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.

Democracy Does Not Cause Growth: The Importance of Endogeneity Arguments

Curated on Posted on by Stefaan Verhulst

IADB Working Paper by JEL Codes:”This article challenges recent findings that democracy has sizable effects on economic growth. As extensive political science research indicates that economic turmoil is responsible for causing or facilitating many democratic transitions, the paper focuses on this endogeneity concern. Using a worldwide survey of 165 country-specific democracy experts conducted for this study, the paper separates democratic transitions into those occurring for reasons related to economic turmoil, here called endogenous, and those grounded in reasons more exogenous to economic growth. The behavior of economic growth following these more exogenous democratizations strongly indicates that democracy does not cause growth. Consequently, the common positive association between democracy and economic growth is driven by endogenous democratization episodes (i.e., due to faulty identification)….(More)”

Digital Government: overcoming the systemic failure of transformation

Curated on Posted on by Stefaan Verhulst

Paul Waller and Vishanth Weerakkody: “This Working Paper contains propositions regarding the use of digital technology to “transform” government that significantly conflict with received wisdom in academia and governments across the world. It counters assertions made in countless political, official and commercial statements and reports produced over past decades….

The “transformation of government” has often been proposed as an objective of e-government; frequently presented as a phase in stage models following the provision online of information and transactions. Yet in literature or official documents there is no established definition of transformation as applied to government. Implicitly or explicitly, it mostly refers to a change in organisational form, signalled by the terms “joining-up” or “integration”, of government. In some work,

In some work, transformation is limited to changing processes or “services”— though “services” is a term unhelpfully applied to a multitude of entities. There is in academic or other literature little evidence of any type of “transformation” achieved beyond a change in an administrative process, nor a robust framework of benefits one might deliver. This begs the questions of what it actually means in reality and why it might be a desired goal.

In essence, what we aim to do in this paper is to develop a structured frame of reference for making sense of how information and communications technologies (ICT), in all their forms, really fit within the world of government and public administration — exactly the challenge set by Professor Christopher Hood in his 2007 paper:

“But we need to have a way of assessing current developments in administrative technologies with those of other eras, such as development of telephones, cars, radios, and fingerprinting in police work in the early part of the twentieth century, or of exact methods of measurement on excise tax collection in the eighteenth century. And if the analysis of the changes such developments bring is to amount to anything more than a breathless tour d’horizon of the latest technological gizmos in public policy (much though governments themselves have a liking for that sort of approach), it needs to be related to some foundational analysis that is, in some way, technology-free and rooted in the nature of government as a social and legal phenomenon.”

After a brief historical review, the paper starts by considering what governments and public administrations actually do: specifically, policy design and implementation through policy instruments. It redefines transformation in terms of changing the policy instrument set chosen to implement policy and sets out broad rationales for how and why ICT can enable this. It proposes a frame of reference of terminology, concepts and objects that enable the examination of not only such transformation, but e-government in general as it has developed over two decades. …(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.

Privacy, security and data protection in smart cities: a critical EU law perspective

Curated on Posted on by Stefaan Verhulst

CREATe Working Paper by Lilian Edwards: “Smart cities” are a buzzword of the moment. Although legal interest is growing, most academic responses at least in the EU, are still from the technological, urban studies, environmental and sociological rather than legal, sectors2 and have primarily laid emphasis on the social, urban, policing and environmental benefits of smart cities, rather than their challenges, in often a rather uncritical fashion3 . However a growing backlash from the privacy and surveillance sectors warns of the potential threat to personal privacy posed by smart cities . A key issue is the lack of opportunity in an ambient or smart city environment for the giving of meaningful consent to processing of personal data; other crucial issues include the degree to which smart cities collect private data from inevitable public interactions, the “privatisation” of ownership of both infrastructure and data, the repurposing of “big data” drawn from IoT in smart cities and the storage of that data in the Cloud.

This paper, drawing on author engagement with smart city development in Glasgow as well as the results of an international conference in the area curated by the author, argues that smart cities combine the three greatest current threats to personal privacy, with which regulation has so far failed to deal effectively; the Internet of Things(IoT) or “ubiquitous computing”; “Big Data” ; and the Cloud. While these three phenomena have been examined extensively in much privacy literature (particularly the last two), both in the US and EU, the combination is under-explored. Furthermore, US legal literature and solutions (if any) are not simply transferable to the EU because of the US’s lack of an omnibus data protection (DP) law. I will discuss how and if EU DP law controls possible threats to personal privacy from smart cities and suggest further research on two possible solutions: one, a mandatory holistic privacy impact assessment (PIA) exercise for smart cities: two, code solutions for flagging the need for, and consequences of, giving consent to collection of data in ambient environments….(More)

Digital Weberianism: Towards a reconceptualization of bureaucratic social order in the digital age

Curated on Posted on by Stefaan Verhulst

Working Paper by Chris Muellerleile & Susan Robertson: “The social infrastructures that the global economy relies upon are becoming dependent on digital code, big data, and algorithms. At the same time the digital is also changing the very nature of economic and social institutions. In this paper we attempt to make sense of the relationships between the emergence of digitalism, and transformations in both capitalism, and the ways that capitalism is regulated by digitized social relations. We speculate that the logic, rationalities, and techniques of Max Weber’s bureau, a foundational concept in his theory of modernity, helps explain the purported efficiency, objectivity, and rationality of digital technologies. We argue that digital rationality constitutes a common thread of social infrastructure that is increasingly overdetermining the nature of sociality. We employ the example of the smart city and the digitizing university to expose some of the contradictions of digital order, and we end by questioning what digital order might mean after the end of modernity….(More)”

Peer review in 2015: A global view

Curated on Posted on by Stefaan Verhulst

A white paper by Taylor & Francis: “Within the academic community, peer review is widely recognized as being at the heart of scholarly research. However, faith in peer review’s integrity is of ongoing and increasing concern to many. It is imperative that publishers (and academic editors) of peer-reviewed scholarly research learn from each other, working together to improve practices in areas such as ethical issues, training, and data transparency….Key findings:

  • Authors, editors and reviewers all agreed that the most important motivation to publish in peer reviewed journals is making a contribution to the field and sharing research with others.
  • Playing a part in the academic process and improving papers are the most important motivations for reviewers. Similarly, 90% of SAS study respondents said that playing a role in the academic community was a motivation to review.
  • Most researchers, across the humanities and social sciences (HSS) and science, technology and medicine (STM), rate the benefit of the peer review process towards improving their article as 8 or above out of 10. This was found to be the most important aspect of peer review in both the ideal and the real world, echoing the earlier large-scale peer review studies.
  • In an ideal world, there is agreement that peer review should detect plagiarism (with mean ratings of 7.1 for HSS and 7.5 for STM out of 10), but agreement that peer review is currently achieving this in the real world is only 5.7 HSS / 6.3 STM out of 10.
  • Researchers thought there was a low prevalence of gender bias but higher prevalence of regional and seniority bias – and suggest that double blind peer review is most capable of preventing reviewer discrimination where it is based on an author’s identity.
  • Most researchers wait between one and six months for an article they’ve written to undergo peer review, yet authors (not reviewers / editors) think up to two months is reasonable .
  • HSS authors say they are kept less well informed than STM authors about the progress of their article through peer review….(More)”

How open company data was used to uncover the powerful elite benefiting from Myanmar’s multi-billion dollar jade industry

Curated on Posted on by Stefaan Verhulst

OpenCorporates: “Today, we’re pleased to release a white paper on how OpenCorporates data was used to uncover the powerful elite benefiting from Myanmar’s multi-billion dollar jade industry, in a ground-breaking report from Global Witness. This investigation is an important case study on how open company data and identifiers are critical tool to uncover corruption and the links between companies and the real people benefitting from it.

This white paper shows how not only was it critical that OpenCorporates had this information (much of the information was removed from the official register during the investigation), but that the fact that it was machine-readable data, available via an API (data service), and programmatically combinable with other data was essential to discover the hidden connections between the key actors and the jade industry. Global Witness was able to analyse this data with the help of Open Knowledge.

In this white paper, we make recommendations about the collection and publishing of statutory company information as open data to facilitate the creation of a hostile environment for corruption by providing a rigorous framework for public scrutiny and due diligence.

You can find the white paper here or read it on Medium.”

Can Mobile Phone Surveys Identify People’s Development Priorities?

Curated on Posted on by Stefaan Verhulst

Ben Leo and Robert Morello at the Center for Global Development: “Mobile phone surveys are fast, flexible, and cheap. But, can they be used to engage citizens on how billions of dollars in donor and government resources are spent? Over the last decade, donor governments and multilateral organizations have repeatedly committed to support local priorities and programs. Yet, how are they supposed to identify these priorities on a timely, regular basis? Consistent discussions with the local government are clearly essential, but so are feeding ordinary people’s views into those discussions. However, traditional tools, such as household surveys or consultative roundtables, present a range of challenges for high-frequency citizen engagement. That’s where mobile phone surveys could come in, enabled by the exponential rise in mobile coverage throughout the developing world.

Despite this potential, there have been only a handful of studies into whether mobile surveys are a reliable and representative tool across a broad range of developing-country contexts. Moreover, there have been almost none that specifically look at collecting information about people’s development priorities. Along with Tiago Peixoto,Steve Davenport, and Jonathan Mellon, who focus on promoting citizen engagement and open government practices at the World Bank, we sought to address this policy research gap. Through a study focused on four low-income countries (Afghanistan, Ethiopia, Mozambique, and Zimbabwe), we rigorously tested the feasibility of interactive voice recognition (IVR) surveys for gauging citizens’ development priorities.

Specifically, we wanted to know whether respondents’ answers are sensitive to a range of different factors, such as (i) the specified executing actor (national government or external partners); (ii) time horizons; or (iii) question formats. In other words, can we be sufficiently confident that surveys about people’s priorities can be applied more generally to a range of development actors and across a range of country contexts?

Several of these potential sensitivity concerns were raised in response to an earlier CGD working paper, which found that US foreign aid is only modestly aligned with Africans’ and Latin Americans’ most pressing concerns. This analysis relied upon Afrobarometer and Latinobarometro survey data (see explanatory note below). For instance, some argued that people’s priorities for their own government might be far less relevant for donor organizations. Put differently, the World Bank or USAID shouldn’t prioritize job creation in Nigeria simply because ordinary Nigerians cite it as a pressing government priority. Our hypothesis was that development priorities would likely transcend all development actors, and possibly different timeframes and question formats as well. But, we first needed to test these assumptions.

So, what did we find? We’ve included some of the key highlights below. For a more detailed description of the study and the underlying analysis, please see our new working paper. Along with our World Bank colleagues, we also published an accompanying paper that considers a range of survey method issues, including survey representativeness….(More)”

Testing governance: the laboratory lives and methods of policy innovation labs

Curated on Posted on by Stefaan Verhulst

Ben Williamson at Code Acts in Education: “Digital technologies are increasingly playing a significant role in techniques of governance in sectors such as education as well as healthcare, urban management, and in government innovation and citizen engagement in government services. But these technologies need to be sponsored and advocated by particular individuals and groups before they are embedded in these settings.

Testing governance cover

I have produced a working paper entitled Testing governance: the laboratory lives and methods of policy innovation labs which examines the role of innovation labs as sponsors of new digital technologies of governance. By combining resources and practices from politics, data analysis, media, design, and digital innovation, labs act as experimental R&D labs and practical ideas organizations for solving social and public problems, located in the borderlands between sectors, fields and disciplinary methodologies. Labs are making methods such as data analytics, design thinking and experimentation into a powerful set of governing resources.They are, in other words, making digital methods into key techniques for understanding social and public issues, and in the creation and circulation of solutions to the problems of contemporary governance–in education and elsewhere.

The working paper analyses the key methods and messages of the labs field, in particular by investigating the documentary history of Futurelab, a prototypical lab for education research and innovation that operated in Bristol, UK, between 2002 and 2010, and tracing methodological continuities through the current wave of lab development. Centrally, the working paper explores Futurelab’s contribution to the production and stabilization of a ‘sociotechnical imaginary’ of the future of education specifically, and to the future of public services more generally. It offers some preliminary analysis of how such an imaginary was embedded in the ‘laboratory life’ of Futurelab, established through its organizational networks, and operationalized in its digital methods of research and development as well as its modes of communication….(More)”