Harnessing the Power of Open Data for Children and Families

Curated on Posted on by Stefaan Verhulst

Article by Kathryn L.S. Pettit and Rob Pitingolo: “Child advocacy organizations, such as members of the KIDS COUNT network, have proven the value of using data to advocate for policies and programs to improve the lives of children and families. These organizations use data to educate policymakers and the public about how children are faring in their communities. They understand the importance of high-quality information for policy and decisionmaking. And in the past decade, many state governments have embraced the open data movement. Their data portals promote government transparency and increase data access for a wide range of users inside and outside government.

At the request of the Annie E. Casey Foundation, which funds the KIDS COUNT network, the authors conducted research to explore how these state data efforts could bring greater benefits to local communities. Interviews with child advocates and open data providers confirmed the opportunity for child advocacy organizations and state governments to leverage open data to improve the lives of children and families. But accomplishing this goal will require new practices on both sides.

This brief first describes the current state of practice for child advocates using data and for state governments publishing open data. It then provides suggestions for what it would take from both sides to increase the use of open data to improve the lives of children and families. Child and family advocates will find five action steps in section 2. These steps encourage them to assess their data needs, build relationships with state data managers, and advocate for new data and preservation of existing data.
State agency staff will find five action steps in section 3. These steps describe how staff can engage diverse stakeholders, including agency staff beyond typical “data people” and data users outside government. Although this brief focuses on state-level institutions, local advocates an governments will find these lessons relevant. In fact, many of the lessons and best practices are based on pioneering efforts at the local level….(More)”.

Big data needs big governance: best practices from Brain-CODE, the Ontario Brain Institute’s neuroinformatics platform

Curated on Posted on by Stefaan Verhulst

Shannon C. Lefaivre et al in Frontiers of Genetics: “The Ontario Brain Institute (OBI) has begun to catalyze scientific discovery in the field of neuroscience through its large-scale informatics platform, known as Brain-CODE. The platform supports the capture, storage, federation, sharing and analysis of different data types across several brain disorders. Underlying the platform is a robust and scalable data governance structure which allows for the flexibility to advance scientific understanding, while protecting the privacy of research participants.

Recognizing the value of an open science approach to enabling discovery, the governance structure was designed not only to support collaborative research programs, but also to support open science by making all data open and accessible in the future. OBI’s rigorous approach to data sharing maintains the accessibility of research data for big discoveries without compromising privacy and security. Taking a Privacy by Design approach to both data sharing and development of the platform has allowed OBI to establish some best practices related to large scale data sharing within Canada. The aim of this report is to highlight these best practices and develop a key open resource which may be referenced during the development of similar open science initiatives….(More)”.

Evolving Measurement for an Evolving Economy: Thoughts on 21st Century US Economic Statistics

Curated on Posted on by Stefaan Verhulst

Ron S. Jarmin at the Journal of Economic Perspectives: “The system of federal economic statistics developed in the 20th century has served the country well, but the current methods for collecting and disseminating these data products are unsustainable. These statistics are heavily reliant on sample surveys. Recently, however, response rates for both household and business surveys have declined, increasing costs and threatening quality. Existing statistical measures, many developed decades ago, may also miss important aspects of our rapidly evolving economy; moreover, they may not be sufficiently accurate, timely, or granular to meet the increasingly complex needs of data users. Meanwhile, the rapid proliferation of online data and more powerful computation make privacy and confidentiality protections more challenging. There is broad agreement on the need to transform government statistical agencies from the 20th century survey-centric model to a 21st century model that blends structured survey data with administrative and unstructured alternative digital data sources. In this essay, I describe some work underway that hints at what 21st century official economic measurement will look like and offer some preliminary comments on what is needed to get there….(More)”.

Applying behavioral insights to improve postsecondary education outcomes

Curated on Posted on by Stefaan Verhulst

Brookings: “Policymakers under President Obama implemented behaviorally-informed policies to improve college access, completion, and affordability. Given the complexity of the college application process, many of these policies aimed to simplify college and financial aid application processes and reduce informational barriers that students face when evaluating college options. Katharine Meyer and Kelly Ochs Rosinger summarize empirical evidence on these policies and conclude that behaviorally-informed policies play an important role, especially as supplements to (rather than replacements for) broader structural changes. For example, recent changes in the FAFSA filing timeline provided students with more time to complete the form. But this large shift may be more effective in changing behavior when accompanied by informational campaigns and nudges that improve students’ understanding of the new system. Governments and colleges can leverage behavioral science to increase awareness of student support services if more structural policy changes occur to provide the services in the first place….(More)”.

The Stanford Open Policing Project

Curated on Posted on by Stefaan Verhulst

About: “On a typical day in the United States, police officers make more than 50,000 traffic stops. Our team is gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country. Our goal is to help researchers, journalists, and policymakers investigate and improve interactions between police and the public.

Currently, a comprehensive, national repository detailing interactions between police and the public doesn’t exist. That’s why the Stanford Open Policing Project is collecting and standardizing data on vehicle and pedestrian stops from law enforcement departments across the country — and we’re making that information freely available. We’ve already gathered 130 million records from 31 state police agencies and have begun collecting data on stops from law enforcement agencies in major cities, as well.

We, the Stanford Open Policing Project, are an interdisciplinary team of researchers and journalists at Stanford University. We are committed to combining the academic rigor of statistical analysis with the explanatory power of data journalism….(More)”.

Algorithmic fairness: A code-based primer for public-sector data scientists

Curated on Posted on by Stefaan Verhulst

Paper by Ken Steif and Sydney Goldstein: “As the number of government algorithms grow, so does the need to evaluate algorithmic fairness. This paper has three goals. First, we ground the notion of algorithmic fairness in the context of disparate impact, arguing that for an algorithm to be fair, its predictions must generalize across different protected groups. Next, two algorithmic use cases are presented with code examples for how to evaluate fairness. Finally, we promote the concept of an open source repository of government algorithmic “scorecards,” allowing stakeholders to compare across algorithms and use cases….(More)”.

Opening the Government of Canada The Federal Bureaucracy in the Digital Age

Curated on Posted on by Stefaan Verhulst

Book by Amanda Clarke: “In the digital age, governments face growing calls to become more open, collaborative, and networked. But can bureaucracies abandon their closed-by-design mindsets and operations and, more importantly, should they?

Opening the Government of Canada presents a compelling case for the importance of a more open model of governance in the digital age – but a model that continues to uphold traditional democratic principles at the heart of the Westminster system. Drawing on interviews with public officials and extensive analysis of government documents and social media accounts, Clarke details the untold story of the Canadian federal bureaucracy’s efforts to adapt to new digital pressures from the mid-2000s onward. This book argues that the bureaucracy’s tradition of closed government, fuelled by today’s antagonistic political communications culture, is at odds with evolving citizen expectations and new digital policy tools, including social media, crowdsourcing, and open data. Amanda Clarke also cautions that traditional democratic principles and practices essential to resilient governance must not be abandoned in the digital age, which may justify a more restrained opening of our governing institutions than is currently proposed by many academics and governments alike.

Striking a balance between reform and tradition, Opening the Government of Canada concludes with a series of pragmatic recommendations that lay out a roadmap for building a democratically robust, digital-era federal government….(More)”.

Using Data Sharing Agreements as Tools of Indigenous Data Governance: Current Uses and Future Options

Curated on Posted on by Stefaan Verhulst

Paper by Martinez, A. and Rainie, S. C.: “Indigenous communities and scholars have been influencing a shift in participation and inclusion in academic and agency research over the past two decades. As a response, Indigenous peoples are increasingly asking research questions and developing their own studies rooted in their cultural values. They use the study results to rebuild their communities and to protect their lands. This process of Indigenous-driven research has led to partnering with academic institutions, establishing research review boards, and entering into data sharing agreements to protect environmental data, community information, and local and traditional knowledges.

Data sharing agreements provide insight into how Indigenous nations are addressing the key areas of data collection, ownership, application, storage, and the potential for data reuse in the future. By understanding this mainstream data governance mechanism, how they have been applied, and how they have been used in the past, we aim to describe how Indigenous nations and communities negotiate data protection and control with researchers.

The project described here reviewed publicly available data sharing agreements that focus on research with Indigenous nations and communities in the United States. We utilized qualitative analysis methods to identify specific areas of focus in the data sharing agreements, whether or not traditional or cultural values were included in the language of the data sharing agreements, and how the agreements defined data. The results detail how Indigenous peoples currently use data sharing agreements and potential areas of expansion for language to include in data sharing agreements as Indigenous peoples address the research needs of their communities and the protection of community and cultural data….(More)”.

State Capability, Policymaking and the Fourth Industrial Revolution

Curated on Posted on by Stefaan Verhulst

Demos Helsinki: “The world as we know it is built on the structures of the industrial era – and these structures are falling apart. Yet the vision of a new, sustainable and fair post-industrial society remains unclear. This discussion paper is the result of a collaboration between a group of organisations interested in the implications of the rapid technological development to policymaking processes and knowledge systems that inform policy decisions.

In the discussion paper, we set out to explore what the main opportunities and concerns that accompany the Fourth Industrial Revolution for policymaking and knowledge systems are particularly in middle-income countries. Overall, middle-income countries are home to five billion of the world’s seven billion people and 73 per cent of the world’s poor people; they represent about one-third of the global Gross Domestic Product (GDP) and are major engines of global growth (World Bank 2018).

The paper is co-produced with Capability (Finland), Demos Helsinki (Finland), HELVETAS Swiss Intercooperation (Switzerland), Politics & Ideas (global), Southern Voice (global), UNESCO Montevideo (Uruguay) and Using Evidence (Canada).

The guiding questions for this paper are:

– What are the critical elements of the Fourth Industrial Revolution?

– What does the literature say about the impact of this revolution on societies and economies, and in particular on middle-income countries?

– What are the implications of the Fourth Industrial Revolution for the achievement of the Sustainable Development Goals (SDGs) in middle-income countries?

– What does the literature say about the challenges for governance and the ways knowledge can inform policy during the Fourth Industrial Revolution?…(More)”.

Full discussion paper:  “State Capability, Policymaking and the Fourth Industrial Revolution: Do Knowledge Systems Matter?”

…

The privacy threat posed by detailed census data

Curated on Posted on by Stefaan Verhulst

Gillian Tett at the Financial Times: “Wilbur Ross suffered the political equivalent of a small(ish) black eye last month: a federal judge blocked the US commerce secretary’s attempts to insert a question about citizenship into the 2020 census and accused him of committing “egregious” legal violations.

The Supreme Court has agreed to hear the administration’s appeal in April. But while this high-profile fight unfolds, there is a second, less noticed, census issue about data privacy emerging that could have big implications for businesses (and citizens). Last weekend John Abowd, the Census Bureau’s chief scientist, told an academic gathering that statisticians had uncovered shortcomings in the protection of personal data in past censuses. There is no public evidence that anyone has actually used these weaknesses to hack records, and Mr Abowd insisted that the bureau is using cutting-edge tools to fight back. But, if nothing else, this revelation shows the mounting problem around data privacy. Or, as Mr Abowd, noted: “These developments are sobering to everyone.” These flaws are “not just a challenge for statistical agencies or internet giants,” he added, but affect any institution engaged in internet commerce and “bioinformatics”, as well as commercial lenders and non-profit survey groups. Bluntly, this includes most companies and banks.

The crucial problem revolves around what is known as “re-identification” risk. When companies and government institutions amass sensitive information about individuals, they typically protect privacy in two ways: they hide the full data set from outside eyes or they release it in an “anonymous” manner, stripped of identifying details. The census bureau does both: it is required by law to publish detailed data and protect confidentiality. Since 1990, it has tried to resolve these contradictory mandates by using “household-level swapping” — moving some households from one geographic location to another to generate enough uncertainty to prevent re-identification. This used to work. But today there are so many commercially-available data sets and computers are so powerful that it is possible to re-identify “anonymous” data by combining data sets. …

Thankfully, statisticians think there is a solution. The Census Bureau now plans to use a technique known as “differential privacy” which would introduce “noise” into the public statistics, using complex algorithms. This technique is expected to create just enough statistical fog to protect personal confidentiality in published data — while also preserving information in an encrypted form that statisticians can later unscramble, as needed. Companies such as Google, Microsoft and Apple have already used variants of this technique for several years, seemingly successfully. However, nobody has employed this system on the scale that the Census Bureau needs — or in relation to such a high stakes event. And the idea has sparked some controversy because some statisticians fear that even “differential privacy” tools can be hacked — and others fret it makes data too “noisy” to be useful….(More)”.