Paper by Iryna Susha, Marijn Janssen and Stefaan Verhulst: “Data collaboratives present a new form of cross-sector and public-private partnership to leverage (often corporate) data for addressing a societal challenge. They can be seen as the latest attempt to make data accessible to solve public problems. Although an increasing number of initiatives can be found, there is hardly any analysis of these emerging practices. This paper seeks to develop a taxonomy of forms of data collaboratives. The taxonomy consists of six dimensions related to data sharing and eight dimensions related to data use. Our analysis shows that data collaboratives exist in a variety of models. The taxonomy can help organizations to find a suitable form when shaping their efforts to create public value from corporate and other data. The use of data is not only dependent on the organizational arrangement, but also on aspects like the type of policy problem, incentives for use, and the expected outcome of data collaborative….(More)”
Developing transparency through digital means? Examining institutional responses to civic technology in Latin America
Rebecca Rumbul at Journal of eDemocracy and Open Government: “A number of NGOs across the world currently develop digital tools to increase citizen interaction with official information. The successful operation of such tools depends on the expertise and efficiency of the NGO, and the willingness of institutions to disclose suitable information and data. It is this institutional interaction with civic technology that this study examines. The research explores empirical interview data gathered from government officials, public servants, campaigners and NGO’s involved in the development and implementation of civic technologies in Chile, Argentina and Mexico. The findings identify the impact these technologies have had upon government bureaucracy, and the existing barriers to openness created by institutionalised behaviours and norms. Institutionalised attitudes to information rights and conventions are shown to inform the approach that government bureaucracy takes in the provision of information, and institutionalised procedural behaviour is shown to be a factor in frustrating NGOs attempting to implement civic technology….(More)”.
Making Citizen-Generated Data Work
Danny Lämmerhirt at Open Knowledge: “We are pleased to announce a new research series investigating how citizens and civil society create data to drive sustainable development. The series follows on from earlier papers on Democratising The Data Revolution and how citizen-generated data can change what public institutions measure. The first report “Making Citizen-Generated Data Work” asks what makes citizens and others want to produce and use citizen-generated data. It was written by myself, Shazade Jameson, and Eko Prasetyo.
“The goal of Citizen-Generated Data is to monitor, advocate for, or drive change around an issue important to citizens”
The report demonstrates that citizen-generated data projects are rarely the work of individual citizens. Instead, they often depend on partnerships to thrive and are supported by civil society organisations, community-based organisations, governments, or business. These partners play a necessary role to provide resources, support, and knowledge to citizens. In return, they can harness data created by citizens to support their own mission. Thus, citizens and their partners often gain mutual benefits from citizen-generated data.
But if CGD projects rely on partnerships, who has to be engaged, and through which incentives, to enable CGD projects to achieve their goals? How are such multi-stakeholder projects organised, and which resources and expertise do partners bring into a project? What can other projects do to support and benefit their own citizen-generated data initiatives? This report offers recommendations to citizens, civil society organisations, policy-makers, donors, and others on how to foster stronger collaborations….(Read the full report here).
The Open Science Prize
“The Open Science Prize is a new initiative from the Wellcome Trust, US National Institutes of Health and Howard Hughes Medical Institute to encourage and support the prototyping and development of services, tools and/or platforms that enable open content – including publications, datasets, code and other research outputs – to be discovered, accessed and re-used in ways that will advance research, spark innovation and generate new societal benefits….
The volume of digital objects for research available to researchers and the wider public is greater now than ever before, and so, consequently, are the opportunities to mine and extract value from existing open content and to generate new discoveries and other societal benefits. A key obstacle in realizing these benefits is the discoverability of open content, and the ability to access and utilize it.
The goal of this Prize is to stimulate the development of novel and ground-breaking tools and platforms to enable the reuse and repurposing of open digital research objects relevant to biomedical or health applications. A Prize model is necessary to help accelerate the field of open biomedical research beyond what current funding mechanisms can achieve. We also hope to demonstrate the huge potential value of Open Science approaches, and to generate excitement, momentum and further investment in the field….(More)”.
Global Standards in National Contexts: The Role of Transnational Multi-Stakeholder Initiatives in Public Sector Governance Reform
Paper by Brandon Brockmyer: “Multi-stakeholder initiatives (i.e., partnerships between governments, civil society, and the private sector) are an increasingly prevalent strategy promoted by multilateral, bilateral, and nongovernmental development organizations for addressing weaknesses in public sector governance. Global public sector governance MSIs seek to make national governments more transparent and accountable by setting shared standards for information disclosure and multi- stakeholder collaboration. However, research on similar interventions implemented at the national or subnational level suggests that the effectiveness of these initiatives is likely to be mediated by a variety of socio-political factors.
This dissertation examines the transnational evidence base for three global public sector governance MSIs — the Extractive Industries Transparency Initiative, the Construction Sector Transparency Initiative, and the Open Government Partnership — and investigates their implementation within and across three shared national contexts — Guatemala, the Philippines, and Tanzania — in order to determine whether and how these initiatives lead to improvements in proactive transparency (i.e., discretionary release of government data), demand-driven transparency (i.e., reforms that increase access to government information upon request), and accountability (i.e., the extent to which government officials are compelled to publicly explain their actions and/or face penalties or sanction for them), as well as the extent to which they provide participating governments with an opportunity to project a public image of transparency and accountability, while maintaining questionable practices in these areas (i.e., openwashing).
The evidence suggests that global public sector governance MSIs often facilitate gains in proactive transparency by national governments, but that improvements in demand-driven transparency and accountability remain relatively rare. Qualitative comparative analysis reveals that a combination of multi-stakeholder power sharing and civil society capacity is sufficient to drive improvements in proactive transparency, while the absence of visible, high-level political support is sufficient to impede such reforms. The lack of demand-driven transparency or accountability gains suggests that national-level coalitions forged by global MSIs are often too narrow to successfully advocate for broader improvements to public sector governance. Moreover, evidence for openwashing was found in one-third of cases, suggesting that national governments sometimes use global MSIs to deliberately mislead international observers and domestic stakeholders about their commitment to reform….(More)”
How Artificial Intelligence Will Usher in the Next Stage of E-Government
Daniel Castro at GovTech: “Since the earliest days of the Internet, most government agencies have eagerly explored how to use technology to better deliver services to citizens, businesses and other public-sector organizations. Early on, observers recognized that these efforts often varied widely in their implementation, and so researchers developed various frameworks to describe the different stages of growth and development of e-government. While each model is different, they all identify the same general progression from the informational, for example websites that make government facts available online, to the interactive, such as two-way communication between government officials and users, to the transactional, like applications that allow users to access government services completely online.
However, we will soon see a new stage of e-government: the perceptive.
The defining feature of the perceptive stage will be that the work involved in interacting with government will be significantly reduced and automated for all parties involved. This will come about principally from the integration of artificial intelligence (AI) — computer systems that can learn, reason and decide at levels similar to that of a human — into government services to make it more insightful and intelligent.
Consider the evolution of the Department of Motor Vehicles. The informational stage made it possible for users to find the hours for the local office; the interactive stage made it possible to ask the agency a question by email; and the transactional stage made it possible to renew a driver’s license online.
In the perceptive stage, the user will simply say, “Siri, I need a driver’s license,” and the individual’s virtual assistant will take over — collecting any additional information from the user, coordinating with the government’s system and scheduling any in-person meetings automatically. That’s right: AI might finally end your wait at the DMV.
In general, there are at least three ways that AI will impact government agencies. First, it will enable government workers to be more productive since the technology can be used to automate many tasks. …
Second, AI will create a faster, more responsive government. AI enables the creation of autonomous, intelligent agents — think online chatbots that answer citizens’ questions, real-time fraud detection systems that constantly monitor government expenditures and virtual legislative assistants that quickly synthesize feedback from citizens to lawmakers.
Third, AI will allow people to interact more naturally with digital government services…(More)”
Artificial Intelligence Could Help Colleges Better Plan What Courses They Should Offer
Jeffrey R. Young at EdSsurge: Big data could help community colleges better predict how industries are changing so they can tailor their IT courses and other programs. After all, if Amazon can forecast what consumers will buy and prestock items in their warehouses to meet the expected demand, why can’t colleges do the same thing when planning their curricula, using predictive analytics to make sure new degree or certificates programs are started just in time for expanding job opportunities?
That’s the argument made by Gordon Freedman, president of the nonprofit National Laboratory for Education Transformation. He’s part of a new center that will do just that, by building a data warehouse that brings together up-to-date information on what skills employers need and what colleges currently offer—and then applying artificial intelligence to attempt to predict when sectors or certain employment needs might be expanding.
He calls the approach “opportunity engineering,” and the center boasts some heavy-hitting players to assist in the efforts, including the University of Chicago, the San Diego Supercomputing Center and Argonne National Laboratory. It’s called the National Center for Opportunity Engineering & Analysis.
Ian Roark, vice president of workforce development at Pima Community College in Arizona, is among those eager for this kind of “opportunity engineering” to emerge.
He explains when colleges want to start new programs, they face a long haul—it takes time to develop a new curriculum, put it through an internal review, and then send it through an accreditor….
Other players are already trying to translate the job market into a giant data set to spot trends. LinkedIn sits on one of the biggest troves of data, with hundreds of millions of job profiles, and ambitions to create what it calls the “economic graph” of the economy. But not everyone is on LinkedIn, which attracts mainly those in white-collar jobs. And companies such as Burning Glass Technologies have scanned hundreds of thousands of job listings and attempt to provide real-time intelligence on what employers say they’re looking for. Those still don’t paint the full picture, Freedman argues, such as what jobs are forming at companies.
“We need better information from the employer, better information from the job seeker and better information from the college, and that’s what we’re going after,” Freedman says…(More)”.
Rethinking how we collect, share, and use development results data
Development Gateway: “The international development community spends a great deal of time, effort, and money gathering data on thousands of indicators embedded in various levels of Results Frameworks. These data comprise outputs (school enrollment, immunization figures), program outcomes (educational attainment, disease prevalence), and, in some cases, impacts (changes in key outcomes over time).
Ostensibly, we use results data to allocate resources to the places, partners, and programs most likely to achieve lasting success. But is this data good enough – and is it used well enough – to genuinely increase development impact in priority areas?
Experience suggests that decision-makers at all levels may often face inadequate, incorrect, late, or incomplete results data. At the same time, a figurative “Tower of Babel” of both project-level M&E and program-level outcome data can make it difficult for agencies and organizations to share and use data effectively. Further, potential users may not have the skills, resources, or enabling environment to meaningfully analyze and apply results data to decisions. With these challenges in mind, the development community needs to re-think its investments in results data, making sure that the right users are able to collect, share, and use this information to maximum effect.
Our Initiative
To this end, Development Gateway (DG), with the support of the Bill & Melinda Gates Foundation, aims to “diagnose” the results data ecosystem in three countries, identifying ways to improve data quality, sharing, and use in the health and agriculture sectors. Some of our important questions include:
- Quality: Who collects data and how? Is data quality adequate? Does the data meet actual needs? How much time does data collection demand? How can data collection, quality, and reporting be improved?
- Sharing: How can we compare results data from different donors, governments, and implementers? Is there demand for comparability? Should data be shared more freely? If so, how?
- Use: How is results data analyzed and used to inform actual policies and plans? Does (or can) access to results data improve decision-making? Do the right people have the right data? How else can (or should) we promote data use?…(More)”
Tech is moving beyond cities to focus on civic engagement in every U.S. county
Hollie Russon Gilman at TechCrunch: “While gridlock has taken hold in a paralyzed Washington, D.C. mayors across the country are taking a pragmatic approach to solving local problems and its time for tech to reach out to them….
The United States has 3,0007 counties. And all of them have an appetite to shift the momentum from the federal government to the communities where people live and work. This can’t just involve coastal cities or urban areas within states. Rather, after Trump’s election, now is the moment to redouble policy efforts in communities across the country from states to rural counties.
Cities from Chicago, Los Angeles, Boston, to New York have been leading the way to think about how to provide better services and engagement opportunities. They’ve been exciting places where rich networks of talent from academia to philanthropy have been helping foster ecosystems to catalyze new policy solutions….
There are a host of illustrative experiments occurring across communities that are leveraging policy innovation, data, and technology for more responsive and inclusive governance. The engagements that work focus on process to ensure that diverse stakeholders are a part of decision making….
Wisconsin:
In Eau Claire, Wisconsin a local organization called Clear Vision is teaming up with stakeholders on a poverty summit to reduce the number of people living poverty in income insecurity and build more resilient and inclusive communities. Citizen action groups will work on key issues they identify as part of the engagement process.
A key component of this poverty summit is to bring in traditionally marginalized communities into the process including low-income households, rural poor, youth and black and Hispanic communities. There is even a community-supported, nonprofit journalism site to support the local work in Eau Claire, Chippewa, and Dunn counties….
Oregon:
In Oregon, a “Kitchen Table” is enabling residents from across the state to contribute ideas, resources, and feedback to inform public policy. The Kitchen Table enables public officials to consult with representatives about key policy areas, crowdfund, and micro-lend for local startups and community businesses….
Another practice in Oregon is the Citizens Initiative Review, where a representative sampling of citizens convenes for deliberations over several days to discuss state ballot measures. After being established by the state’s bipartisan legislature in 2009, there have been six random representative samples of citizens for multi-day deliberations to draft voting guides written for the people, by their neighbors….
This requires tapping into existing networks and civic organizations, leveraging data, technology and policy innovations, and re-shifting our focus from federal policy towards building an infrastructure of governance that is durable through collective development and buy-in from people…(More)”
Introducing the Agricultural Open Data Package: BETA Version
PressRelease: “GODAN, Open Data for Development (OD4D) Network, Open Data Charter, and the Open Data Institute are pleased to announce the release of the Agricultural Open Data Package: BETA version. …The Agriculture Open Data Package (http://AgPack.info) has been designed to help governments get to impact with open data in the agriculture sector. This practical resource provides key policy areas, key data categories, examples datasets, relevant interoperability initiatives, and use cases that policymakers and other stakeholders in the agriculture sector or open data should focus on, in order to address food security challenges.
The Package is meant as a source of inspiration and an invitation to start a national open data for agriculture initiative.
In the Package we identify fourteen key categories of data and discuss the effort it will take for a government to make this data available in a meaningful way. …
The Package also highlights more than ten use cases (the number is growing) demonstrating how open data is being harnessed to address sustainable agriculture and food security around the world. Examples include:
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mapping water points to optimise scarce resource allocation in Burkina Faso
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surfacing daily price information on multiple food commodities across India
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benchmarking agricultural productivity in the Netherlands
Where relevant we also highlight applicable interoperability initiatives, such as open contracting, international aid transparency initiative (IATI), and global product classification (GPC) standards.
We recognise that the agriculture sector is diverse, with many contextual differences affecting scope of activities, priorities and capacities. In the full version of the Agricultural Open Data Package we discuss important implementation considerations such as inter-agency coordination and resourcing to develop an appropriate data infrastructure and a healthy data ‘ecosystem’ for agriculture….(More)”