of increasing access to private sector data, both to improve research and academic inquiry and also to help solve practical, real-world problems. He also describes a number of initiatives underway at Bloomberg along these lines.    
  • Mann argues that data generated at private companies “could enable amazing discoveries and research,” but is often inaccessible to those who could put it to those uses. Beyond research, he notes that corporate data could, for instance, benefit:
      • Public health – including suicide prevention, addiction counseling and mental health monitoring.
    • Legal and ethical questions – especially as they relate to “the role algorithms have in decisions about our lives,” such as credit checks and resume screening.
  • Mann recognizes the privacy challenges inherent in private sector data sharing, but argues that it is a common misconception that the only two choices are “complete privacy or complete disclosure.” He believes that flexible frameworks for differential privacy could open up new opportunities for responsibly leveraging data collaboratives.

Pastor Escuredo, D., Morales-Guzmán, A. et al, “Flooding through the Lens of Mobile Phone Activity.” IEEE Global Humanitarian Technology Conference, GHTC 2014. Available from: http://bit.ly/1OzK2bK

  • This report describes the impact of using mobile data in order to understand the impact of disasters and improve disaster management. The report was conducted in the Mexican state of Tabasco in 2009 as a multidisciplinary, multi-stakeholder consortium involving the UN World Food Programme (WFP), Telefonica Research, Technical University of Madrid (UPM), Digital Strategy Coordination Office of the President of Mexico, and UN Global Pulse.
  • Telefonica Research, a division of the major Latin American telecommunications company, provided call detail records covering flood-affected areas for nine months. This data was combined with “remote sensing data (satellite images), rainfall data, census and civil protection data.” The results of the data demonstrated that “analysing mobile activity during floods could be used to potentially locate damaged areas, efficiently assess needs and allocate resources (for example, sending supplies to affected areas).”
  • In addition to the results, the study highlighted “the value of a public-private partnership on using mobile data to accurately indicate flooding impacts in Tabasco, thus improving early warning and crisis management.”

* Perkmann, M. and Schildt, H. “Open data partnerships between firms and universities: The role of boundary organizations.” Research Policy, 44(5), 2015. http://bit.ly/25RRJ2c. 

  • This paper discusses the concept of a “boundary organization” in relation to industry-academic partnerships driven by data. Boundary organizations perform mediated revealing, allowing firms to disclose their research problems to a broad audience of innovators and simultaneously minimize the risk that this information would be adversely used by competitors.
  • The authors identify two especially important challenges for private firms to enter open data or participate in data collaboratives with the academic research community that could be addressed through more involvement from boundary organizations:
    • First is a challenge of maintaining competitive advantage. The authors note that, “the more a firm attempts to align the efforts in an open data research programme with its R&D priorities, the more it will have to reveal about the problems it is addressing within its proprietary R&D.”
    • Second, involves the misalignment of incentives between the private and academic field. Perkmann and Schildt argue that, a firm seeking to build collaborations around its opened data “will have to provide suitable incentives that are aligned with academic scientists’ desire to be rewarded for their work within their respective communities.”

Robin, N., Klein, T., & Jütting, J. “Public-Private Partnerships for Statistics: Lessons Learned, Future Steps.” OECD. 2016. http://bit.ly/24FLYlD.

  • This working paper acknowledges the growing body of work on how different types of data (e.g, telecom data, social media, sensors and geospatial data, etc.) can address data gaps relevant to National Statistical Offices (NSOs).
  • Four models of public-private interaction for statistics are describe: in-house production of statistics by a data-provider for a national statistics office (NSO), transfer of data-sets to NSOs from private entities, transfer of data to a third party provider to manage the NSO and private entity data, and the outsourcing of NSO functions.
  • The paper highlights challenges to public-private partnerships involving data (e.g., technical challenges, data confidentiality, risks, limited incentives for participation), suggests deliberate and highly structured approaches to public-private partnerships involving data require enforceable contracts, emphasizes the trade-off between data specificity and accessibility of such data, and the importance of pricing mechanisms that reflect the capacity and capability of national statistic offices.
  • Case studies referenced in the paper include:
    • A mobile network operator’s (MNO Telefonica) in house analysis of call detail records;
    • A third-party data provider and steward of travel statistics (Positium);
    • The Data for Development (D4D) challenge organized by MNO Orange; and
    • Statistics Netherlands use of social media to predict consumer confidence.

Stuart, Elizabeth, Samman, Emma, Avis, William, Berliner, Tom. “The data revolution: finding the missing millions.” Overseas Development Institute, 2015. Available from: http://bit.ly/1bPKOjw

  • The authors of this report highlight the need for good quality, relevant, accessible and timely data for governments to extend services into underrepresented communities and implement policies towards a sustainable “data revolution.”
  • The solutions focused on this recent report from the Overseas Development Institute focus on capacity-building activities of national statistical offices (NSOs), alternative sources of data (including shared corporate data) to address gaps, and building strong data management systems.

Taylor, L., & Schroeder, R. “Is bigger better? The emergence of big data as a tool for international development policy.” GeoJournal, 80(4). 2015. 503-518. http://bit.ly/1RZgSy4.

  • This journal article describes how privately held data – namely “digital traces” of consumer activity – “are becoming seen by policymakers and researchers as a potential solution to the lack of reliable statistical data on lower-income countries.
  • They focus especially on three categories of data collaborative use cases:
    • Mobile data as a predictive tool for issues such as human mobility and economic activity;
    • Use of mobile data to inform humanitarian response to crises; and
    • Use of born-digital web data as a tool for predicting economic trends, and the implications these have for LMICs.
  • They note, however, that a number of challenges and drawbacks exist for these types of use cases, including:
    • Access to private data sources often must be negotiated or bought, “which potentially means substituting negotiations with corporations for those with national statistical offices;”
    • The meaning of such data is not always simple or stable, and local knowledge is needed to understand how people are using the technologies in question
    • Bias in proprietary data can be hard to understand and quantify;
    • Lack of privacy frameworks; and
    • Power asymmetries, wherein “LMIC citizens are unwittingly placed in a panopticon staffed by international researchers, with no way out and no legal recourse.”

van Panhuis, Willem G., Proma Paul, Claudia Emerson, John Grefenstette, Richard Wilder, Abraham J. Herbst, David Heymann, and Donald S. Burke. “A systematic review of barriers to data sharing in public health.” BMC public health 14, no. 1 (2014): 1144. Available from: http://bit.ly/1JOBruO

  • The authors of this report provide a “systematic literature of potential barriers to public health data sharing.” These twenty potential barriers are classified in six categories: “technical, motivational, economic, political, legal and ethical.” In this taxonomy, “the first three categories are deeply rooted in well-known challenges of health information systems for which structural solutions have yet to be found; the last three have solutions that lie in an international dialogue aimed at generating consensus on policies and instruments for data sharing.”
  • The authors suggest the need for a “systematic framework of barriers to data sharing in public health” in order to accelerate access and use of data for public good.

Verhulst, Stefaan and Sangokoya, David. “Mapping the Next Frontier of Open Data: Corporate Data Sharing.” In: Gasser, Urs and Zittrain, Jonathan and Faris, Robert and Heacock Jones, Rebekah, “Internet Monitor 2014: Reflections on the Digital World: Platforms, Policy, Privacy, and Public Discourse (December 15, 2014).” Berkman Center Research Publication No. 2014-17. http://bit.ly/1GC12a2

  • This essay describe a taxonomy of current corporate data sharing practices for public good: research partnerships; prizes and challenges; trusted intermediaries; application programming interfaces (APIs); intelligence products; and corporate data cooperatives or pooling.
  • Examples of data collaboratives include: Yelp Dataset Challenge, the Digital Ecologies Research Partnerhsip, BBVA Innova Challenge, Telecom Italia’s Big Data Challenge, NIH’s Accelerating Medicines Partnership and the White House’s Climate Data Partnerships.
  • The authors highlight important questions to consider towards a more comprehensive mapping of these activities.

Verhulst, Stefaan and Sangokoya, David, 2015. “Data Collaboratives: Exchanging Data to Improve People’s Lives.” Medium. Available from: http://bit.ly/1JOBDdy

  • The essay refers to data collaboratives as a new form of collaboration involving participants from different sectors exchanging data to help solve public problems. These forms of collaborations can improve people’s lives through data-driven decision-making; information exchange and coordination; and shared standards and frameworks for multi-actor, multi-sector participation.
  • The essay cites four activities that are critical to accelerating data collaboratives: documenting value and measuring impact; matching public demand and corporate supply of data in a trusted way; training and convening data providers and users; experimenting and scaling existing initiatives.
  • Examples of data collaboratives include NIH’s Precision Medicine Initiative; the Mobile Data, Environmental Extremes and Population (MDEEP) Project; and Twitter-MIT’s Laboratory for Social Machines.

Verhulst, Stefaan, Susha, Iryna, Kostura, Alexander. “Data Collaboratives: matching Supply of (Corporate) Data to Solve Public Problems.” Medium. February 24, 2016. http://bit.ly/1ZEp2Sr.

  • This piece articulates a set of key lessons learned during a session at the International Data Responsibility Conference focused on identifying emerging practices, opportunities and challenges confronting data collaboratives.
  • The authors list a number of privately held data sources that could create positive public impacts if made more accessible in a collaborative manner, including:
    • Data for early warning systems to help mitigate the effects of natural disasters;
    • Data to help understand human behavior as it relates to nutrition and livelihoods in developing countries;
    • Data to monitor compliance with weapons treaties;
    • Data to more accurately measure progress related to the UN Sustainable Development Goals.
  • To the end of identifying and expanding on emerging practice in the space, the authors describe a number of current data collaborative experiments, including:
    • Trusted Intermediaries: Statistics Netherlands partnered with Vodafone to analyze mobile call data records in order to better understand mobility patterns and inform urban planning.
    • Prizes and Challenges: Orange Telecom, which has been a leader in this type of Data Collaboration, provided several examples of the company’s initiatives, such as the use of call data records to track the spread of malaria as well as their experience with Challenge 4 Development.
    • Research partnerships: The Data for Climate Action project is an ongoing large-scale initiative incentivizing companies to share their data to help researchers answer particular scientific questions related to climate change and adaptation.
    • Sharing intelligence products: JPMorgan Chase shares macro economic insights they gained leveraging their data through the newly established JPMorgan Chase Institute.
  • In order to capitalize on the opportunities provided by data collaboratives, a number of needs were identified:
    • A responsible data framework;
    • Increased insight into different business models that may facilitate the sharing of data;
    • Capacity to tap into the potential value of data;
    • Transparent stock of available data supply; and
    • Mapping emerging practices and models of sharing.

Vogel, N., Theisen, C., Leidig, J. P., Scripps, J., Graham, D. H., & Wolffe, G. “Mining mobile datasets to enable the fine-grained stochastic simulation of Ebola diffusion.” Paper presented at the Procedia Computer Science. 2015. http://bit.ly/1TZDroF.

  • The paper presents a research study conducted on the basis of the mobile calls records shared with researchers in the framework of the Data for Development Challenge by the mobile operator Orange.
  • The study discusses the data analysis approach in relation to developing a situation of Ebola diffusion built around “the interactions of multi-scale models, including viral loads (at the cellular level), disease progression (at the individual person level), disease propagation (at the workplace and family level), societal changes in migration and travel movements (at the population level), and mitigating interventions (at the abstract government policy level).”
  • The authors argue that the use of their population, mobility, and simulation models provide more accurate simulation details in comparison to high-level analytical predictions and that the D4D mobile datasets provide high-resolution information useful for modeling developing regions and hard to reach locations.

Welle Donker, F., van Loenen, B., & Bregt, A. K. “Open Data and Beyond.” ISPRS International Journal of Geo-Information, 5(4). 2016. http://bit.ly/22YtugY.

  • This research has developed a monitoring framework to assess the effects of open (private) data using a case study of a Dutch energy network administrator Liander.
  • Focusing on the potential impacts of open private energy data – beyond ‘smart disclosure’ where citizens are given information only about their own energy usage – the authors identify three attainable strategic goals:
    • Continuously optimize performance on services, security of supply, and costs;
    • Improve management of energy flows and insight into energy consumption;
    • Help customers save energy and switch over to renewable energy sources.
  • The authors propose a seven-step framework for assessing the impacts of Liander data, in particular, and open private data more generally:
    • Develop a performance framework to describe what the program is about, description of the organization’s mission and strategic goals;
    • Identify the most important elements, or key performance areas which are most critical to understanding and assessing your program’s success;
    • Select the most appropriate performance measures;
    • Determine the gaps between what information you need and what is available;
    • Develop and implement a measurement strategy to address the gaps;
    • Develop a performance report which highlights what you have accomplished and what you have learned;
    • Learn from your experiences and refine your approach as required.
  • While the authors note that the true impacts of this open private data will likely not come into view in the short term, they argue that, “Liander has successfully demonstrated that private energy companies can release open data, and has successfully championed the other Dutch network administrators to follow suit.”

World Economic Forum, 2015. “Data-driven development: pathways for progress.” Geneva: World Economic Forum. http://bit.ly/1JOBS8u

  • This report captures an overview of the existing data deficit and the value and impact of big data for sustainable development.
  • The authors of the report focus on four main priorities towards a sustainable data revolution: commercial incentives and trusted agreements with public- and private-sector actors; the development of shared policy frameworks, legal protections and impact assessments; capacity building activities at the institutional, community, local and individual level; and lastly, recognizing individuals as both produces and consumers of data.

Workplace innovation in the public sector

Curated on Posted on by Stefaan Verhulst

Eurofound: “Innovative organisational practices in the workplace, which aim to make best use of human capital, are traditionally associated with the private sector. The nature of the public sector activities makes it more difficult to identify these types of internal innovation in publicly funded organisations.

It is widely thought that public sector organisations are neither dynamic nor creative and are typified by a high degree of inertia. Yet the necessity of innovation ought not to be dismissed. The public sector represents a quarter of total EU employment, and it is of critical importance as a provider and regulator of services. Improving how it performs has a knock-on effect not only for private sector growth but also for citizens’ satisfaction. Ultimately, this improves governance itself.

So how can innovative organisation practices help in dealing with the challenges faced by the public sector? Eurofound, as part of a project on workplace innovation in European companies, carried out case studies of both private and public sector organisations. The findings show a number of interesting practices and processes used.

Employee participation

The case studies from the public sector, some of which are described below, demonstrate the central role of employee participation in the implementation of workplace innovation and its impacts on organisation and employees. They indicate that innovative practices have resulted in enhanced organisational performance and quality of working life.

It is widely thought that changes in the public sector are initiated as a response to government policies. This is often true, but workplace innovation may also be introduced as a result of well-designed initiatives driven by external pressures (such as the need for a more competitive public service) or internal pressures (such as a need to update the skills map to better serve the public).

Case study findings

The state-owned Lithuanian energy company Lietuvos Energijos Gamyba (140 KB PDF) encourages employee participation by providing a structured framework for all employees to propose improvements. This has required a change in managerial approach and has spread a sense of ownership horizontally and vertically in the company. The Polish public transport company Jarosław City Transport (191 KB PDF), when faced with serious financial stability challenges, as well as implementing operational changes, set up ways for employees’ voices to be heard, which enabled a contributory dialogue and strengthened partnerships. Consultation, development of mutual trust, and common involvement ensured an effective combination of top-down and bottom-up initiatives.

The Lithuanian Post, AB Lietuvos Pastas (136 KB PDF) experienced a major organisation transformation in 2010 to improve efficiency and quality of service. Through a programme of ‘Loyalty day’ monthly visits, both top and middle management of the central administration visit any part of the company and work with colleagues in other units. Under budgetary pressure to ‘earn their money’, the Danish Vej and Park Bornholm (142 KB PDF) construction services in roads, parks and forests had to find innovative solutions to deal with a merger and privatisation. Their intervention had the characteristics of workplace partnership with a new set of organisational values set from the bottom up. Self-managing teams are essential for the operation of the company.

The world of education has provided new structures that provide better outcomes for students. The South West University of Bulgaria (214 KB PDF) also operates small self-managing teams responsible for employee scheduling. Weekly round-tables encourage participation in collectively finding solutions, creating a more effective environment in which to respond to the competitive demands of education provision.

In Poland, an initiative by the Pomeranian Library (185 KB PDF) improved employee–management dialogue and communication through increased participation. The initiative is a response to the new frameworks for open access to knowledge for users, with the library mirroring the user experience through its own work practices.

Through new dialogue, government advisory bodies have also developed employee-led improvement. Breaking away from a traditional hierarchy is considered important in achieving a more flexible work organisation. Under considerable pressure, the top-heavy management of the British Geological Survey (89 KB PDF) now operates a flexible matrix that promotes innovative and entrepreneurial ways of working. And in Germany, Niersverband (138 KB PDF), a publicly owned water-management company innovated through training, learning, reflection partnerships and workplace partnerships. New occupational profiles were developed to meet external demands. Based on dialogue concerning workplace experiences and competences, employees acquired new qualifications that allowed the company to be more competitive.

In the Funen Village Museum in Odense, Denmark, (143 KB PDF) innovation came about at the request of staff looking for more flexibility in how they work. Formerly most of their work was maintenance tasks, but now they can now engage more with visitors. Control of schedules has moved to the team rather than being the responsibility of a single manager. As a result, museum employees are now hosts as well as craftspeople. They no longer feel ‘forgotten’ and are happier in their work….(More)”

The report Workplace innovation in European companies provides a full analysis of the case studies.

The 51 case studies and the  list of companies (PDF 119 KB) the case studies are based on are available for download.

Global governance and ICTs: exploring online governance networks around gender and media

Curated on Posted on by Stefaan Verhulst

Claudia Padovani and Elena Pavan in the journal “Global Networks“: In this article, we address transformations in global governance brought about by information and communication technologies (ICTs). Focusing on the specific domain of ‘gender-oriented communication governance’, we investigate online interactions among different kinds of actors active in promoting gender equity in and through the media. By tracing and analysing online issue networks, we investigate which actors are capable of influencing the framing of issues and of structuring discursive practices. From the analysis, different forms of power emerge, reflecting diverse modes of engaging in online interactions, where actors can operate as network ‘programmers’, ‘mobilizers’, or ‘switchers’. Our case study suggests that, often, old ways of conceiving actors’ interactions accompany the implementation of new communication tools, while the availability of a pervasive networked infrastructure does not automatically translate into meaningful interactions among all relevant actors in a specific domain….(More)”

The era of development mutants

Curated on Posted on by Stefaan Verhulst

Guilo Quaggiotto at Nesta: “If you were looking for the cutting edge of the development sector, where would you go these days? You would probably look at startups like Premise who have predicted food trends 25 days faster than national statistics in Brazil, or GiveDirectly who are pushing the boundaries on evidence – from RCTs to new ways of mapping poverty – to fast track the adoption of cash transfers.

Or perhaps you might draw your attention to PetaJakarta who are experimenting with new responses to crises by harnessing human sensor networks. You might be tempted to consider Airbnb’s Disaster Response programme as an indicator of an emerging alternative infrastructure for disaster response (and perhaps raising questions about the political economy of this all).

And could Bitnation’s Refugee Emergency programme in response to the European refugee crisis be the possible precursor of future solutions for transnational issues – among the development sector’s hardest challenges? Are the business models of One Acre Fund, which provides services for smallholder farmers, or Floodtags, which analyses citizen data during floods for water and disaster managers, an indicator of future pathways to scale – that elusive development unicorn?

If you want to look at the future of procuring solutions for the development sector, should you be looking at initiatives like Citymart, which works with municipalities across the world to rethink traditional procurement and unleash the expertise and innovation capabilities of their citizens? By the same token, projects like Pathogen Box, Poverty Stoplight or Patient Innovation point to a brave new world where lead-user innovation and harnessing ‘sticky’ local knowledge becomes the norm, rather than the exception. You would also be forgiven for thinking that social movements across the world are the place to look for signs of future mechanisms for harnessing collective intelligence – Kawal Pamilu’s “citizen experts” self-organising around the Indonesian elections in 2014 is a textbook case study in this department.

The list could go on and on: welcome to the era of development mutants. While established players in the development sector are engrossed in soul-searching and their fitness for purpose is being scrutinised from all quarters, a whole new set of players is emerging, unfettered by legacy and borrowing from a variety of different disciplines. They point to a potentially different future – indeed, many potentially different futures – for the sector…..

But what if we wanted to invert this paradigm? How could we move from denial to fruitful collaboration with the ‘edgeryders’ of the development sector and accelerate its transformation?

Adopting new programming principles

Based on our experience working with development organisations, we believe that partnering with the mutants involves two types of shifts for traditional players: at the programmatic and the operational level. At the programmatic level, our work on the ground led us to articulate the following emerging principles:

  1. Mapping what people have, not what they need: even though approaches like jugaad and positive deviance have been around for a long time, unfortunately the default starting point for many development projects is still mapping needs, not assets. Inverting this paradigm allows for potentially disruptive project design and partnerships to emerge. (Signs of the future: Patient Innovation, Edgeryders, Community Mirror, Premise)

  2. Getting ready for multiple futures: When distributed across an organisation and not limited to a centralised function, the discipline of scanning the horizon for emergent solutions that contradict the dominant paradigm can help move beyond the denial phase and develop new interfaces to collaborate with the mutants. Here the link between analysis (to understand not only what is probable, but also what is possible) and action is critical – otherwise this remains purely an academic exercise. (Signs of the future: OpenCare, Improstuctures, Seeds of Good Anthropocene, Museum of the Future)

  3. Running multiple parallel experiments: According to Dave Snowden, in order to intervene in a complex system “you need multiple parallel experiments and they should be based on different and competing theories/hypotheses”. Unfortunately, many development projects are still based on linear narratives and assumptions such as “if only we run an awareness raising campaign citizens will change their behaviour”. Turning linear narratives into hypotheses to be tested (without becoming religious on a specific approach) opens up the possibility to explore the solution landscape and collaborate with non-obvious partners that bring new approaches to the table. (Signs of the future: Chukua Hakua, GiveDirectly, Finnish PM’s Office of Experiments, Ideas42, Cognitive Edge)

  4. Embracing obliquity: A deep, granular understanding of local assets and dynamics along with system mapping (see point 5 below) and pairing behavioural experts with development practitioners can help identify entry points for exploring new types of intervention based on obliquity principles. Mutants are often faster in adopting this approach and partnering with them is a way to bypass organisational inertia and explore nonlinear interventions. (Signs of the future: Sardex, social prescriptions, forensic architecture)

  5. From projects to systems: development organisations genuinely interested in developing new partnerships need to make the shift from the project logic to system investments. This involves, among other things, shifting the focus from providing solutions to helping every actor in the system to develop a higher level of consciousness about the issues they are facing and to take better decisions over time. It also entails partnering with mutants to explore entirely new financial mechanisms. (Signs of the future: Lankelly Chase, Indonesia waste banks, Dark Matter Labs)

Adopting new interfaces for working with the mutants

Harvard Business School professor Carliss Baldwin argued that most bureaucracies these days have a ‘non-contractible’ problem: they don’t know where smart people are, or how to evaluate how good they are. Most importantly, most smart people don’t want to work for them because they find them either too callous, unrewarding or slow (or a combination of all of these)….(More)”

Selected Readings on Data and Humanitarian Response

Curated on Posted on 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

Risks of Using Big Data in Humanitarian Context

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

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