Article by David Zendle & Heather Wardle: “Industry data sharing has the potential to revolutionise evidence on video gaming and mental health, as well as a host of other critical topics. However, collaborative data sharing agreements between academics and industry partners may also afford industry enormous power in steering the development of this evidence base. In this paper, we outline how nonfinancial conflicts of interest may emerge when industry share data with academics. We then go on to describe ways in which such conflicts may affect the quality of the evidence base. Finally, we suggest strategies for mitigating this impact and preserving research independence. We focus on the development of data infrastructure: technological, social, and educational architecture that facilitates unfettered and free access to the kinds of high-quality data that industry hold, but without industry involvement…(More)”.
Use of new data sources for measuring international migration
UNICE Report: “Migration and other forms of cross-border mobility are issues of high policy importance. Demands for statistics in these areas have further increased in light of the 2030 Agenda for Sustainable Development and the 2018 Global Compact for Safe, Orderly and Regular Migration. The statistical community continues to be challenged to capture international migration and cross-border mobility in a way that would meet the growing needs of users.
Measurement of migration and cross-border mobility relies on a variety of sources, such as population and housing censuses, household surveys and administrative records, with each of them having their own strengths and limitations. Integration of data from different sources is often seen as a way to enhance the richness of data and reduce coverage or accuracy problems. Yet, even this would often not capture all dimensions of migration and cross-border mobility.
New non-conventional data sources, such as data gathered from the use of mobile telephones, credit cards and social networks — generally known as big and social media data — could be useful for producing migration statistics when used in combination with conventional sources. Notwithstanding the challenges of accessibility, accuracy and access to these new sources, examples are emerging that highlight their potential.
In 2020 the Bureau of the Conference of European Statisticians (CES) set up a task force to review existing experience and plans for using new data sources for measuring international migration in national statistical offices and outside official statistics; analyse the material collected; and compile the examples into a reference tool.
This publication presents the results of the work of the task force, including various national experiences with big data and new data sources collected through two surveys among countries participating in the CES…(More)”.
ResearchDataGov
“ResearchDataGov.org is a product of the federal statistical agencies and units, created in response to the Foundations of Evidence-based Policymaking Act of 2018. The site is the single portal for discovery of restricted data in the federal statistical system. The agencies have provided detailed descriptions of each data asset. Users can search for data by topic, agency, and keywords. Questions related to the data should be directed to the owning agency, using the contact information on the page that describes the data. In late 2022, users will be able to apply for access to these data using a single-application process built into ResearchDataGov. ResearchDataGov.org is built by and hosted at ICPSR at the University of Michigan, under contract and guidance from the National Center for Science and Engineering Statistics within the National Science Foundation.
The data described in ResearchDataGov.org are owned by and accessed through the agencies and units of the federal statistical system. Data access is determined by the owning or distributing agency and is limited to specific physical or virtual data enclaves. Even though all data assets are listed in a single inventory, they are not necessarily available for use in the same location(s). Multiple data assets accessed in the same location may not be able to be used together due to disclosure risk and other requirements. Please note the access modality of the data in which you are interested and seek guidance from the owning agency about whether assets can be linked or otherwise used together…(More)”.
Data Solidarity
White Paper by Barbara Prainsack et al: “…The concept of solidarity, applied to data governance, offers an approach to address the issues raised above. Solidarity-based data governance (in short: data solidarity) seeks to increase collective control, oversight and ownership over digital data and resources. In today’s societies, digital technologies and practices are entrenched in every domain of practice. Even people who are not heavy users of digital technologies contribute to the benefits that emerge from digital data and practice. They do so when data about their bodies and behaviours are captured by public institutions and companies, and as members of societies that make available the technical, social and knowledge infrastructures necessary for the generation and analysis of digital data. In short, in digital societies, all people contribute to the benefits resulting from digital data and practice. Similarly, everyone bears risks – not only that their privacy will be infringed, but also that they or other people will be discriminated against, profiled, or otherwise harmed as a result of data analytics and other data practices in fields as diverse as policing, administration and insurance. Against this backdrop, approaches that seek to increase the control of individuals over the use of their data remain important, but they are not sufficient to address the issues emerging from political and economic constellations.
Data solidarity’s core premise is that the benefits and the risks of digital practices need to be borne by societies collectively. The structure of this White Paper is as follows: After sketching our understanding of data solidarity and what a governance framework based on it should entail (Section 2), we discuss how data solidarity is different from related concepts (Section 3). We then give an overview of manifestations of data solidarity in existing legal frameworks (Section 4). Following this, we elaborate on policy instruments that can realise the proposed solidarity-based data governance framework (Section 5). We then discuss other ways to enable and improve data solidarity (Section 6). We end by providing specific recommendations to policymakers and other actors (Section 7) and presenting a brief research agenda for the immediate and near future (Section 8)…(More)“.
Industry Data for Society Partnership
Press Release: “On Wednesday, a new Industry Data for Society Partnership (IDSP) was launched by GitHub, Hewlett Packard Enterprise (HPE), LinkedIn, Microsoft, Northumbrian Water Group, R2 Factory and UK Power Networks. The IDSP is a first-of-its-kind cross-industry partnership to help advance more open and accessible private-sector data for societal good. The founding members of the IDSP agree to provide greater access to their data, where appropriate, to help tackle some of the world’s most pressing challenges in areas such as sustainability and inclusive economic growth.
In the past few years, open data has played a critical role in enabling faster research and collaboration across industries and with the public sector. As we saw during COVID-19, pandemic data that was made more open enabled researchers to make faster progress and gave citizens more information to inform their day-to-day activities. The IDSP’s goal is to continue this model into new areas and help address other complex societal challenges. The IDSP will serve as a forum for the participating companies to foster collaboration, as well as a resource for other entities working on related issues.
IDSP members commit to the following:
- To open data or provide greater access to data, where appropriate, to help solve pressing societal problems in a usable, responsible and inclusive manner.
- To share knowledge and information for the effective use of open data and data collaboration for social benefit.
- To invest in skilling a broad class of professionals to use data effectively and responsibly for social impact.
- To protect individuals’ privacy in all these activities.
The IDSP will also bring in other organizations with expertise in societal issues. At launch, The GovLab’s Data Program based at New York University and the Open Data Institute will both be partnership Affiliates to provide guidance and expertise for partnership endeavors…(More)”.
Using private sector geospatial data to inform policy
OECD Report: “Over the last decade, a large variety of geospatial data sources, such as GPS trajectories, geotagged photos, and social media have become available for research and statistical applications. These new data sources are often generated, voluntarily or non-voluntarily, by private sector organisations and can provide highly granular and timely information to policymakers. Drawing on experiences of several OECD countries, this paper highlights the potential of combining traditional and unconventional data from both public and private sources, and makes the case for facilitating co-operation between data providers and organisations responsible for public policy. In addition, the paper provides a series of best practices on leveraging private data for the public good and identifies opportunities, challenges, and ways forward for public and private sector partnerships on data sharing….(More)”.
The potential of Facebook advertising data for understanding flows of people from Ukraine to the European Union
Paper by Umberto Minora et al: “This work contributes to the discussion on how innovative data can support a fast crisis response. We use operational data from Facebook to gain useful insights on where people fleeing Ukraine following the Russian invasion are likely to be displaced, focusing on the European Union. In this context, it is extremely important to anticipate where these people are moving so that local and national authorities can better manage challenges related to their reception and integration. By means of the audience estimates provided by Facebook advertising platform, we analyse the flows of people fleeing Ukraine towards the European Union. At the fifth week since the beginning of the war, our results indicate an increase in the number of Ukrainian stocks derived from Ukrainian-speaking Facebook user estimates in all the European Union (EU) countries, with Poland registering the highest percentage share (33%) of the overall increase, followed by Germany (17%), and Czechia (15%). We assess the reliability of prewar Facebook estimates by comparison with official statistics on the Ukrainian diaspora, finding a strong correlation between the two data sources (Pearson’s ?=0.9r=0.9, ?<0.0001p<0.0001). We then compare our results with data on refugees in EU countries bordering Ukraine reported by the UNHCR, and we observe a similarity in their trend. In conclusion, we show how Facebook advertising data could offer timely insights on international mobility during crises, supporting initiatives aimed at providing humanitarian assistance to the displaced people, as well as local and national authorities to better manage their reception and integration…(More)”.
Bridging Data Gaps Can Help Tackle the Climate Crisis
Article by Bo Li and Bert Kroese: “A famous physicist once said: “When you can measure what you are speaking about, and express it in numbers, you know something about it”.
Nearly 140 years later, this maxim remains true and is particularly poignant for policymakers tasked with addressing climate mitigation and adaptation.
That’s because they face major information gaps that impede their ability to understand the impact of policies—from measures to incentivize cuts in emissions, to regulations that reduce physical risks and boost resilience to climate shocks. And without comprehensive and internationally comparable data to monitor progress, it’s impossible to know what works, and where course corrections are needed.
This underscores the importance of the support of G20 leaders for a new Data Gaps Initiative to make official statistics more detailed, and timely. It calls for better data to understand climate change, together with indicators that cover income and wealth, financial innovation and inclusion, access to private and administrative data, and data sharing. In short, official statistics need to be broader, more detailed, and timely.
The sector where change is needed the most is energy, the largest contributor to greenhouse gas emissions, accounting for around three-quarters of the total.
Economies must expand their renewable energy sources and curb fossil fuel use, but while there’s been a gradual shift in that direction, the pace is still not sufficient. And not only is there a lack of policy ambition in many cases, there also is a lack of comprehensive and internationally comparable data to monitor progress.
To accelerate cuts to emissions, policymakers need detailed statistics to monitor the path of the energy transition and assist them in devising effective mitigation measures that can deliver the fastest and least disruptive pathway toward net zero emissions…(More)”.
Marine Data Sharing: Challenges, Technology Drivers and Quality Attributes
Paper by Keila Lima et al: “Many companies have been adopting data-driven applications in which products and services are centered around data analysis to approach new segments of the marketplace. Data ecosystems rise from data sharing among organizations premeditatedly. However, this migration to this new data sharing paradigm has not come that far in the marine domain. Nevertheless, better utilizing the ocean data might be crucial for humankind in the future, for food production, and minerals, to ensure the ocean’s health….We investigate the state-of-the-art regarding data sharing in the marine domain with a focus on aspects that impact the speed of establishing a data ecosystem for the ocean.…We conducted an exploratory case study based on focus groups and workshops to understand the sharing of data in this context. Results: We identified main challenges of current systems that need to be addressed with respect to data sharing. Additionally, aspects related to the establishment of a data ecosystem were elicited and analyzed in terms of benefits, conflicts, and solutions…(More)”.
Is Facebook’s advertising data accurate enough for use in social science research? Insights from a cross-national online survey
Paper by André Grow et al: “Social scientists increasingly use Facebook’s advertising platform for research, either in the form of conducting digital censuses of the general population, or for recruiting participants for survey research. Both approaches depend on the accuracy of the data that Facebook provides about its users, but little is known about how accurate these data are. We address this gap in a large-scale, cross-national online survey (N = 137,224), in which we compare self-reported and Facebook-classified demographic information (sex, age and region of residence). Our results suggest that Facebook’s advertising platform can be fruitfully used for conducing social science research if additional steps are taken to assess the accuracy of the characteristics under consideration…(More)”.