Expert Group to Eurostat releases its report on the re-use of privately-held data for Official Statistics

Curated on Posted on by Stefaan Verhulst

Blog by Stefaan Verhulst: “…To inform its efforts, Eurostat set up an expert group in 2021 on ‘Facilitating the use of new data sources for official statistics’ to reflect on opportunities offered by the data revolution to enhance the reuse of private sector data for official statistics”.

Data reuse is a particularly important area for exploration, both because of the potential it offers and because it is not sufficiently covered by current policies. Data reuse occurs when data collected for one purpose is shared and reused for another, often with resulting social benefit. Currently, this process is limited by a fragmented or outdated policy and regulatory framework, and often quite legitimate concerns over ethical challenges represented by sharing (e.g., threats to individual privacy).

Nonetheless, despite such hurdles, a wide variety of evidence supports the idea that responsible data reuse can strengthen and supplement official statistics, and potentially lead to lasting and positive social impact.

Having reviewed and deliberated about these issues over several months, the expert group issued its report this week entitled “Empowering society by reusing privately held data for official statistics”. It seeks to develop recommendations and a framework for sustainable data reuse in the production of official statistics. It highlights regulatory gaps, fragmentation of practices, and a lack of clarity regarding businesses’ rights and obligations, and it draws attention to the ways in which current efforts to reuse data have often led to ad-hoc, one-off projects rather than systematic transformation.

The report considers a wide variety of evidence, including historical, policy, and academic research, as well as the theoretical literature… (More)”.

Read the Eurostat report at: https://ec.europa.eu/eurostat/cros/content/read-final-report_en

Parallel Worlds: Revealing the Inequity of Access to Urban Spaces in Mexico City Through Mobility Data

Curated on Posted on by Stefaan Verhulst

Paper by Emmanuel Letouzé et al: “The near-ubiquitous use of mobile devices generates mobility data that can paint pictures of urban behavior at unprecedented levels of granularity and complexity. In the current period of intense sociopolitical polarization, mobility data can help reveal which urban spaces serve to attenuate or accentuate socioeconomic divides. If urban spaces served to bridge class divides, people from different socioeconomic groups would be prone to mingle in areas further removed from their homes, creating opportunities for sharing experiences in the physical world. In an opposing scenario, people would remain among neighbors and peers, creating “local urban bubbles” that reflect and reinforce social inequities and their adverse effects on social mixity, cohesion, and trust. These questions are especially salient in cities with high levels of socioeconomic inequality, such as Mexico City.

Building on a joint research project between Data-Pop Alliance and Oxfam Mexico titled “Mundos Paralelos” [Parallel Worlds], this paper leverages privacy-preserving mobility data to unveil the unequal use and appropriation of urban spaces by the inhabitants of Mexico City. This joint research harnesses a year (2018–2019) of anonymized mobility data to perform mobility and behavioral analysis of specific groups at high spatial resolution. Its main findings suggest that Mexico City is a spatially fragmented, even segregated city: although distinct socioeconomic groups do meet in certain spaces, a pattern emerges where certain points of interest are exclusive to the high- and low-income groups analyzed in this paper. The results demonstrate that spatial inequality in Mexico City is marked by unequal access to government services and cultural sites, which translates into unequal experiences of urban life and biased access to the city. The paper concludes with a series of public policy recommendations to foster a more equitable and inclusive appropriation of public space…(More)”.

Public Health Struggles to Get Rid of Its Data Silos

Curated on Posted on by Stefaan Verhulst

Article by Carl Smith: “…In September 2019, before the first COVID-19 case was reported in the U.S., the Council of State and Territorial Epidemiologists (CSTE) published a report calling for a “public health data superhighway” capable of detecting health challenges and informing the response to them.

The technology to accomplish this already exists, CSTE noted. But even so, “public health departments struggle to take advantage of these advancements and continue to rely on sluggish, manual processes like paper records, phone calls, spreadsheets, and faxes requiring manual data entry.”

The limitations of this data ecosystem became a considerable liability when public health officials ran up against a virus that had never been seen before, working to both understand and control it at the same time. “There were mixed messages, and the pandemic made us look like our data was not adequate to the task,” says Gail C. Christopher, executive director of the National Collaborative for Health Equity.

This provided an opening for political or social actors to push anti-public health campaigns that continue to fuel public distrust of public health leaders, workers and guidelines. Reliable and timely data could help heal some of the harm that has been done, says Christopher.

“I think every health department has aspects of a complete data system,” says Brian Castrucci, president and CEO of the DeBeaumont Foundation, which funded the CSTE report. “But we need to articulate what a complete data system looks like — right now, we don’t even know what the destination is, so it’s hard to tell when we’re lost.”

A Data Modernization Movement

Data systems improvement is one of three major topics that recur in discussions about rebuilding public health, along with workforce expansion and regaining public trust, says Michael Fraser, executive director of the Association of State and Territorial Health Officials (ASTHO). “A major finding from all the conversations that we’ve had about COVID is that data systems need to be modernized.”

In recent years, there has been considerable effort by the public health community to find ways to move away from “silo-based” or disease-based surveillance between states and the federal government to an enterprise-wide system, says Fraser. “During COVID, a lot of states had a hard time sharing data, and there are many parts of this country where people go back and forth between multiple states on any given day — it’s not just the ability for states to share data with the federal government, but for states to share amongst themselves.”

The CDC’s Data Modernization Initiative, launched in 2020, is a $1.2 billion effort to address this challenge, envisioning resilient, connected systems that could “solve problems before they happen and reduce the harm caused by the problems that do happen.” The CSTE campaign “Data: Elemental to Health” is working to ensure sustained public funding for this work…(More)”.

Satellites zoom in on cities’ hottest neighborhoods to help combat the urban heat island effect

Curated on Posted on by Stefaan Verhulst

Article by Daniel P. Johnson: “Spend time in a city in summer and you can feel the urban heat rising from the pavement and radiating from buildings. Cities are generally hotter than surrounding rural areas, but even within cities, some residential neighborhoods get dangerously warmer than others just a few miles away.

Within these “micro-urban heat islands,” communities can experience heat wave conditions well before officials declare a heat emergency.

I use Earth-observing satellites and population data to map these hot spots, often on projects with NASA. Satellites like the Landsat program have become crucial for pinpointing urban risks so cities can prepare for and respond to extreme heat, a top weather-related killer.

Among the many things we’ve been able to track with increasingly detailed satellite data is that the hottest neighborhoods are typically low-income and often have predominantly Black or Hispanic residents….

With rising global temperatures increasing the likelihood of dangerous heat waves, cities need to know which neighborhoods are at high risk. Excessive heat can lead to dehydration, heat exhaustion, heat stroke and even death with prolonged exposure, and the most at-risk residents often lack financial resources to adapt.

Map of Chicago showing how heat deaths clustered in the urban core during the 1995 heat wave.
The July 1995 Chicago heat wave was blamed for over 739 deaths in a five-day period. Most victims were poor and elderly people who lacked air conditioning or feared opening windows because of crime. This figure shows the location of heat-related deaths clustered in areas of higher surface urban heat intensity.

Satellite instruments can identify communities vulnerable to extreme heat because they can measure and map the surface urban heat island in high detail.

For example, industrial and commercial zones are frequently among the hottest areas in cities. They typically have fewer trees to cool the air and more pavement and buildings to retain and radiate heat…(More)”

Forecasting hospital-level COVID-19 admissions using real-time mobility data

Curated on Posted on by Stefaan Verhulst

Paper by Brennan Klein et al: “For each of the COVID-19 pandemic waves, hospitals have had to plan for deploying surge capacity and resources to manage large but transient increases in COVID-19 admissions. While a lot of effort has gone into predicting regional trends in COVID-19 cases and hospitalizations, there are far fewer successful tools for creating accurate hospital-level forecasts. At the same time, anonymized phone-collected mobility data proved to correlate well with the number of cases for the first two waves of the pandemic (spring 2020, and fall-winter 2021). In this work, we show how mobility data could bolster hospital-specific COVID-19 admission forecasts for five hospitals in Massachusetts during the initial COVID-19 surge. The high predictive capability of the model was achieved by combining anonymized, aggregated mobile device data about users’ contact patterns, commuting volume, and mobility range with COVID hospitalizations and test-positivity data. We conclude that mobility-informed forecasting models can increase the lead-time of accurate predictions for individual hospitals, giving managers valuable time to strategize how best to allocate resources to manage forthcoming surges…(More)”.

Public Data Commons: A public-interest framework for B2G data sharing in the Data Act

Curated on Posted on by Stefaan Verhulst

Policy Brief by Alek Tarkowski & Francesco Vogelezang: “It is by now a truism that data is a crucial resource in the digital era. Yet today access to data and the capacity to make use of data and to benefit from it are unevenly distributed. A new understanding of data is needed, one that takes into account a society-wide data sharing and value creation. This will solve power asymmetries related to data ownership and the capacity to use it, and fill the public value gap with regard to data-driven growth and innovation.

Public institutions are also in a unique position to safeguard the rule of law, ensure democratic control and accountability, and drive the use of data to generate non-economic value.

The “data sharing for public good” narratives have been presented for over a decade, arguing that privately-owned big data should be used for the public interest. The idea of the commons has attracted the attention of policymakers interested in developing institutional responses that can advance public interest goals. The concept of the data commons offers a generative model of property that is well-aligned with the ambitions of the European data strategy. And by employing the idea of the data commons, the public debate can be shifted beyond an opposition between treating data as a commodity or protecting it as the object of fundamental rights.

The European Union is uniquely positioned to deliver a data governance framework that ensures Business-to-Government (B2G) data sharing in the public interest. The policy vision for such a framework has been presented in the European strategy for data, and specific recommendations for a robust B2G data sharing model have been made by the Commission’s high-level expert group.

There are three connected objectives that must be achieved through a B2G data sharing framework. Firstly, access to data and the capacity to make use of it needs to be ensured for a broader range of actors. Secondly, exclusive corporate control over data needs to be reduced. And thirdly, the information power of the state and its generative capacity should be strengthened.

Yet the current proposal for the Data Act fails to meet these goals, due to a narrow B2G data sharing mandate limited only to situations of public emergency and exceptional need.

This policy brief therefore presents a model for public interest B2G data sharing, aimed to complement the current proposal. This framework would also create a robust baseline for sectoral regulations, like the recently proposed Regulation on the European Health Data Space. The proposal includes the creation of the European Public Data Commons, a body that acts as a recipient and clearinghouse for the data made available…(More)”.

We can’t create shared value without data. Here’s why

Curated on Posted on by Stefaan Verhulst

Article by Kriss Deiglmeier: “In 2011, I was co-teaching a course on Corporate Social Innovation at the Stanford Graduate School of Business, when our syllabus nearly went astray. A paper appeared in Harvard Business Review (HBR), titled “Creating Shared Value,” by Michael E. Porter and Mark R. Kramer. The students’ excitement was palpable: This could transform capitalism, enabling Adam Smith’s “invisible hand” to bend the arc of history toward not just efficiency and profit, but toward social impact…

History shows that the promise of shared value hasn’t exactly been realized. In the past decade, most indexes of inequality, health, and climate change have gotten worse, not better. The gap in wealth equality has widened – the combined worth of the top 1% in the United States increased from 29% of all wealth in 2011 to 32.3% in 2021 and the bottom 50% increased their share from 0.4% to 2.6% of overall wealth; everyone in between saw their share of wealth decline. The federal minimum wage has remained stagnant at $7.25 per hour while the US dollar has seen a cumulative price increase of 27.81%…

That said, data is by no means the only – or even primary – obstacle to achieving shared value, but the role of data is a key aspect that needs to change. In a shared value construct, data is used primarily for profit and not the societal benefit at the speed and scale required.

Unfortunately, the technology transformation has resulted in an emerging data divide. While data strategies have benefited the commercial sector, the public sector and nonprofits lag in education, tools, resources, and talent to use data in finding and scaling solutions. The result is the disparity between the expanding use of data to create commercial value, and the comparatively weak use of data to solve social and environmental challenges…

Data is part of our future and is being used by corporations to drive success, as they should. Bringing data into the shared value framework is about ensuring that other entities and organizations also have the access and tools to harness data for solving social and environmental challenges as well….

Business has the opportunity to help solve the data divide through a shared value framework by bringing talent, product and resources to bear beyond corporate boundaries to help solve our social and environmental challenges. To succeed, it’s essential to re-envision the shared value framework to ensure data is at the core to collectively solve these challenges for everyone. This will require a strong commitment to collaboration between business, government and NGOs – and it will undoubtedly require a dedication to increasing data literacy at all levels of education….(More)”.

Facebook-owner Meta to share more political ad targeting data

Curated on Posted on by Stefaan Verhulst

Article by Elizabeth Culliford: “Facebook owner Meta Platforms Inc (FB.O) will share more data on targeting choices made by advertisers running political and social-issue ads in its public ad database, it said on Monday.

Meta said it would also include detailed targeting information for these individual ads in its “Facebook Open Research and Transparency” database used by academic researchers, in an expansion of a pilot launched last year.

“Instead of analyzing how an ad was delivered by Facebook, it’s really going and looking at an advertiser strategy for what they were trying to do,” said Jeff King, Meta’s vice president of business integrity, in a phone interview.

The social media giant has faced pressure in recent years to provide transparency around targeted advertising on its platforms, particularly around elections. In 2018, it launched a public ad library, though some researchers criticized it for glitches and a lack of detailed targeting data.Meta said the ad library will soon show a summary of targeting information for social issue, electoral or political ads run by a page….The company has run various programs with external researchers as part of its transparency efforts. Last year, it said a technical error meant flawed data had been provided to academics in its “Social Science One” project…(More)”.

Mobile phone data reveal the effects of violence on internal displacement in Afghanistan

Curated on Posted on by Stefaan Verhulst

Paper by Nearly 50 million people globally have been internally displaced due to conflict, persecution and human rights violations. However, the study of internally displaced persons—and the design of policies to assist them—is complicated by the fact that these people are often underrepresented in surveys and official statistics. We develop an approach to measure the impact of violence on internal displacement using anonymized high-frequency mobile phone data. We use this approach to quantify the short- and long-term impacts of violence on internal displacement in Afghanistan, a country that has experienced decades of conflict. Our results highlight how displacement depends on the nature of violence. High-casualty events, and violence involving the Islamic State, cause the most displacement. Provincial capitals act as magnets for people fleeing violence in outlying areas. Our work illustrates the potential for non-traditional data sources to facilitate research and policymaking in conflict settings….(More)”.

Building a Data Infrastructure for the Bioeconomy

Curated on Posted on by Stefaan Verhulst

Article by Gopal P. Sarma and Melissa Haendel: “While the development of vaccines for COVID-19 has been widely lauded, other successful components of the national response to the pandemic have not received as much attention. The National COVID Cohort Collaborative (N3C), for example, flew under the public’s radar, even though it aggregated crucial US public health data about the new disease through cross-institutional collaborations among government, private, and nonprofit health and research organizations. These data, which were made available to researchers via cutting-edge software tools, have helped in myriad ways: they led to identification of the clinical characteristics of acute COVID-19 for risk prediction, assisted in providing clinical care for immunocompromised adults, revealed how COVID infection affects children, and documented that vaccines appear to reduce the risk of developing long COVID.

N3C has created the largest national, publicly available patient-level dataset in US history. Through a unique public-private partnership, over 300 participating organizations quickly overcame privacy concerns and data silos to include 13 million patient records in the project. More than 3,000 participating scientists are now working to overcome the particular challenge faced in the United States—the lack of a national healthcare data infrastructure available in many other countries—to support public health and medical responses. N3C shows great promise for unraveling answers to questions related to COVID, but it could easily be expanded for many areas of public health, including pandemic preparedness and monitoring disease status across the population.

As public servants dedicated to improving public health and equity, we believe that to unite the nation’s fragmented public health system, the United States should establish a standing capacity to collect, harmonize, and sustain a wide range of data types and sources. The public health data collected by N3C would ultimately be but one component of a rich landscape of interoperable data systems that can guide public policy in an era of rapid environmental change, sophisticated biological threats, and an economy enabled by biotechnology. Such an effort will require new thinking about data collection, infrastructure, and regulation, but its benefits could be enormous—enabling policymakers to make decisions in an increasingly complex world. And as the interconnections between society, industry, and government continue to intensify, decisionmaking of all types and scales will be more efficient and responsive if it can rely on significantly expanded data collection and analysis capabilities…(More)”.