We encourage partnerships between libraries and local data intermediaries that will better serve data users, further democratize data, and support equitable access to information. Our project is created an online guide and toolkit for libraries interested in expanding (or beginning) their role around civic information…(More)”.
Article by Takanori Fujita, Masayasu Okajima and Hiroyuki Miuchi: “The digital revolution in healthcare offers the promise of better health and longer lives for people around the world. New digital tools can help doctors and patients to predict, prevent and treat disease, opening the door to personalised medical care that is cost-efficient and highly effective.
Digitization across the entire healthcare sector — from hospital operations to the production of medical devices, vaccines and other pharmaceuticals — stands to benefit everyone, through improved efficiency at medical institutions, better care at home and stronger support for everyday health and wellbeing.
The essential ingredient in digital healthcare is data. Developers and service providers need health data to build and deploy effective solutions. So far, unfortunately, the potential benefits of digital healthcare have been under-realized, in large part because of data chokepoints…
It should go without saying that the ‘reward’ for sharing data is better health. Lifestyle-related diseases, which are more prevalent in ageing populations, often do not become symptomatic until they have progressed to a dangerous level. That makes timely monitoring and assessment crucial. In a world where people are living longer and longer— ‘100-year societies,’ as we say in Japan — data-enabled early detection is perhaps the best tool we have to stave off age-related health crises.
Abstract arguments, however, rarely convince people to consent to sharing personal data. Special efforts are needed to show specific, individual benefits and make people feel a tangible sense of control.
In Japan, the city of Arao is conducting an experiment to enable patients and their families to check information on electronic health records (EHRs) using their smartphones when they visit affiliated hospitals. Test results, prescribed medications and other information can be monitored. The system is expected to reduce costs for municipalities that are struggling to fund medical and nursing care for growing elderly populations. The money saved can be diverted to programs that help people live healthier lives, creating a virtuous cycle….Digital healthcare isn’t just a matter for patients and medical professionals. Lifestyle data with implications for health is broadly distributed, so the non-medical field needs to be involved as well. Takamatsu, another Japanese city, is attempting to address this difficult issue by building a common data collaboration infrastructure for the public and private sectors.
SOMPO Light Vortex, a subsidiary of SOMPO Holdings, a Japanese insurance and nursing care company, has created an app for Covid-19 vaccination certification and personal health records (PHRs) that is connected to Takamatsu’s municipal data infrastructure. Combining a range of data on health and lifestyle patterns in a trusted platform overseen by local government is expected to offer benefits in areas ranging from disaster prevention to wellbeing…(More)”.
Report by the OECD: “Data have become a key input into the production of many goods and services. But just how important? What is the value of data – their contribution to economic growth and well-being? This report discusses different approaches to data valuation, their advantages and shortcomings and their applicability in different contexts. It argues that the value of data depends to a large extent on the data governance framework determining how they can be created, shared and used. In addition, the report provides estimates of the value of data and data flows. Its focus is on the monetary valuation of data produced by private economic actors and their recording in economic statistics. Finally, the report puts forward a draft measurement agenda for the future…(More)”.
Report by Judah Axelrod, Karolina Ramos, and Rebecca Bullied: “Data are central to understanding the lived experiences of different people and communities and can serve as a powerful force for promoting racial equity. Although public data, including foundational sources for policymaking such as the US Census Bureau’s American Community Survey (ACS), offer accessible information on a range of topics, challenges of timeliness, granularity, representativeness, and degrees of disaggregation can limit those data’s utility for real-time analysis. Private data—data produced by private-sector organizations either through standard business or to market as an asset for purchase—can serve as a richer, more granular, and higher-frequency supplement or alternative to public data sources. This raises questions about how well private data assets can offer race-disaggregated insights that can inform policymaking.
In this report, we explore the current landscape of public-private data sharing partnerships that address topic areas where racial equity research faces data gaps: wealth and assets, financial well-being and income, and employment and job quality. We held 20 semistructured interviews with current producers and users of private-sector data and subject matter experts in the areas of data-sharing models and ethical data usage. Our findings are divided into five key themes:
Incentives and disincentives, benefits, and risks to public-private data sharing Agreements with prestigious public partners can bolster credibility for private firms and broaden their customer base, while public partners benefit from access to real-time, granular, rich data sources. But data sharing is often time and labor intensive, and firms can be concerned with conflicting business interests or diluting the value of proprietary data assets.
Availability of race-disaggregated data sources We found no examples in our interviews of race-disaggregated data sources related to our thematic focus areas that are available externally. However, there are promising methods for data imputation, linkage, and augmentation through internal surveys.
Data collaboratives in practice Most public-private data sharing agreements we learned about are between two parties and entail free or “freemium” access. However, we found promising examples of multilateral agreements that diversify the data-sharing landscape.
From data champions to data stewards We found many examples of informal data champions who bear responsibility for relationship-building and securing data partnerships. This role has yet to mature to an institutionalized data steward within private firms we interviewed, which can make data sharing a fickle process.
Considerations for ethical data usage Data privacy and transparency about how data are accessed and used are prominent concerns among prospective data users. Interviewees also stressed the importance of not privileging existing quantitative data above qualitative insights in cases where communities have offered long-standing feedback and narratives about their own experiences facing racial inequities, and that policymakers should not use a need to collect more data as an excuse for delaying policy action.
Our research yielded several recommendations for data producers and users that engage in data sharing, and for funders seeking to advance data-sharing efforts and promote racial equity…(More)”
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)”.
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.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)”.
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)“.
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)”.
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)”.
