Why Technology Hasn’t Delivered More Democracy


Collection of POVs aggregated by Thomas Carothers at Foreign Policy: “New technologies offer important tools for empowerment — yet democracy is stagnating. What’s up?…

THe current moment confronts us with a paradox. The first fifteen years of this century have been a time of astonishing advances in communications and information technology, including digitalization, mass-accessible video platforms, smart phones, social media, billions of people gaining internet access, and much else. These revolutionary changes all imply a profound empowerment of individuals through exponentially greater access to information, tremendous ease of communication and data-sharing, and formidable tools for networking. Yet despite these changes, democracy — a political system based on the idea of the empowerment of individuals — has in these same years become stagnant in the world. The number of democracies today is basically no greater than it was at the start of the century. Many democracies, both long-established ones and newer ones, are experiencing serious institutional debilities and weak public confidence.

How can we reconcile these two contrasting global realities — the unprecedented advance of technologies that facilitate individual empowerment and the overall lack of advance of democracy worldwide? To help answer this question, I asked six experts on political change, all from very different professional and national perspectives. Here are their responses, followed by a few brief observations of my own.

1. Place a Long Bet on the Local By Martin Tisné

2. Autocrats Know How to Use Tech, Too By Larry Diamond

3. Limits on Technology Persist By Senem Aydin Düzgit

4. The Harder Task By Rakesh Rajani

5. Don’t Forget Institutions By Diane de Gramont

6. Mixed Lessons from Iran By Golnaz Esfandiari

7. Yes, It’s Complicated byThomas Carothers…(More)”

The Open Seventeen


Crowdsourcing the Verification of the Sustainable Development Goals with Open Data : In 2015, the United Nations is announcing seventeen Sustainable Development Goals (SDGs) for the world. Success at implementing the SDGs by 2030 could put the planet on the right course for the rest of the century. Failure could result in a breakdown of trust in global initiatives and cynical pursuit of self-interest by nations and corporations.

One way to ensure SDGs are achieved is to establish an independent means for verifying that all stakeholders – governments, corporations, NGOs and international organisations – live up to their promises. This requires harnessing the grassroots efforts of concerned citizens on a global scale.

To ignite this effort, ONE– in collaboration with the Citizen Cyberscience Centre and the Crowdcrafting platform for open research – is launching The Open Seventeen, a challenge to develop crowdsourcing projects that tackle SDGs using open data.

How does this challenge work?

You’ll find a big blue button further down this page. Use this to pitch a crowdsourcing project that tackles any of the 17 SDGs, at either a local, regional or global level, and tell us what open data set could be analysed for this purpose.

To inspire you, we’ve provided below some >examples of crowdsourcing projects that have already been tackling different aspects of the SDGs, from deforestation to corruption, and from drought to disease. Projects proposed for the challenge should have clear and realistic goals, and build on existing open data sets.

ONE and its partners will select three proposals and create crowdsourcing projects based on these. The winners and their projects will be profiled by ONE in upcoming international events related to the launch of the SDGs. Your project could inspire the world….

What can you do with open data to help verify SDGs? Have a look at what citizens have already created using the open source technology PyBossa that powers the Crowdcrafting platform and other crowdsourcing projects….(More)”

A Repository of Open Data Repositories: Open Data Impact Case Studies and Examples


“As part of its core mission, the GovLab has been engaged in a series of ongoing efforts to build awareness and gather evidence about the value, use, and impact of open data around the world – including the GovLab’s Open Data 500.

The GovLab is currently scoping a project with Omidyar Network to build a repository of in-depth, global case studies on existing examples of open data demand, use and impact. The goal of the project is to develop a more nuanced understanding of the various processes and factors underlying the value chain of open data.

As a part of our literature review in undertaking this scoping project, and in time for the 3rd International Open Data Conference, we first mapped several repositories of open data cases and examples that may serve as an empirical foundation for further case-studies.

Below is a non-exhaustive list of organizations that have compiled open data case study repositories in a complementary fashion.

LET US KNOW if you are aware of other compilations of open data examples and case studies we should include as to complete the below overview… by emailing Stefaan Verhulst (stefaan at thegovlab.org).

1. Open Data Case Study Repositories
2. Open Data Portal Repositories
3. Open Data Intermediary Repositories

WFP And OCHA Join Forces To Make Data More Accessible


World Food Programme Press Release: “The United Nations World Food Programme (WFP) and the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) have teamed up to provide access to global data on hunger and food insecurity. The data can be used to understand the type of food available in certain markets, how families cope in the face of food insecurity and how WFP provides food assistance in emergencies to those in need.

The data is being made available through OCHA’s Humanitarian Data Exchange (HDX), an open platform for sharing crisis data. The collaboration between WFP, the world’s largest humanitarian organization fighting hunger worldwide, and OCHA began at the height of the Ebola crisis when WFP shared its data on food market prices in affected countries in West Africa.

With funding from the UK’s Department for International Development (DFID) and the Bill & Melinda Gates Foundation, WFP has since been able to make large amounts of its data available dynamically, making it easier to integrate with other systems, including HDX.

From there, HDX built an interactive visualization for Food Prices data that allows a range of users, from the general public to a data scientist, to explore the data in insightful ways. The same visualization is also available on the WFP VAM Shop….(More)

World of Labs


NESTA: “Governments across the world are creating innovation teams and labs to help them find new ways of tackling the complex challenges of the 21st century. If you want to get a sense of the scale of this global trend then check out this searchable global map of innovation labs worldwide.

There are about 80 in total represented here – colour-coded for the level of government (blue for local, green for regional, red national and yellow international). In this map I’ve concentrated on labs inside government excluding the dozens of public and social innovation labs (#psilabs) like Nesta, MaRS Solutions Lab or The GovLab that work alongside the public sector though they themselves are outside it. I’ve probably left lots of government i-teams and labs out of this list – so please suggest more and I’ll add them in.

Public innovation labs can claim to be a global movement not just in sheer numbers of teams and labs worldwide but also because of the momentum behind the creation of new ones, at a current rate of least one a month. Though some of the most celebrated examples e.g. Denmark’s MindLab are well into their second decade about a third of the labs set out here have been born in the last two years.

The early wave of scenario-based creative “future centres” (like the Netherlands-based De Werf)  was soon followed by the kind of design-based lab that continues to dominate much of the thinking and practice in the field.  But lately this has been complemented by a new wave of teams using other tools (data and technology or behavioural economics) as well as the more hybrid approach often adopted by innovation delivery teams at a municipal level, particularly in the US. At a global level the shift to a lab-based approach in development policy has been particularly marked….(More)”

Selected Readings on Data Governance


Jos Berens (Centre for Innovation, Leiden University) and Stefaan G. Verhulst (GovLab)

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 governance was originally published in 2015.

Context
The field of Data Collaboratives is premised on the idea that sharing and opening-up private sector datasets has great – and yet untapped – potential for promoting social good. At the same time, the potential of data collaboratives depends on the level of societal trust in the exchange, analysis and use of the data exchanged. Strong data governance frameworks are essential to ensure responsible data use. Without such governance regimes, the emergent data ecosystem will be hampered and the (perceived) risks will dominate the (perceived) benefits. Further, without adopting a human-centered approach to the design of data governance frameworks, including iterative prototyping and careful consideration of the experience, the responses may fail to be flexible and targeted to real needs.

Selected Readings List (in alphabetical order)

Annotated Selected Readings List (in alphabetical order)

Better Place Lab, “Privacy, Transparency and Trust.” Mozilla, 2015. Available from: http://www.betterplace-lab.org/privacy-report.

  • This report looks specifically at the risks involved in the social sector having access to datasets, and the main risks development organizations should focus on to develop a responsible data use practice.
  • Focusing on five specific countries (Brazil, China, Germany, India and Indonesia), the report displays specific country profiles, followed by a comparative analysis centering around the topics of privacy, transparency, online behavior and trust.
  • Some of the key findings mentioned are:
    • A general concern on the importance of privacy, with cultural differences influencing conception of what privacy is.
    • Cultural differences determining how transparency is perceived, and how much value is attached to achieving it.
    • To build trust, individuals need to feel a personal connection or get a personal recommendation – it is hard to build trust regarding automated processes.

Montjoye, Yves Alexandre de; Kendall, Jake and; Kerry, Cameron F. “Enabling Humanitarian Use of Mobile Phone Data.” The Brookings Institution, 2015. Available from: http://www.brookings.edu/research/papers/2014/11/12-enabling-humanitarian-use-mobile-phone-data.

  • Focussing in particular on mobile phone data, this paper explores ways of mitigating privacy harms involved in using call detail records for social good.
  • Key takeaways are the following recommendations for using data for social good:
    • Engaging companies, NGOs, researchers, privacy experts, and governments to agree on a set of best practices for new privacy-conscientious metadata sharing models.
    • Accepting that no framework for maximizing data for the public good will offer perfect protection for privacy, but there must be a balanced application of privacy concerns against the potential for social good.
    • Establishing systems and processes for recognizing trusted third-parties and systems to manage datasets, enable detailed audits, and control the use of data so as to combat the potential for data abuse and re-identification of anonymous data.
    • Simplifying the process among developing governments in regards to the collection and use of mobile phone metadata data for research and public good purposes.

Centre for Democracy and Technology, “Health Big Data in the Commercial Context.” Centre for Democracy and Technology, 2015. Available from: https://cdt.org/insight/health-big-data-in-the-commercial-context/.

  • Focusing particularly on the privacy issues related to using data generated by individuals, this paper explores the overlap in privacy questions this field has with other data uses.
  • The authors note that although the Health Insurance Portability and Accountability Act (HIPAA) has proven a successful approach in ensuring accountability for health data, most of these standards do not apply to developers of the new technologies used to collect these new data sets.
  • For non-HIPAA covered, customer facing technologies, the paper bases an alternative framework for consideration of privacy issues. The framework is based on the Fair Information Practice Principles, and three rounds of stakeholder consultations.

Center for Information Policy Leadership, “A Risk-based Approach to Privacy: Improving Effectiveness in Practice.” Centre for Information Policy Leadership, Hunton & Williams LLP, 2015. Available from: https://www.informationpolicycentre.com/uploads/5/7/1/0/57104281/white_paper_1-a_risk_based_approach_to_privacy_improving_effectiveness_in_practice.pdf.

  • This white paper is part of a project aiming to explain what is often referred to as a new, risk-based approach to privacy, and the development of a privacy risk framework and methodology.
  • With the pace of technological progress often outstripping the capabilities of privacy officers to keep up, this method aims to offer the ability to approach privacy matters in a structured way, assessing privacy implications from the perspective of possible negative impact on individuals.
  • With the intended outcomes of the project being “materials to help policy-makers and legislators to identify desired outcomes and shape rules for the future which are more effective and less burdensome”, insights from this paper might also feed into the development of innovative governance mechanisms aimed specifically at preventing individual harm.

Centre for Information Policy Leadership, “Data Governance for the Evolving Digital Market Place”, Centre for Information Policy Leadership, Hunton & Williams LLP, 2011. Available from: http://www.huntonfiles.com/files/webupload/CIPL_Centre_Accountability_Data_Governance_Paper_2011.pdf.

  • This paper argues that as a result of the proliferation of large scale data analytics, new models governing data inferred from society will shift responsibility to the side of organizations deriving and creating value from that data.
  • It is noted that, with the reality of the challenge corporations face of enabling agile and innovative data use “In exchange for increased corporate responsibility, accountability [and the governance models it mandates, ed.] allows for more flexible use of data.”
  • Proposed as a means to shift responsibility to the side of data-users, the accountability principle has been researched by a worldwide group of policymakers. Tailing the history of the accountability principle, the paper argues that it “(…) requires that companies implement programs that foster compliance with data protection principles, and be able to describe how those programs provide the required protections for individuals.”
  • The following essential elements of accountability are listed:
    • Organisation commitment to accountability and adoption of internal policies consistent with external criteria
    • Mechanisms to put privacy policies into effect, including tools, training and education
    • Systems for internal, ongoing oversight and assurance reviews and external verification
    • Transparency and mechanisms for individual participation
    • Means of remediation and external enforcement

Crawford, Kate; Schulz, Jason. “Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harm.” NYU School of Law, 2014. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2325784&download=yes.

  • Considering the privacy implications of large-scale analysis of numerous data sources, this paper proposes the implementation of a ‘procedural data due process’ mechanism to arm data subjects against potential privacy intrusions.
  • The authors acknowledge that some privacy protection structures already know similar mechanisms. However, due to the “inherent analytical assumptions and methodological biases” of big data systems, the authors argue for a more rigorous framework.

Letouze, Emmanuel, and; Vinck, Patrick. “The Ethics and Politics of Call Data Analytics”, DataPop Alliance, 2015. Available from: http://static1.squarespace.com/static/531a2b4be4b009ca7e474c05/t/54b97f82e4b0ff9569874fe9/1421442946517/WhitePaperCDRsEthicFrameworkDec10-2014Draft-2.pdf.

  • Focusing on the use of Call Detail Records (CDRs) for social good in development contexts, this whitepaper explores both the potential of these datasets – in part by detailing recent successful efforts in the space – and political and ethical constraints to their use.
  • Drawing from the Menlo Report Ethical Principles Guiding ICT Research, the paper explores how these principles might be unpacked to inform an ethics framework for the analysis of CDRs.

Data for Development External Ethics Panel, “Report of the External Ethics Review Panel.” Orange, 2015. Available from: http://www.d4d.orange.com/fr/content/download/43823/426571/version/2/file/D4D_Challenge_DEEP_Report_IBE.pdf.

  • This report presents the findings of the external expert panel overseeing the Orange Data for Development Challenge.
  • Several types of issues faced by the panel are described, along with the various ways in which the panel dealt with those issues.

Federal Trade Commission Staff Report, “Mobile Privacy Disclosures: Building Trust Through Transparency.” Federal Trade Commission, 2013. Available from: www.ftc.gov/os/2013/02/130201mobileprivacyreport.pdf.

  • This report looks at ways to address privacy concerns regarding mobile phone data use. Specific advise is provided for the following actors:
    • Platforms, or operating systems providers
    • App developers
    • Advertising networks and other third parties
    • App developer trade associations, along with academics, usability experts and privacy researchers

Mirani, Leo. “How to use mobile phone data for good without invading anyone’s privacy.” Quartz, 2015. Available from: http://qz.com/398257/how-to-use-mobile-phone-data-for-good-without-invading-anyones-privacy/.

  • This paper considers the privacy implications of using call detail records for social good, and ways to mitigate risks of privacy intrusion.
  • Taking example of the Orange D4D challenge and the anonymization strategy that was employed there, the paper describes how classic ‘anonymization’ is often not enough. The paper then lists further measures that can be taken to ensure adequate privacy protection.

Bernholz, Lucy. “Several Examples of Digital Ethics and Proposed Practices” Stanford Ethics of Data conference, 2014, Available from: http://www.scribd.com/doc/237527226/Several-Examples-of-Digital-Ethics-and-Proposed-Practices.

  • This list of readings prepared for Stanford’s Ethics of Data conference lists some of the leading available literature regarding ethical data use.

Abrams, Martin. “A Unified Ethical Frame for Big Data Analysis.” The Information Accountability Foundation, 2014. Available from: http://www.privacyconference2014.org/media/17388/Plenary5-Martin-Abrams-Ethics-Fundamental-Rights-and-BigData.pdf.

  • Going beyond privacy, this paper discusses the following elements as central to developing a broad framework for data analysis:
    • Beneficial
    • Progressive
    • Sustainable
    • Respectful
    • Fair

Lane, Julia; Stodden, Victoria; Bender, Stefan, and; Nissenbaum, Helen, “Privacy, Big Data and the Public Good”, Cambridge University Press, 2014. Available from: http://www.dataprivacybook.org.

  • This book treats the privacy issues surrounding the use of big data for promoting the public good.
  • The questions being asked include the following:
    • What are the ethical and legal requirements for scientists and government officials seeking to serve the public good without harming individual citizens?
    • What are the rules of engagement?
    • What are the best ways to provide access while protecting confidentiality?
    • Are there reasonable mechanisms to compensate citizens for privacy loss?

Richards, Neil M, and; King, Jonathan H. “Big Data Ethics”. Wake Forest Law Review, 2014. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2384174.

  • This paper describes the growing impact of big data analytics on society, and argues that because of this impact, a set of ethical principles to guide data use is called for.
  • The four proposed themes are: privacy, confidentiality, transparency and identity.
  • Finally, the paper discusses how big data can be integrated into society, going into multiple facets of this integration, including the law, roles of institutions and ethical principles.

OECD, “OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data”. Available from: http://www.oecd.org/sti/ieconomy/oecdguidelinesontheprotectionofprivacyandtransborderflowsofpersonaldata.htm.

  • A globally used set of principles to inform thought about handling personal data, the OECD privacy guidelines serve as one the leading standards for informing privacy policies and data governance structures.
  • The basic principles of national application are the following:
    • Collection Limitation Principle
    • Data Quality Principle
    • Purpose Specification Principle
    • Use Limitation Principle
    • Security Safeguards Principle
    • Openness Principle
    • Individual Participation Principle
    • Accountability Principle

The White House Big Data and Privacy Working Group, “Big Data: Seizing Opportunities, Preserving Values”, White House, 2015. Available from: https://www.whitehouse.gov/sites/default/files/docs/big_data_privacy_report_5.1.14_final_print.pdf.

  • Documenting the findings of the White House big data and privacy working group, this report lists i.a. the following key recommendations regarding data governance:
    • Bringing greater transparency to the data services industry
    • Stimulating international conversation on big data, with multiple stakeholders
    • With regard to educational data: ensuring data is used for the purpose it is collected for
    • Paying attention to the potential for big data to facilitate discrimination, and expanding technical understanding to stop discrimination

William Hoffman, “Pathways for Progress” World Economic Forum, 2015. Available from: http://www3.weforum.org/docs/WEFUSA_DataDrivenDevelopment_Report2015.pdf.

  • This paper treats i.a. the lack of well-defined and balanced governance mechanisms as one of the key obstacles preventing particularly corporate sector data from being shared in a controlled space.
  • An approach that balances the benefits against the risks of large scale data usage in a development context, building trust among all stake holders in the data ecosystem, is viewed as key.
  • Furthermore, this whitepaper notes that new governance models are required not just by the growing amount of data and analytical capacity, and more refined methods for analysis. The current “super-structure” of information flows between institutions is also seen as one of the key reasons to develop alternatives to the current – outdated – approaches to data governance.

Advances in Crowdsourcing


New book edited by Garrigos-Simon, Fernando J., Gil-Pechuán, Ignacio, Estelles-Miguel, Sofia: “This book attempts to link some of the recent advances in crowdsourcing with advances in innovation and management. It contributes to the literature in several ways. First, it provides a global definition, insights and examples of this managerial perspective resulting in a theoretical framework. Second, it explores the relationship between crowdsourcing and technological innovation, the development of social networks and new behaviors of Internet users. Third, it explores different crowdsourcing applications in various sectors such as medicine, tourism, information and communication technology (ICT), and marketing. Fourth, it observes the ways in which crowdsourcing can improve production, finance, management and overall managerial performance.

Crowdsourcing, also known as “massive outsourcing” or “voluntary outsourcing,” is the act of taking a job or a specific task usually performed by an employee of a company or contractors, and outsourcing it to a large group of people or a community (crowd or mass) via the Internet, through an open call. The term was coined by Jeff Howe in a 2006 issue of Wired magazine. It is being developed in different sciences (i.e., medicine, engineering, ICT, management) and is used in the most successful companies of the modern era (i.e., Apple, Facebook, Inditex, Starbucks). The developments in crowdsourcing has theoretical and practical implications, which will be explored in this book.

Including contributions from international academics, scholars and professionals within the field, this book provides a global, multidimensional perspective on crowdsourcing.​…(More)”

Data for Development


Jeffrey D. Sachs at Project Syndicate: “The data revolution is rapidly transforming every part of society. Elections are managed with biometrics, forests are monitored by satellite imagery, banking has migrated from branch offices to smartphones, and medical x-rays are examined halfway around the world. With a bit of investment and foresight, spelled out in a new report, prepared by the UN Sustainable Development Solutions Network (SDSN), on Data for Development, the data revolution can drive a sustainable development revolution, and accelerate progress toward ending poverty, promoting social inclusion, and protecting the environment.
The world’s governments will adopt the new Sustainable Development Goals (SDGs) at a special United Nations summit on September 25. The occasion will likely be the largest gathering of world leaders in history, as some 170 heads of state and government adopt shared goals that will guide global development efforts until 2030. Of course, goals are easier to adopt than to achieve. So we will need new tools, including new data systems, to turn the SDGs into reality by 2030. In developing these new data systems, governments, businesses, and civil-society groups should promote four distinct purposes.

The first, and most important, is data for service delivery. The data revolution gives governments and businesses new and greatly improved ways to deliver services, fight corruption, cut red tape, and guarantee access in previously isolated places. Information technology is already revolutionizing the delivery of health care, education, governance, infrastructure (for example, prepaid electricity), banking, emergency response, and much more.
The second purpose is data for public management. Officials can now maintain real-time dashboards informing them of the current state of government facilities, transport networks, emergency relief operations, public health surveillance, violent crimes, and much more. Citizen feedback can also improve functioning, such as by crowd-sourcing traffic information from drivers. Geographic information systems (GIS) allow for real-time monitoring across local governments and districts in far-flung regions.
The third purpose is data for accountability of governments and businesses. It is a truism that government bureaucracies cut corners, hide gaps in service delivery, exaggerate performance, or, in the worst cases, simply steal when they can get away with it. Many businesses are no better. The data revolution can help to ensure that verifiable data are accessible to the general public and the intended recipients of public and private services. When services do not arrive on schedule (owing to, say, a bottleneck in construction or corruption in the supply chain), the data system will enable the public to pinpoint problems and hold governments and businesses to account.
Finally, the data revolution should enable the public to know whether or not a global goal or target has actually been achieved. The Millennium Development Goals, which were set in the year 2000, established quantitative targets for the year 2015. But, although we are now in the MDGs’ final year, we still lack precise knowledge of whether certain MDG targets have been achieved, owing to the absence of high-quality, timely data. Some of the most important MDG targets are reported with a lag of several years. The World Bank, for example, has not published detailed poverty data since 2010…..(More)”

The Quiet Power of Indicators: Measuring Governance, Corruption, and Rule of Law


New book edited by Sally Engle MerryKevin Davis, and Benedict Kingsbury: “Using a power-knowledge framework, this volume critically investigates how major global indicators of legal governance are produced, disseminated and used, and to what effect. Original case studies include Freedom House’s Freedom in the World indicator, the Global Reporting Initiative’s structure for measuring and reporting on corporate social responsibility, the World Justice Project’s measurement of the rule of law, the World Bank’s Doing Business index, the World Bank-supported Worldwide Governance Indicators, the World Bank’s Country Performance Institutional Assessment (CPIA), and the Transparency International Corruption (Perceptions) index. Also examined is the use of performance indicators by the European Union for accession countries and by the US Millennium Challenge Corporation in allocating US aid funds…(More)”

A new approach to measuring the impact of open data


 at SunLight Foundation: “Strong evidence on the long-term impact of open data initiatives is incredibly scarce. The lack of compelling proof is partly due to the relative novelty of the open government field, but also to the inherent difficulties in measuring good governance and social change. We know that much of the impact of policy advocacy, for instance, occurs even before a new law or policy is introduced, and is thus incredibly difficult to evaluate. At the same time, it is also very hard to detect the causality between a direct change in the legal environment and the specific activities of a policy advocacy group. Attribution is equally challenging when it comes to assessing behavioral changes – who gets to take credit for increased political engagement and greater participation in democratic processes?

Open government projects tend to operate in an environment where the contribution of other stakeholders and initiatives is essential to achieving sustainable change, making it even more difficult to show the causality between a project’s activities and the impact it strives to achieve. Therefore, these initiatives cannot be described through simple “cause and effect” relationships, as they mostly achieve changes through their contribution to outcomes produced by a complex ecosystem of stakeholders — including journalists, think tanks, civil society organizations, public officials and many more — making it even more challenging to measure their direct impact.

We at the Sunlight Foundation wanted to tackle some of the methodological challenges of the field through building an evidence base that can empower further generalizations and advocacy efforts, as well as developing a methodological framework to unpack theories of change and to evaluate the impact of open data and digital transparency initiatives. A few weeks ago, we presented our research at the Cartagena Data Festival, and today we are happy to launch the first edition of our paper, which you can read below or on Scribd.

The outputs of this research include:

  • A searchable repository of more than 100 examples on the outputs, outcomes and impacts of open data and digital technology projects;
  • Three distinctive theories of change for open data and digital transparency initiatives from the Global South;
  • A methodological framework to help develop more robust indicators of social and political change for the ecosystem of open data initiatives, by applying and revising the Outcome Mapping approach of IDRC to the field…(You can read the study at :The Social Impact of Open Data by juliakeseru)