A User’s Guide to The Periodic Table of Open Data
Identifying the elements that matter when providing increased access to data
Leveraging our research on the variables that determine Open Data’s Impact, The Open Data Policy Lab is pleased to announce the publication of a new report designed to assist organizations in implementing the elements of a successful data collaborative: A User’s Guide to The Periodic Table of Open Data.
The User's Guide is a fillable document designed to empower data stewards and others seeking to improve data access. It can be used as a checklist and tool to weigh different elements based on their context and priorities. By completing the forms (offline/online), you will be able to take a more comprehensive and strategic view of what resources and interventions may be required.
Download and fill out the User’s Guide to operationalize the elements in your data initiative
In conjunction with the release of our User's Guide, the Open Data Policy Lab is pleased to present a completely reworked version of our Periodic Table of Open Data Elements, first launched alongside in 2016. We sought to categorize the elements that matter in open data initiatives into five categories: problem and demand definition, capacity and culture, governance and standards, personnel and partnerships, and risk mitigation. More information on each can be found in the attached report or in the interactive table below.
Read more about the Periodic Table of Open Data Elements and how you can use it to support your work.
Problem and Demand Definition
Bg
Benefits and Goals
Bg
Benefits and Goals
Open data projects can benefit from articulating the tangible value that they will produce for their project’s sponsors and the public to maintain interest and engagement. Clear, quantifiable goals, coupled with metrics, can demonstrate progress.
Di
Data Audit and Inventory
Di
Data Audit and Inventory
An important aspect of a data-driven initiative is understanding what data is collected and generated and which can still be made available. A data audit allows data practitioners to understand what they have access to and who is accountable for the datasets
Ds
Data Ecosystem and Stakeholder Assessment
Ds
Data Ecosystem and Stakeholder Assessment
When data, expertise, or other resources are not immediately available, a robust understanding of the broader ecosystem and stakeholders can be useful in finding partner agencies, businesses, and nonprofits who can fill those gaps.
Pr
Problem Refinement
Pr
Problem Refinement
Effective data-driven initiatives are often those that identify a specific purpose or issue to solve, the data needed to produce insights, and how those insights can be acted upon to produce real public value. It helps make the effort targeted and purpose-specific.
Ur
User Research
Ur
User Research
User research helps data practitioners identify, map, and understand a problem, its components, and users’ needs. It pushes against the notion of “if you build it, they will come.”
Capacity and Culture
Ci
Culture and Institutional
Buy-in
Ci
Culture and Institutional
Buy-in
By gaining approval from the leaders of their organization and fellow associates, open data advocates can gather the resources needed to unlock institutional resources and overcome roadblocks.
Di
Data Infrastructure
Di
Data Infrastructure
Sophisticated data portals, repositories, and other technological assets are important for collecting, storing, managing, and sharing open data assets.
Ic
Institutional Data Literacy and Capacity
Ic
Institutional Data Literacy and Capacity
Data practitioners can increase the societal and organizational value created through data reuse by bolstering their personnel’s skills and distributing those with skills throughout the organization.
Is
Issue Salience
Is
Issue Salience
When data practitioners can connect their project to an issue of substantial interest to their target audience, institution, or the public, they are more likely to receive support and funding than if their work had no resonance at all.
Pe
Public Engagement
Pe
Public Engagement
People often will not engage with data efforts if they don’t know they exist and don’t know how data can help them. By promoting trust and understanding in data initiatives and processes, practitioners can increase the likelihood their work is adopted by the public.
Rs
Resource Availability and Sustainability
Rs
Resource Availability and Sustainability
Technological innovation and infrastructure development can be cost-intensive exercises with extended time frames. Organizations often benefit if they have internal and external sources of funding to support long-term, responsible data reuse.
Rf
Responsive Feedback Loops
Rf
Responsive Feedback Loops
By creating mechanisms for data users and beneficiaries to provide input on a data initiative, practitioners can proactively address risks as they arise and foster public trust by demonstrating their commitment to act on concerns.
Sl
Social License
Sl
Social License
The acceptance granted to a company or organization by a community is called a social license. Projects that gain a social license to operate (after meaningfully informing and engaging with people who will be impacted) are less likely to suffer backlash and may support important ideation.
St
Strategic Leadership
St
Strategic Leadership
Project and organizational leadership are central in the success of open data projects. Engaged leaders can enact policies, mobilize resources, and advocate for data openness.
Governance
Dl
Data Licensing
Dl
Data Licensing
Data licensing regimes protect and promote the re-use of data by outlining conditions under which practitioners can use and re-use data.
Dq
Data Quality
Dq
Data Quality
Good data quality allows data practitioners to reach insights that reflect the issue they are studying. If data quality is unaddressed, it can lead to inaccurate or harmful results.
Pr
Principles
Pr
Principles
Principles help data practitioners and those they collaborate with to align toward the same goals. They can be useful for determining the type of data collaboration, as well as the practices and processes used.
Pa
Data Standards
Pa
Data Standards
Data standards are the technical specifications that make it possible to share, exchange and combine data. They also provide the framework necessary for data collaboration and enable machine readability and data portability.
Cd
Contracts and Data Sharing Agreements
Cd
Contracts and Data Sharing Agreements
Contracts and data sharing agreements establish the terms for how data is shared between parties. They can be useful for defining the structure of an open data initiative or data collaboration in a way that lets each party contribute what they are most capable of.
Od
Open by Default
Od
Open by Default
“Open by default” refers to the presumption that data should be published in absence of a legitimate justification to the contrary. This principle can allow insights to reach as many people as possible.
Pp
Policies, Positions, and Procedures
Pp
Policies, Positions, and Procedures
Policies, professional positions, and procedures guide how to progress on a data initiative by outlining the necessary roles and guidelines.
Partnerships
Ds
Data Stewards
Ds
Data Stewards
Data stewards are responsible data leaders empowered to seek new ways to create public value through cross-sector data collaboration. They can be useful for proactively collaborating, protecting customers, and acting on opportunities.
Do
Domain Experts
Do
Domain Experts
Domain experts are individuals with knowledge of a particular domain or sector whose knowledge can be used to better identify opportunities to (re)use data for the public benefit or otherwise identify, design, analyze, and communicate insights about open data.
Tp
Third Party Supporters
Tp
Third Party Supporters
Organizations, institutions, and individuals invested in a project’s success can be critical for building a broad base of support for a data-driven effort. These supporters can be cultivated and engaged to build a project audience.
Risks
Se
Data Security
Se
Data Security
Organizations and individuals can be reluctant to share data if they believe it will be exposed in ways that cause harm. By protecting against attacks and breaches, organizations can reduce distrust in their work.
Id
Inclusive Design
Id
Inclusive Design
Data can often consolidate and reinforce privileges in ways that benefit elites. By remaining mindful of inequalities and including more inclusive design practices into their work, data practitioners can reduce asymmetries and improve the impact of their work so it is broadly felt.
Ia
Institutional Alignment
Ia
Institutional Alignment
By encouraging all stakeholders to share a common end goal, data practitioners can increase the probability that all the work put into a project is complementary and effectively uses the resources available.
Lr
Legal and Regulatory Requirements
Lr
Legal and Regulatory Requirements
Legal and regulatory requirements can be an effective way of helping data practitioners understand their responsibilities and be accountable for misuse. These requirements can build trust and minimize harm.
Pd
Privacy by Design
Pd
Privacy by Design
By instituting privacy in the design of open data efforts, organizations can minimize risk and boost public confidence and trust in their work.
Pe
Proactive Data Holder Engagement
Pe
Proactive Data Holder Engagement
Proactively engaging with data holders can minimize the chances of missing or ignoring opportunities of using siloed data. It can bolster projects by helping them make use of all the resources available.
Increase your window size to enable interactive table
Problem and Demand Definition
Particularly in developing economies, where resources to put toward data release or data use can be in short supply, a clear, detailed understanding of the problem to be addressed by open data can help to ensure that efforts are targeted and optimized. Some of the most effective open data projects examined here are laser-focused on a specific user group (e.g., smallholder farmers in Colombia or Ghana), or identified gap (e.g., the lack of power quality in the Indian energy sector). Clearly defining the problem can also aid in the development of metrics of success and a strategy for monitoring progress against a well-defined baseline. Many of the initiatives studied as part of this project lacked such a monitoring strategy, making assessments of impact, evidence-driven iteration, and the demonstration of return on investment more challenging.
Bg
Benefits and Goals
Open data projects can benefit from articulating the tangible value that they will produce for their project’s sponsors and the public to maintain interest and engagement. Clear, quantifiable goals, coupled with metrics, can demonstrate progress.
Di
Data Audit and Inventory
An important aspect of a data-driven initiative is understanding what data is collected and generated and which can still be made available. A data audit allows data practitioners to understand what they have access to and who is accountable for the datasets
Ds
Data Ecosystem and Stakeholder Assessment
When data, expertise, or other resources are not immediately available, a robust understanding of the broader ecosystem and stakeholders can be useful in finding partner agencies, businesses, and nonprofits who can fill those gaps.
Pr
Problem Refinement
Effective data-driven initiatives are often those that identify a specific purpose or issue to solve, the data needed to produce insights, and how those insights can be acted upon to produce real public value. It helps make the effort targeted and purpose-specific.
Ur
User Research
User research helps data practitioners identify, map, and understand a problem, its components, and users’ needs. It pushes against the notion of “if you build it, they will come.”
Capacity and Culture
Particularly in developing economies, where resources to put toward data release or data use can be in short supply, a clear, detailed understanding of the problem to be addressed by open data can help to ensure that efforts are targeted and optimized. Some of the most effective open data projects examined here are laser-focused on a specific user group (e.g., smallholder farmers in Colombia or Ghana), or identified gap (e.g., the lack of power quality in the Indian energy sector). Clearly defining the problem can also aid in the development of metrics of success and a strategy for monitoring progress against a well-defined baseline. Many of the initiatives studied as part of this project lacked such a monitoring strategy, making assessments of impact, evidence-driven iteration, and the demonstration of return on investment more challenging.
Ci
Culture and Institutional
Buy-in
By gaining approval from the leaders of their organization and fellow associates, open data advocates can gather the resources needed to unlock institutional resources and overcome roadblocks.
Di
Data Infrastructure
Sophisticated data portals, repositories, and other technological assets are important for collecting, storing, managing, and sharing open data assets.
Ic
Institutional Data Literacy and Capacity
Data practitioners can increase the societal and organizational value created through data reuse by bolstering their personnel’s skills and distributing those with skills throughout the organization.
Is
Issue Salience
When data practitioners can connect their project to an issue of substantial interest to their target audience, institution, or the public, they are more likely to receive support and funding than if their work had no resonance at all.
Pe
Public Engagement
People often will not engage with data efforts if they don’t know they exist and don’t know how data can help them. By promoting trust and understanding in data initiatives and processes, practitioners can increase the likelihood their work is adopted by the public.
Rs
Resource Availability and Sustainability
Technological innovation and infrastructure development can be cost-intensive exercises with extended time frames. Organizations often benefit if they have internal and external sources of funding to support long-term, responsible data reuse.
Rf
Responsive Feedback Loops
By creating mechanisms for data users and beneficiaries to provide input on a data initiative, practitioners can proactively address risks as they arise and foster public trust by demonstrating their commitment to act on concerns.
Sl
Social License
The acceptance granted to a company or organization by a community is called a social license. Projects that gain a social license to operate (after meaningfully informing and engaging with people who will be impacted) are less likely to suffer backlash and may support important ideation.
St
Strategic Leadership
Project and organizational leadership are central in the success of open data projects. Engaged leaders can enact policies, mobilize resources, and advocate for data openness.
Governance
Particularly in developing economies, where resources to put toward data release or data use can be in short supply, a clear, detailed understanding of the problem to be addressed by open data can help to ensure that efforts are targeted and optimized. Some of the most effective open data projects examined here are laser-focused on a specific user group (e.g., smallholder farmers in Colombia or Ghana), or identified gap (e.g., the lack of power quality in the Indian energy sector). Clearly defining the problem can also aid in the development of metrics of success and a strategy for monitoring progress against a well-defined baseline. Many of the initiatives studied as part of this project lacked such a monitoring strategy, making assessments of impact, evidence-driven iteration, and the demonstration of return on investment more challenging.
Dl
Data Licensing
Data licensing regimes protect and promote the re-use of data by outlining conditions under which practitioners can use and re-use data.
Dq
Data Quality
Good data quality allows data practitioners to reach insights that reflect the issue they are studying. If data quality is unaddressed, it can lead to inaccurate or harmful results.
Pr
Principles
Principles help data practitioners and those they collaborate with to align toward the same goals. They can be useful for determining the type of data collaboration, as well as the practices and processes used.
Pa
Data Standards
Data standards are the technical specifications that make it possible to share, exchange and combine data. They also provide the framework necessary for data collaboration and enable machine readability and data portability.
Cd
Contracts and Data Sharing Agreements
Contracts and data sharing agreements establish the terms for how data is shared between parties. They can be useful for defining the structure of an open data initiative or data collaboration in a way that lets each party contribute what they are most capable of.
Od
Open by Default
“Open by default” refers to the presumption that data should be published in absence of a legitimate justification to the contrary. This principle can allow insights to reach as many people as possible.
Pp
Policies, Positions, and Procedures
Policies, professional positions, and procedures guide how to progress on a data initiative by outlining the necessary roles and guidelines.
Partnerships
In many high-impact open data projects, partnerships within and especially across sectors play a key role in enabling success. Whether creating touchpoints with citizens through partnerships with civil society, informing the public through media partnerships, or filling important data gaps through partnerships with private sector entities, open data suppliers and users often improve outcomes through collaboration.
Ds
Data Stewards
Data stewards are responsible data leaders empowered to seek new ways to create public value through cross-sector data collaboration. They can be useful for proactively collaborating, protecting customers, and acting on opportunities.
Do
Domain Experts
Domain experts are individuals with knowledge of a particular domain or sector whose knowledge can be used to better identify opportunities to (re)use data for the public benefit or otherwise identify, design, analyze, and communicate insights about open data.
Tp
Third Party Supporters
Organizations, institutions, and individuals invested in a project’s success can be critical for building a broad base of support for a data-driven effort. These supporters can be cultivated and engaged to build a project audience.
Risks
The release and use of open data in developing economies are not without risks. An upfront mapping and consideration of risks associated with intended uses of open data can allow practitioners to design programs from the outset in a way that is well-positioned to overcome or mitigate those risks. The risks listed here, however, should not be considered arguments against using open data in development. Rather, they are reasons for taking a more fine-grained approach that pays close attention to the empirical evidence, sifting out what works and what does not, and identifying conditions for scaling and replication.
Se
Data Security
Organizations and individuals can be reluctant to share data if they believe it will be exposed in ways that cause harm. By protecting against attacks and breaches, organizations can reduce distrust in their work.
Id
Inclusive Design
Data can often consolidate and reinforce privileges in ways that benefit elites. By remaining mindful of inequalities and including more inclusive design practices into their work, data practitioners can reduce asymmetries and improve the impact of their work so it is broadly felt.
Ia
Institutional Alignment
By encouraging all stakeholders to share a common end goal, data practitioners can increase the probability that all the work put into a project is complementary and effectively uses the resources available.
Lr
Legal and Regulatory Requirements
Legal and regulatory requirements can be an effective way of helping data practitioners understand their responsibilities and be accountable for misuse. These requirements can build trust and minimize harm.
Pd
Privacy by Design
By instituting privacy in the design of open data efforts, organizations can minimize risk and boost public confidence and trust in their work.
Pe
Proactive Data Holder Engagement
Proactively engaging with data holders can minimize the chances of missing or ignoring opportunities of using siloed data. It can bolster projects by helping them make use of all the resources available.
Reference
1World Wide Web Foundation, Open Data Barometer, Fourth Edition, 2016, http://opendatabarometer.org/.
2See Open Government Partnership website, http://www.opengovpartnership.org/, accessed November 30, 2016.
3Andrew Young, Stefaan Verhulst, and Juliet McMurren, “The GovLab Selected Readings on Open Data for Developing Economies,” August 1, 2016, http://thegovlab.org/open-data-for-developing-economies/.
4See Appendix D for an annotated selection of the key Readings.
5GovLab, “Open Data: What’s in a Name,” January 16, 2014, GovLab Blog, http://thegovlab.org/open-data-whats-in-a-name/.
6Open by Default; Timely and Comprehensive; Accessible and Usable; Comparable and Interoperable; For Improved Governance and Citizen Engagement; For Inclusive Development and Innovation. http://opendatacharter.net.
7Open Data for Development Network, Open Data for Development: Building an inclusive data revolution, Annual Report, 2015, 11, http://od4d.com/wp-content/uploads/2016/06/OD4D_annual_report_2015.pdf.
8See 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.
9At the same time, there is a growing recognition of open data’s potential to meet the Sustainable Development Goals (SDGs). The World Bank, for instance, has explored the various ways in which open data could help to make progress toward the SDGs. Similarly, a recent White Paper by the Open Data Institute (ODI) concludes: “Open data can make an impact across the globe. Its role in combating development challenges of the next 15 years, both as a tool for measuring progress and in finding solutions, is becoming more clear.” See The World Bank, “Open Data for Sustainable Development,” Policy Note, August 2015, http://bit.ly/2aGjaJ4; and Open Data Institute, Supporting Sustainable Development with Open Data, 2015, 3, http://theodi.org/supporting-sustainable-development-with-open-data.
10Tim Davies, for instance, notes that, “researchers and other users outside of government may highlight inaccuracies and inconsistencies between datasets” as a result of access to open data, and thereby improving data quality and usefulness. Tim Davies, “Open Data in Developing Countries: Emerging insights from Phase I,” Open Data Research, July 15, 2014, http://opendataresearch.org/sites/default/files/publications/Phase 1 - Synthesis - Full Report-print.pdf.
11Aspasia Papaloi and Dimitris Gouscos, “Parliamentary Information Visualization as a Means for Legislative Transparency and Citizen Empowerment,” Journal of Democracy and Open Government, 2013, http://www.jedem.org/index.php/jedem/article/view/222/183.
12“By using common open repositories, public administrations can save time and money from the automisation of internal data exchange,” Raimondo Lemma, Federico Morando and Michele Osella, “Breaking Public Administrations’ Data Silos: The case of Open-DAI, and a comparison between open data platforms,” Journal of Democracy & Open Government, 2014, http://www.jedem.org/index.php/jedem/article/view/304.
13Jae-Nam Lee, Juyeon Ham and Byounggu Choi, “Effect of Government Data Openness on a Knowledge-based Economy,” Procedia Computer Science, 91, 2016. http://www.sciencedirect.com/science/article/pii/S1877050916312364.
14Ali Clare, David Sangokoya, Stefaan Verhulst and Andrew Young, “Open Contracting and Procurement In Slovakia,” GovLab, Accessed October 25, 2016, http://odimpact.org/case-open-contracting-and-procurement-in-slovakia.html.
15World Bank, World Development Report 2016: Digital Dividends, World Bank, 2016, 4, http://documents.worldbank.org/curated/en/896971468194972881/pdf/102725-PUB-Replacement-PUBLIC.pdf.
16Laura Dabbish, et al., “Social Coding in GitHub: Transparency and collaboration in an open software repository,” Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work, February 11, 2012, http://dl.acm.org/citation.cfm?id=2145396.
17Dietmar Harhoff and Karim R. Lakhani (eds.), Revolutionizing Innovation: Users, communities, and open innovation, Boston: MIT Press, 2016.
18See GovLab, “Open Data: What’s in a Name,” January 16, 2014, GovLab Blog, http://thegovlab.org/open-data-whats-in-a-name/.
19See also (in Spanish), Silvana Fumega, “Algunas Ideas para ‘Debates Conceptuales sobre el Gobierno Abierto,’” September 25, 2016, http://silvanafumega.blogspot.fr/2016/09/algunas-ideas-para-debates-conceptuales.html.
20George Washington Law Review 26, no. 1 (October 1957), http://heinonline.org/HOL/Page?handle=hein.journals/gwlr26&div=10&id=&page=&collection=journals.
22Open Government Partnership, “Open Government Declaration,” http://www.opengovpartnership.org/about/open-government-declaration.
23See Matthew L. Smith and Katherine M.A. Reilly, eds., Open Development: Networked innovations in international development, MIT Press, 2013, http://idl-bnc.idrc.ca/dspace/bitstream/10625/52348/1/IDL-52348.pdf.
25Ibid.
26Jonathan Gray, “Five Ways Open Data Can Boost Democracy Around the World,” The Guardian, February 20, 2015, https://www.theguardian.com/public-leaders-network/2015/feb/20/open-data-day-fairer-taxes.
27Duncan Edwards and Rosie McGee, eds., “Opening Governance,” IDS Bulletin 47, no. 1 (January 2016), https://opendocs.ids.ac.uk/opendocs/bitstream/handle/123456789/7686/IDSB_47_1_10.190881968-2016.103.pdf?sequence=1.
28José M. Alonso, “Measuring Impact of Open Government Data — Open Data Research (South) Meeting Report,” May 24, 2012, http://webfoundation.org/2012/05/odrs-meeting1-report-available/.
29Martin Hilbert, “Big Data for Development: A review of promises and challenges,” Development Policy Review 34, no. 1 (January 2016), http://onlinelibrary.wiley.com/doi/10.1111/dpr.12142/full.
30See also Andrew Young, Stefaan Verhulst, and Juliet McMurren, “The GovLab Selected Readings on Open Data for Developing Economies,” August 1, 2016, http://thegovlab.org/open-data-for-developing-economies/.
31The author of a case study from the participating Open Data Institute, which disseminated the results of the effort, notes that, “Whether or not the improved information flow and accessibility to results — enabled by the application of open data — led to increased trust in the election process, or even an improved process, is not something that we can or indeed set out to prove or show empirically, although the outcome of this case study is certainly supportive of that conclusion.” Anna Scott, “Case Study: Burkina Faso’s open elections,” Open Data Institute, October 2016, https://theodi.org/case-study-burkina-fasos-open-elections#1.
32Auralice Graft, Stefaan Verhulst and Andrew Young , “Indonesia’s Kawal Pemilu — Elections: Free fair and open data,” The Governance Lab, http://odimpact.org/case-indonesias-kawal-pemilu.html.
33Third International Open Data Conference (IODC), “Enabling the Data Revolution: An International Open Data Roadmap,” http://1a9vrva76sx19qtvg1ddvt6f.wpengine.netdna-cdn.com/wp-content/uploads/2015/09/IODC2015-Final-Report-web.pdf.
34Jonathan Gray, “Open Budget Data: Mapping the Landscape,” https://github.com/okfn/research/blob/master/research/OpenBudgetData.pdf.
35“Credit Happy Brazilian Minister Admits Mistake and Resigns,” Merco Press, February 3, 2008, http://en.mercopress.com/2008/02/03/credit-happy-brazilian-minister-admits-mistake-and-resigns.
36Alan Freihof Tygel, Maria Luiza Machado Campos and Celso Alexandre Souza de Alvear, “Teaching Open Data for Social Movements: A research strategy, Journal of Community Informatics, 11, no. 3 (2015), http://ci-journal.net/index.php/ciej/article/view/1220/1165.
37See, for example, James Manyika, et al., “Open Data: Unlocking innovation and performance with liquid information,” McKinsey & Company, October 2013, http://www.mckinsey.com/business-functions/business-technology/our-insights/open-data-unlocking-innovation-and-performance-with-liquid-information.
38Open Data Fact Sheet, “Business, Research and Consulting,” Fall 2016, http://opendataimpactmap.org/Bus_Factsheet.pdf.
39Open Data Fact Sheet, “IT and Geospacial,” http://opendataimpactmap.org/IT_Factsheet.pdf.
41Empowering Local Communities with Open Data and Interactive Community Mapping,” Caribbean Open Institute, http://caribbeanopeninstitute.org/node/133.
42Evangelia Berdou, “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.
43Open Data Watch, “Real-time Data for Mapping Forest Change Worldwide,” Data Impacts Case Studies, http://dataimpacts.org/project/forest-watch/.
44Victor Montoro, “Satellite-based Forest Mapping PlatformHhits Its Stride,” Mongabay, June 26, 2015, https://news.mongabay.com/2015/06/satellite-based-forest-mapping-platform-hits-its-stride/.
45Andrew Young and Stefaan Verhulst, “Battling Ebola in Sierra Leone: Data sharing to improve crisis response,” GovLab, http://odimpact.org/case-battling-ebola-in-sierra-leone.html.
46Michael P. Canares, “Opening the Gates: Will open data initiatives make local government in the Philippines more transparent?” Open Data Research Network Report, 2014, http://www.opendataresearch.org/content/2014/672/opening-gates-will-open-data-initiatives-make-local-governments-philippines-more.
47“UN Reviews Security after Pakistani Taliban ‘Threat,’” BBC News, August 26, 2010, http://www.bbc.com/news/world-south-asia-11095267.
48See Andrew Young and Stefaan Verhulst, “Kenya’s Open Duka: Open data for transactional transparency,” GovLab, http://odimpact.org/case-kenyas-open-duka.html.
49See Francois Van Schalkwyk, et al., “Open Data Intermediaries in Developing Countries,” Journal of Community Informatics 12, no. 2 (2016), http://ci-journal.net/index.php/ciej/article/view/1146.
50See, for example, Alexandra Wood, David O’Brien, and Urs Gasser, “Privacy and Open Data Research Briefing,” 2016, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2842816.
51See, for example, Ira Rubinstein and Woodrow Hartzog, “Anonymization and Risk,” 2015, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2646185.
52Stefan Kulk and Bastiaan van Loenen, “Brave New Open Data World?” International Journal of Spatial Data Infrastructures Research, 7, 2012, https://www.researchgate.net/profile/S_Kulk/publication/254811532_Brave_New_Open_Data_World/links/0c96053a43af7ceb94000000.pdf.
53David Burt, et al., “The Cybersecurity Risk Paradox: Impact of social, economic, and technological factors on rates of malware,” Microsoft Security Intelligence Report Special Edition, January 2014, http://download.microsoft.com/download/E/1/8/E18A8FBB-7BA6-48BD-97D2-9CD32A71B434/Cybersecurity-Risk-Paradox.pdf.
54See, Michael Canares and Satyarupa Shekhar, “Open Data and Sub-national Governments: Lessons from developing countries,” Open Data for Development, 2016, http://od4d.com/wp-content/uploads/2016/01/ODDC-2-Open-Data-and-Sub-national-Governments.pdf.
55Michael Gurstein, “Open Data: Empowering the empowered or effective data use for everyone?” First Monday, February 2011, http://firstmonday.org/article/view/3316/2764.
56See odimpact.org.
57See, for example, Christian Villum, “Open-Washing”—The Difference between Opening Your Data and Simply Making Them Available,” Open Data International Blog, March 10, 2014, https://blog.okfn.org/2014/03/10/open-washing-the-difference-between-opening-your-data-and-simply-making-them-available/; and “#openwashing…anyone?” Web Foundation Blog, October 31, 2016, http://webfoundation.org/2016/10/openwashing-anyone/.
58Benjamin Sovacool and Nathan Andrews, “Does Transparency Matter? Evaluating the governance impacts of the Extractive Industries Transparency Initiative in Azerbaijan and Liberia,” Resources Policy 45 (2015), https://eiti.org/sites/default/files/documents/Sovacool%20%26%20Andrews%20%5B2015%5D%20-%20Does%20transparency%20matter%20-%20%20Evaluating%20the%20governance%20impacts%20of%20the%20Extractive%20Industries%20Transparency%20Initiative%20%28EITI%29%20in%20Azerbaijan%20and%20Liberia.pdf.
59See the Open Data Charter website, http://opendatacharter.net/.
60François van Schalkwyk, et al., Open Data Intermediaries in Developing Countries,” ODDC, 2015, http://bit.ly/2aJztWi.
61Organization for Economic Cooperation and Development, “Aid at a Glance Charts,” http://www.oecd.org/dac/stats/aid-at-a-glance.htm.
62Tawnya Bosko and Matthew Briskin, "Transparency in Healthcare: Where does it stand?" Management in Healthcare 1, no.1 (2016): 83-96.
63Like similar efforts in Paraguay and Singapore, researchers in India demonstrated how open data can be analyzed using statistical modeling and machine learning to determine how transmission of dengue (or other mosquito-borne illnesses like Zika) could be minimized through increased citizen awareness and/or more strategic allocation of resources. Vandana Srivastava and Biplave Srivastava, “Towards Timely Public Health Decisions to Tackle Seasonal Diseases with Open Government Data,” World Wide Web and Public Health Intelligence: Papers from the AAAI-14 Workshop, June 18, 2015, http://www.aaai.org/ocs/index.php/WS/AAAIW14/paper/view/8728/8221.
64Open Data Watch, “Data Impacts Case Studies: Using satellite and cell phone data to eliminate malaria in Namibia,” http://dataimpacts.org/project/malaria/.
65Seember Nyager, “Can Data Help Us Attain Healthier Lives?” Budeshi, May 15, 2016, http://www.budeshi.org/2016/05/can-data-help-us-attain-healthier-lives/.
66In regard to the discursive attributes related to the terms “participation,” “empowerment” and “citizenship” in aid, see Andrea Cornwall, Beneficiary, Consumer, Citizen: Perspectives on participation for poverty reduction, Stockholm: Sida, 2000, http://www.alnap.org/resource/10271.
67Vanessa Humphries, “Improving Humanitarian Coordination: Common challenges and lessons learned from the cluster approach,” The Journal of Humanitarian Assistance 30 (2013).
68Eleanor Goldbert, “Open Data Platform Lets Aid Groups Respond More Efficiently to Crises,” Huffington Post, May 31, 2016, http://www.huffingtonpost.com/entry/open-data-platform-enables-aid-groups-to-respond-more-efficiently-to-crises_us_574876fee4b03ede4414a6a4.
69The Humanitarian Data Exchange, https://data.humdata.org/.
70“Diplomacy and Aid in Africa,” The Economist, April 14, 2016, http://www.economist.com/blogs/graphicdetail/2016/04/daily-chart-10.
71Mzwandile Jacks, “China Emerges as Tanzania’s Major Investor,” Ventures Africa, January 29, 2014, http://venturesafrica.com/china-emerges-as-tanzanias-major-investor/.
72“Open Data’s Role in Nepal’s Earthquake,” ICT.govt.nz, 2015, https://www.ict.govt.nz/assets/Uploads/Case-Study-Nepal-Earthquake2.pdf.
73Nirab Pudasaini, “Open Source and Open Data’s Role in Nepal Earthquake Relief,” OpenSource.com, June 8, 2016, https://opensource.com/life/16/6/open-source-open-data-nepal-earthquake.
74Krishna Sapkota, “Exploring the Impacts of Open Aid and Budget Data in Nepal,” Freedom Forum, August 2014, http://www.opendataresearch.org/sites/default/files/publications/Open%20Aid%20and%20Budget%20Data%20in%20Nepal%20-%2015th%20Sept-print.pdf.
75Jane Battersby and Jonathan Crush, “Africa’s Urban Food Deserts,” Urban Forum 25, no. 2, Springer Netherlands, 2014.
76See also the Agriculture Open Data Package developed by GODAN, http://AgPack.info.
77“Big Data, Big Prospects: Crunching data for farmers’ climate adaptation,” CCAFS Annual Report 2015, https://ccafs.cgiar.org/blog/big-data-big-prospects-crunching-data-farmers-climate-adaptation#.WFBRtKOZORu.
78CABI, “Plantwise Knowledge Bank Wins Open Data Award for Social Impact,” Plantwise Blog, November 5, 2014, https://blog.plantwise.org/2014/11/05/plantwise-knowledge-bank-wins-open-data-award-for-social-impact/.
79Business Call to Action, “Empowering Farmers Through Mobile Communication in West Africa,” The Guardian, October 15, 2014, https://www.theguardian.com/sustainable-business/2014/oct/22/empowering-farmers-through-mobile-communication-in-west-africa.
80“Fellowship Programme,” School of Data, http://schoolofdata.org/fellowship-programme/.
81http://wmmd.codeforafrica.org.
82Michael Gurstein, “Open Data: Empowering the empowered or effective data use for everyone,” First Monday, February 2011, http://journals.uic.edu/ojs/index.php/fm/article/view/3316/2764; Kevin Donovan, “Seeing Like a Slum: Towards open, deliberative development,” Georgetown Journal of International Affairs 13, no. 1, April 26, 2012, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2045556.
83http://www.greenbuttondata.org.
84Benjamin Sovacool and Nathan Andrews, “Does Transparency Matter? Evaluating the governance impacts of the Extractive Industries Transparency Initiative in Azerbaijan and Liberia,” Resources Policy 45 (2015), https://eiti.org/sites/default/files/documents/Sovacool%20%26%20Andrews%20%5B2015%5D%20-%20Does%20transparency%20matter%20-%20%20Evaluating%20the%20governance%20impacts%20of%20the%20Extractive%20Industries%20Transparency%20Initiative%20%28EITI%29%20in%20Azerbaijan%20and%20Liberia.pdf.
85“Azerbaijan Suspended from the EITI – a Bankwatch and Counter Balance statement,” Bankwatch, March 9, 2017, http://bankwatch.org/news-media/for-journalists/press-releases/azerbaijan-suspended-eiti-%E2%80%93-bankwatch-and-counter-balance-.
86Andrew Young and Stefaan Verhulst, “Mexico’s Mejora Tu Escuela: Empowering citizens to make data-driven decisions about education,” GovLab, http://odimpact.org/case-mexicos-mejora-tu-escuela.html.
87http://www.qedu.org.br.
88Stefaan Verhulst, “Research Consortium on the Impact of Open Government Processes,” The GovLab Blog, February 11, 2016, http://thegovlab.org/research-consortium-on-the-impact-of-open-government-processes/.
89The GovLab Academy Canvas, http://canvas.govlabacademy.org.
