Paper by Michael J. Burstein and Fiona Murray: “Innovation prizes in reality are significantly different from innovation prizes in theory. The former are familiar from popular accounts of historical prizes like the Longitude Prize: the government offers a set amount for a solution to a known problem, like £20,000 for a method of calculating longitude at sea. The latter are modeled as compensation to inventors in return for donating their inventions to the public domain. Neither the economic literature nor the policy literature that led to the 2010 America COMPETES Reauthorization Act — which made prizes a prominent tool of government innovation policy — provides a satisfying justification for the use of prizes, nor does either literature address their operation. In this article, we address both of these problems. We use a case study of one canonical, high profile innovation prize — the Progressive Insurance Automotive X Prize — to explain how prizes function as institutional means to achieve exogenously defined innovation policy goals in the face of significant uncertainty and information asymmetries. Focusing on the structure and function of actual innovation prizes as an empirical matter enables us to make three theoretical contributions to the current understanding of prizes. First, we offer a stronger normative justification for prizes grounded in their status as a key institutional arrangement for solving a specified innovation problem. Second, we develop a model of innovation prize governance and then situate that model in the administrative state, as a species of “new governance” or “experimental” regulation. Third, we derive from those analyses a novel framework for choosing among prizes, patents, and grants, one in which the ultimate choice depends on a trade off between the efficacy and scalability of the institutional solution….(More)”
Wikidata
Wikidata aims to create a multilingual free knowledge base about the world that can be read and edited by humans and machines alike. It provides data in all the languages of the Wikimedia projects, and allows for the central access to data in a similar vein as Wikimedia Commons does for multimedia files, it is also used by many other websites. The data on Wikidata is added by a community of volunteers both manually and by using software, much like other Wikimedia projects including Wikipedia.
Wikidata has millions of items, each representing a human, a place, a painting, a concept, etc. Each item has statements (key-value pairs), each statement in turn consisting of a property such as “birth date”, and the appropriate value for the item. Likewise, there can be statements for external IDs, such as a VIAF identifier.
Wikidata is hosted by the Wikimedia Foundation, a nonprofit charitable organization dedicated to encouraging the growth, development and distribution of free, multilingual, educational content, and to providing the full content of these wiki-based projects to the public free of chargeWikidata focuses on a basic level of useful information about the world and links to other resources for specialized data on the subject. Sources for data on Wikidata must be:
There are many reasons to add data to Wikidata including:Why add data to Wikidata[edit]
Help more people to see your information[edit]
Data from Wikidata is used by many high traffic websites including Wikipedia which is one of the most used websites in the world receiving over 15 billion page views per month.
Improve open knowledge[edit]
Wikidata hosts data that can be used on Wikimedia projects and beyond. By adding data to Wikidata you can ensure the data on your subject is well covered and up to date in all Wikimedia project languages.
Increase traffic to your website[edit]
Anyone looking at Wikidata or other sites that use Wikidata including Wikipedia can see the reference link for the source of the data.
Make your data more useful for yourself and others[edit]
By adding data to Wikidata it becomes more useful. You can:
- Combine it with other data
- Use Wikidata tools to explore the data
- Visualise your data along with data from other sources…(More)
Missing Maps
About Missing Maps: “Objectives:
- To map the most vulnerable places in the developing world, in order that international and local NGOs and individuals can use the maps and data to better respond to crises affecting the areas.
- To support OpenStreetMap, specifically the Humanitarian OpenStreetMap Team (HOT), in developing technologies, skills, workflows, and communities.
Ethics
- Using OpenStreetMap ensures that all data gathered under the project banner will be free, open, and available for use under OpenStreetMap’s open license.
- All ‘in country’ activities, i.e. local mapping and data collection, will be carried out in collaboration with local people and in a respectful manner at all times.
- When working locally, people come before the data. Meaning if the goal is to map a city there needs to be a plan in place to ensure access to technology and training for those living in that community to continue using the maps after project completion.
- Members of Missing Maps actively contribute to Missing Map’s objectives, the OpenStreetMap repository and benefitting communities, both local and international.
- Missing Maps activities emphasize building, and leaving behind, local capacity and access. We are cautious about rapid data collection without significant local participation, and always make efforts to ensure local access.
- Missing Maps activities are designed to be accessible and open for participation for individuals who want to contribute towards the project objectives.
Membership
Membership of the Missing Maps Project is open to any NGO, educational establishment or civil society group willing to contribute to the goals, and abide by the ethics, stated above. Approval of membership is the responsibility of the current member organisations….(More)”
Community Engagement Matters (Now More Than Ever)
Melody Barnes & Paul Schmitz at Stanford Social Innovation Review: “…Data-driven and evidence-based practices present new opportunities for public and social sector leaders to increase impact while reducing inefficiency. But in adopting such approaches, leaders must avoid the temptation to act in a top-down manner. Instead, they should design and implement programs in ways that engage community members directly in the work of social change. …
Under the sponsorship of an organization called Results for America, we recently undertook a research project that focused on how leaders can and should pursue data-driven social change efforts. For the project, we interviewed roughly 30 city administrators, philanthropists, nonprofit leaders, researchers, and community builders from across the United States. We began this research with a simple premise: Social change leaders now have an unprecedented ability to draw on data-driven insight about which programs actually lead to better results.
Leaders today know that babies born to mothers enrolled in certain home visiting programs have healthier birth outcomes. (The Nurse-Family Partnership, which matches first-time mothers with registered nurses, is a prime example of this type of intervention.3) They know that students in certain reading programs reach higher literacy levels. (Reading Partners, for instance, has shown impressive results with a program that provides one-on-one reading instruction to struggling elementary school students.4) They know that criminal offenders who enter job-training and support programs when they leave prison are less likely to re-offend and more likely to succeed in gaining employment. (The Center for Employment Opportunities has achieved such outcomes by offering life-skills education, short-term paid transitional employment, full-time job placement, and post-placement services.5)
Results for America, which launched in 2012, seeks to enable governments at all levels to apply data-driven approaches to issues related to education, health, and economic opportunity. In 2014, the organization published a book called Moneyball for Government. (The title is a nod to Moneyball, a book by Michael Lewis that details how the Oakland A’s baseball club used data analytics to build championship teams despite having a limited budget for player salaries.) The book features contributions by a wide range of policymakers and thought leaders (including Melody Barnes, a co-author of this article). The editors of Moneyball for Government, Jim Nussle and Peter Orszag, outline three principles that public officials should follow as they pursue social change:
- “Build evidence about the practices, policies, and programs that will achieve the most effective and efficient results so that policymakers can make better decisions.
- “Invest limited taxpayer dollars in practices, policies, and programs that use data, evidence, and evaluation to demonstrate they work.
- “Direct funds away from practices, policies, and programs that consistently fail to achieve measurable outcomes.”6
These concepts sound simple. Indeed, they have the ring of common sense. Yet they do not correspond to the current norms of practice in the public and nonprofit sectors. According to one estimate, less than 1 percent of federal nondefense discretionary spending goes toward programs that are backed by evidence. In a 2014 report, Lisbeth Schorr and Frank Farrow note that the influence of evidence on decision-making—“especially when compared to the influence of ideology, politics, history, and even anecdotes”—has been weak among policymakers and social service providers. (Schorr is a senior fellow at the Center for the Study of Social Policy, and Farrow is director of the center.)
That needs to change. There is both an economic and a moral imperative for adopting data-driven approaches. Given persistently limited budgets, public and nonprofit leaders must direct funds to programs and initiatives that use data to show that they are achieving impact. Even if unlimited funds were available, moreover, leaders would have a responsibility to design programs that will deliver the best results for beneficiaries….
The Need for “Patient Urgency”
The inclination to move fast in creating and implementing data-driven programs and practices is understandable. After all, the problems that communities face today are serious and immediate. People’s lives are at stake. If there is evidence that a particular intervention can (for example) help more children get a healthy start in life—or help them read at grade level, or help them develop marketable skills—then setting that intervention in motion is pressingly urgent.
But acting too quickly in this arena entails a significant risk. All too easily, the urge to initiate programs expeditiously translates into a preference for top-down forms of management. Leaders, not unreasonably, are apt to assume that bottom-up methods will only slow the implementation of programs that have a record of delivering positive results.
A former director of data and analytics for a US city offers a cautionary tale that illustrates this idea. “We thought if we got better results for people, they would demand more of it,” she explains. “Our mayor communicated in a paternal way: ‘I know better than you what you need. I will make things better for you. Trust me.’ The problem is that they didn’t trust us. Relationships matter. Not enough was done to ask people what they wanted, to honor what they see and experience. Many of our initiatives died—not because they didn’t work but because they didn’t have community support.”
To win such support, policymakers and other leaders must treat community members as active partners. “Doing to us, not with us, is a recipe for failure,” says Fuller, who has deep experience in building community-led coalitions. “If we engage communities, then we have a solution and we have the leadership necessary to demand that solution and hold people accountable for it.” Engaging a community is not an activity that leaders can check off on a list. It’s a continuous process that aims to generate the support necessary for long-term change. The goal is to encourage intended beneficiaries not just to participate in a social change initiative but also to champion it.
“This work takes patient urgency,” Fuller argues. “If you aren’t patient, you only get illusory change. Lasting change is not possible without community. You may be gone in 5 or 10 years, but the community will still be there. You need a sense of urgency to push the process forward and maintain momentum.” The tension between urgency and patience is a productive tension. Navigating that tension allows leaders and community members to achieve the right level of engagement.
Rich Harwood, president of the Harwood Institute for Public Innovation, makes this point in a post on his website: “Understanding and strengthening a community’s civic culture is as important to collective efforts as using data, metrics and measuring outcomes. … A weak civic culture undermines the best intentions and the most rigorous of analyses and plans. For change to happen, trust and community ownership must form, people need to engage with one another, and we need to create the right underlying conditions and capabilities for change to take root and spread.”…(More)
Changing What Counts: How Can Citizen-Generated and Civil Society Data Be Used as an Advocacy Tool to Change Official Data Collection?
New report by Open Knowledge and Civicus: “The information systems of public institutions play a crucial role in how we collectively look at and act in the world. They shape the way decisions are made, progress is evaluated, resources are allocated, issues are flagged, debates are framed and action is taken. As a United Nations (UN) report recently put it, “Data are the lifeblood of decision-making and the raw material for accountability.”1
Every information system renders certain aspects of the world visible and lets others recede into the background. Datasets highlight some things and not others. They make the world comprehensible and navigable in their own way – whether for the purposes of policy evaluation, public service delivery, administration or governance.
Given the critical role of public information systems, what happens when they leave out parts of the picture that civil society groups consider vital? What can civil society actors do to shape or influence these systems so they can be used to advance progress around social, democratic and environmental issues?
This report looks at how citizens and civil society groups can generate data as a means to influence institutional data collection. In the following pages, we profile citizen generated and civil society data projects and how they have been used as advocacy instruments to change institutional data collection – including looking at the strategies, methods, technologies and resources that have been mobilised to this end. We conclude with a series of recommendations for civil society groups, public institutions, policy-makers and funders….(More)”
The 4 Types of Cities and How to Prepare Them for the Future
John D. Macomber at Harvard Business Review: “The prospect of urban innovation excites the imagination. But dreaming up what a “smart city” will look like in some gleaming future is, by its nature, a utopian exercise. The messy truth is that cities are not the same, and even the most innovative approach can never achieve universal impact. What’s appealing for intellectuals in Copenhagen or Amsterdam is unlikely to help millions of workers in Jakarta or Lagos. To really make a difference, private entrepreneurs and civic entrepreneurs need to match projects to specific circumstances. An effective starting point is to break cities into four segments across two distinctions: legacy vs. new cities, and developed vs. emerging economies. The opportunities to innovate will differ greatly by segment.
Segment 1: Developed Economy, Legacy City
Examples: London, Detroit, Tokyo, Singapore
Characteristics: Any intervention in a legacy city has to dismantle something that existed before — a road or building, or even a regulatory authority or an entrenched service business. Slow demographic growth in developed economies creates a zero-sum situation (which is part of why the licensed cabs vs Uber/Lyft contest is so heated). Elites live in these cities, so solutions arise that primarily help users spend their excess cash. Yelp, Zillow, and Trip Advisor are examples of innovations in this context.
Implications for city leaders: Leaders should try to establish a setting where entrepreneurs can create solutions that improve quality of life — without added government expense. …
Implications for entrepreneurs: Denizens of developed legacy cities have discretionary income. …
Segment 2: Emerging Economy, Legacy City
Examples: Mumbai, São Paolo, Jakarta
Characteristics: Most physical and institutional structures are already in place in these megacities, but with fast-growing populations and severe congestion, there is an opportunity to create value by improving efficiency and livability, and there is a market of customers with cash to pay for these benefits.
Implications for city leaders: Leaders should loosen restrictions so that private finance can invest in improvements to physical infrastructure, to better use what already exists. …
Implications for entrepreneurs: Focus on public-private partnerships (PPP). …
Segment 3: Emerging Economy, New City
Examples: Phu My Hung, Vietnam; Suzhou, China; Astana, Kazakhstan; Singapore (historically)
Characteristics: These cities tend to have high population growth and high growth rates in GDP per capita, demographic and economic tailwinds that help to boost returns. The urban areas have few existing physical or social structures to dismantle as they grow, hence fewer entrenched obstacles to new offerings. There is also immediate ROI for investments in basic services as population moves in, because they capture new revenues from new users. Finally, in these cities there is an important chance to build it right the first time, notably with respect to the roads, bridges, water, and power that will determine both economic competitiveness and quality of life for decades. The downside? If this chance is missed, new urban agglomerations will be characterized by informal sprawl and new settlements will be hard to reach after the fact with power, roads, and sanitation.
Implications for city leaders: Leaders should first focus on building hard infrastructure that will support services such as schools, hospitals, and parks. …
Implications for entrepreneurs: In these cities, it’s too soon to think about optimizing existing infrastructure or establishing amusing ways for wealthy people to spend their disposable income. …
Segment 4: Developed Economy, New City
Examples and characteristics: Such cities are very rare. All the moment, almost all self-proclaimed “new cities” in the developed world are in fact large, integrated real-estate developments with an urban theme, usually in close proximity to a true municipality. Examples of these initiatives include New Songdo City in South Korea, Masdar City in Abu Dhabi, and Hafen City Hamburg in Germany.
Implications for city leaders: These satellites of existing metropolises compete for jobs and to attract talented participants in the creative economy. ….
Implications for entrepreneurs: Align with city leaders on services that are important to knowledge workers, and help build the cities’ brand. ….
Cities are different. So are solutions….(More)
The impact of a move towards Open Data in West Africa
Olivier Alais at the Georgetown Journal of International Affairs: “The concept of “open data” is not new, but its definition is quite recent. Since computers began communicating through networks, engineers have been developing standards to share data. The open data philosophy holds that some data should be freely available for use, reuse, distribute and publish without copyright and patent controls. Several mechanisms can also limit access to data like restricted database access, use of proprietary technologies or encryption. Ultimately, open data buttresses government initiatives to boost innovation, support transparency, empower citizens, encourage accountability, and fight corruption.
West Africa is primed for open data. The region experienced a 6% growth in 2014, according to the Africa Development Bank. Its Internet user network is also growing: 17% of the sub-Saharan population owned a unique smartphone in 2013, a number projected to grow to 37% by 2020 according to the GSMA. To improve the quality of governance and services in the digital age, the region must develop new infrastructures, revise digital strategies, simplify procurement procedures, adapt legal frameworks, and allow access to public data. Open data can enhance local economies and the standard of living.
This paper speaks towards the impact of open data in West Africa. First it assesses open data as a positive tool for governance and civil society. Then, it analyzes the current situation of open data across the region. Finally, it highlights specific best practices for enhancing impact in the future….(More)”
Data Collaboratives: Matching Demand with Supply of (Corporate) Data to solve Public Problems
Blog by Stefaan G. Verhulst, IrynaSusha and Alexander Kostura: “Data Collaboratives refer to a new form of collaboration, beyond the public-private partnership model, in which participants from different sectors (private companies, research institutions, and government agencies) share data to help solve public problems. Several of society’s greatest challenges — from climate change to poverty — require greater access to big (but not always open) data sets, more cross-sector collaboration, and increased capacity for data analysis. Participants at the workshop and breakout session explored the various ways in which data collaborative can help meet these needs.
Matching supply and demand of data emerged as one of the most important and overarching issues facing the big and open data communities. Participants agreed that more experimentation is needed so that new, innovative and more successful models of data sharing can be identified.
How to discover and enable such models? When asked how the international community might foster greater experimentation, participants indicated the need to develop the following:
· A responsible data framework that serves to build trust in sharing data would be based upon existing frameworks but also accommodates emerging technologies and practices. It would also need to be sensitive to public opinion and perception.
· Increased insight into different business models that may facilitate the sharing of data. As experimentation continues, the data community should map emerging practices and models of sharing so that successful cases can be replicated.
· Capacity to tap into the potential value of data. On the demand side,capacity refers to the ability to pose good questions, understand current data limitations, and seek new data sets responsibly. On the supply side, this means seeking shared value in collaboration, thinking creatively about public use of private data, and establishing norms of responsibility around security, privacy, and anonymity.
· Transparent stock of available data supply, including an inventory of what corporate data exist that can match multiple demands and that is shared through established networks and new collaborative institutional structures.
· Mapping emerging practices and models of sharing. Corporate data offers value not only for humanitarian action (which was a particular focus at the conference) but also for a variety of other domains, including science,agriculture, health care, urban development, environment, media and arts,and others. Gaining insight in the practices that emerge across sectors could broaden the spectrum of what is feasible and how.
In general, it was felt that understanding the business models underlying data collaboratives is of utmost importance in order to achieve win-win outcomes for both private and public sector players. Moreover, issues of public perception and trust were raised as important concerns of government organizations participating in data collaboratives….(More)”
digitalIMPACT.io
“The Digital Civil Society Lab at Stanford created digitalIMPACT.io to support civil society organizations in using digital data ethically, safely, and effectively. The content and tools on the site come from nonprofit and foundation partners.
digitalIMPACT.io is designed to help you learn from and share with others. The materials are provided as examples to inform your decision-making, organizational practice, and policy creation. We invite you to use and adapt what you find here, and hope you will share the practices and policies that you’ve developed. This website is only a start; real change will come as organizations integrate appropriate data management and governance throughout their work.
Digital data hold tremendous promise for civil society and they also raise new challenges. Think of digital data as both assets and liabilities. It’s time to start managing them to help you achieve your mission…. (More)”
Research Consortium on the Impact of Open Government Processes
“Mounting anecdotal evidence supports the case for open government. Sixty-nine national governments andcounting have signed on as participants in the Open Government Partnership, committing to rethinking theway they engage with citizens, while civil society organizations (CSOs) are increasingly demanding andbuilding mechanisms for this shift.Yet even as the open government agenda gains steam, relatively littlesystematic research has been done to examine the ways different types and sequences of reforms haveplayed out in various contexts, and with what impact. This is due in part to the newness of the field, but alsoto the challenges in attributing specific outcomes to any governance initiative. While acknowledging that thesearch for cookie-cutter “best practices” is of limited value, there is no doubt that reform-minded actorscould benefit from a robust analytical framework and more thorough understanding of experiences indifferent contexts to date.
To address these knowledge gaps, and to sharpen our ways of thinking about the difference that opengovernment processes can make, a range of public, academic, and advocacy organizations established aresearch consortium to convene actors, leverage support, and catalyze research. Its founding members areGlobal Integrity,The Governance Lab @ NYU (The GovLab), the World Bank’s Open Government GlobalSolutions Group, Open Government Partnership Support Unit, and Results for Development Institute. TheConsortium aims to build on existing research – including but not limited to the work of existing researchnetworks such as the MacArthur Foundation Research Network on Opening Governance – to improve ourunderstanding of the effectiveness and impact of open government reforms. That is, to what extent andthrough which channels do such reforms actually improve transparency, accessibility, and accountability; how does this play out differently in different contexts; and can we trace tangible improvements in the livesof citizens to these measures…..
Countries participating in the Open Government Partnership have signed on to the view that opengovernment is intrinsically good in terms of strengthening civic participation and democratic processes.Governments are also increasingly looking at such initiatives through a return-on-investment (ROI) lens: dosuch reforms lead to cost savings that allow them to allocate and spend resources more efficiently on publicservices? Does the availability and accessibility of open government data create economic opportunities,including jobs and new businesses? The Consortium is excited to support innovative research aimed atunderstanding the extent to which reforms deliver, not only in terms of open governance itself, but also interms of improved public sector performance and service delivery gains. This focus will also help theConsortium identify research-driven stories of the impact that open governance reforms are having….(More)”