Monitoring global digital gender inequality using the online populations of Facebook and Google

Curated on September 11, 2020September 11, 2020 by Stefaan Verhulst

Paper by Ridhi Kashyap, Masoomali Fatehkia, Reham Al Tamime, and Ingmar Weber: “Background: In recognition of the empowering potential of digital technologies, gender equality in internet access and digital skills is an important target in the United Nations (UN) Sustainable Development Goals (SDGs). Gender-disaggregated data on internet use are limited, particularly in less developed countries.

Objective: We leverage anonymous, aggregate data on the online populations of Google and Facebook users available from their advertising platforms to fill existing data gaps and measure global digital gender inequality.

Methods: We generate indicators of country-level gender gaps on Google and Facebook. Using these online indicators independently and in combination with offline development indicators, we build regression models to predict gender gaps in internet use and digital skills computed using available survey data from the International Telecommunications Union (ITU).

Results: We find that women are significantly underrepresented in the online populations of Google and Facebook in South Asia and sub-Saharan Africa. These platform-specific gender gaps are a strong predictor that women lack internet access and basic digital skills in these populations. Comparing platforms, we find Facebook gender gap indicators perform better than Google indicators at predicting ITU internet use and low-level digital-skill gender gaps. Models using these online indicators outperform those using only offline development indicators. The best performing models, however, are those that combine Facebook and Google online indicators with a country’s development indicators such as the Human Development Index….(More)”.

The economics of Business to Government data sharing

Curated on September 11, 2020September 11, 2020 by Stefaan Verhulst

Paper by Bertin Martens and Nestor Duch Brown: “Data and information are fundamental pieces for effective evidence-based policy making and provision of public services. In recent years, some private firms have been collecting large amounts of data, which, were they available to governments, could greatly improve their capacity to take better policy decisions and to increase social welfare. Business-to-Government (B2G) data sharing can result in substantial benefits for society. It can save costs to governments by allowing them to benefit from the use of data collected by businesses without having to collect the same data again. Moreover, it can support the production of new and innovative outputs based on the shared data by different users. Finally, the data available to government may give only an incomplete or even biased picture, while aggregating complementary datasets shared by different parties (including businesses) may result in improved policies with strong social welfare benefits.

The examples assembled by the High Level Expert Group on B2G data sharing show that most of the current B2G data transactions remain one-off experimental pilot projects that do not seem to be sustainable over time. Overall, the volume of B2G operations still seems to be relatively small and clearly sub-optimal from a social welfare perspective. The market does not seem to scale compared to the economic potential for welfare gains in society. There are likely to be significant potential economic benefits from additional B2G data sharing operations. These could be enabled by measures that would seek to improve their governance conditions to contribute to increase the overall number of transactions. To design such measures, it is important to understand the nature of the current barriers for B2G data sharing operations. In this paper, we focus on the more important barriers from an economic perspective: (a) monopolistic data markets, (b) high transaction costs and perceived risks in data sharing and (c) a lack of incentives for private firms to contribute to the production of public benefits. The following reflections are mainly conceptual, since there is currently little quantitative empirical evidence on the different aspects of B2G transactions.

Monopolistic data markets. Some firms -like big tech companies for instance- may be in a privileged position as the exclusive providers of the type of data that a public body seeks to access. This position enables the firms to charge a high price for the data beyond a reasonable rate of return on costs. While a monopolistic market is still a functioning market, the resulting price may lead to some governments not being able or willing to purchase the data and therefore may cause social welfare losses. Nonetheless, monopolistic pricing may still be justified from an innovation perspective: it strengthens incentives to invest in more and better data collection systems and thereby increases the supply of data in the long run. In some cases, the data seller may be in a position to price-discriminate between commercial buyers and a public body, charging a lower price to the latter since the data would not be used for commercial purposes.
High transaction costs and perceived risks. An important barrier for data sharing comes from the ex-ante costs related to finding a suitable data sharing partner, negotiating a contractual arrangement, re-formatting and cleaning the data, among others. Potentially interested public bodies may not be aware of available datasets or may not be in a position to handle them or understand their advantages and disadvantages. There may also be ex-post risks related to uncertainties in the quality and/or usefulness of the data, the technical implementation of the data sharing deal, ensuring compliance with the agreed conditions, the risk of data leaks to unauthorized third-parties and exposure of personal and confidential data.
Lack of incentives. Firms may be reluctant to share data with governments because it might have a negative impact on them. This could be due to suspicions that the data delivered might be used to implement market regulations and to enforce competition rules that could negatively affect firms’ profits. Moreover, if firms share data with government under preferential conditions, they may have difficulties justifying the foregone profit to shareholders, since the benefits generated by better policies or public services fuelled by the private data will occur to society as a whole and are often difficult to express in monetary terms. Finally, firms might be afraid of entering into a competitive disadvantage if they provide data to public bodies – perhaps under preferential conditions – and their competitors do not.

Several mechanisms could be designed to solve the barriers that may be holding back B2G data sharing initiatives. One would be to provide stronger incentives for the data supplier firm to engage in this type of transactions. These incentives can be direct, i.e., monetary, or indirect, i.e., reputational (e.g. as part of corporate social responsibility programmes). Another way would be to ascertain the data transfer by making the transaction mandatory, with a fair cost compensation. An intermediate way would be based on solutions that seek to facilitate voluntary B2G operations without mandating them, for example by reducing the transaction costs and perceived risks for the provider data supplier, e.g. by setting up trusted data intermediary platforms, or appropriate contractual provisions. A possible EU governance framework for B2G data sharing operations could cover these options….(More)”.

Bringing Structure and Design to Data Governance

Curated on September 9, 2020September 9, 2020 by Stefaan Verhulst

Report by John Wilbanks et al: “Before COVID-19 took over the world, the Governance team at Sage Bionetworks had started working on an analysis of data governance structures and systems to be published as a “green paper” in late 2020. Today we’re happy to publicly release that paper, Mechanisms to Govern Responsible Sharing of Open Data: A Progress Report.

In the paper, we provide a landscape analysis of models of governance for open data sharing based on our observations in the biomedical sciences. We offer an overview of those observations and show areas where we think this work can expand to supply further support for open data sharing outside the sciences.

The central argument of this paper is that the “right” system of governance is determined by first understanding the nature of the collaborative activities intended. These activities map to types of governance structures, which in turn can be built out of standardized parts — what we call governance design patterns. In this way, governance for data science can be easy to build, follow key laws and ethics regimes, and enable innovative models of collaboration. We provide an initial survey of structures and design patterns, as well as examples of how we leverage this approach to rapidly build out ethics-centered governance in biomedical research.

While there is no one-size-fits-all solution, we argue for learning from ongoing data science collaborations and building on from existing standards and tools. And in so doing, we argue for data governance as a discipline worthy of expertise, attention, standards, and innovation.

We chose to call this report a “green paper” in recognition of its maturity and coverage: it’s a snapshot of our data governance ecosystem in biomedical research, not the world of all data governance, and the entire field of data governance is in its infancy. We have licensed the paper under CC-BY 4.0 and published it in github via Manubot in hopes that the broader data governance community might fill in holes we left, correct mistakes we made, add references and toolkits and reference implementations, and generally treat this as a framework for talking about how we share data…(More)”.

The open source movement takes on climate data

Curated on September 9, 2020September 9, 2020 by Stefaan Verhulst

Article by Heather Clancy: “…many companies are moving to disclose “climate risk,” although far fewer are moving to actually minimize it. And as those tasked with preparing those reports can attest, the process of gathering the data for them is frustrating and complex, especially as the level of detail desired and required by investors becomes deeper.

That pain point was the inspiration for a new climate data project launched this week that will be spearheaded by the Linux Foundation, the nonprofit host organization for thousands of the most influential open source software and data initiatives in the world such as GitHub. The foundation is central to the evolution of the Linux software that runs in the back offices of most major financial services firms.

There are four powerful founding members for the new group, the LF Climate Finance Foundation (LFCF): Insurance and asset management company Allianz, cloud software giants Amazon and Microsoft, and data intelligence powerhouse S&P Global. The foundation’s “planning team” includes World Wide Fund for Nature (WWF), Ceres and the Sustainability Account Standards Board (SASB).

The group’s intention is to collaborate on an open source project called the OS-Climate platform, which will include economic and physical risk scenarios that investors, regulators, companies, financial analysts and others can use for their analysis.

The idea is to create a “public service utility” where certain types of climate data can be accessed easily, then combined with other, more proprietary information that someone might be using for risk analysis, according to Truman Semans, CEO of OS-Climate, who was instrumental in getting the effort off the ground. “There are a whole lot of initiatives out there that address pieces of the puzzle, but no unified platform to allow those to interoperate,” he told me. There are a whole lot of initiatives out there that address pieces of the puzzle, but no unified platform to allow those to interoperate.

Why does this matter? It helps to understand the history of open source software, which was once a thing that many powerful software companies, notably Microsoft, abhorred because they were worried about the financial hit on their intellectual property. Flash forward to today and the open source software movement, “staffed” by literally millions of software developers, is credited with accelerating the creation of common system-level elements so that companies can focus their own resources on solving problems directly related to their business.

In short, this budding effort could make the right data available more quickly, so that businesses — particularly financial institutions — can make better informed decisions.

Or, as Microsoft’s chief intellectual property counsel, Jennifer Yokoyama, observed in the announcement press release: “Addressing climate issues in a meaningful way requires people and organizations to have access to data to better understand the impact of their actions. Opening up and sharing our contribution of significant and relevant sustainability data through the LF Climate Finance Foundation will help advance the financial modeling and understanding of climate change impact — an important step in affecting political change. We’re excited to collaborate with the other founding members and hope additional organizations will join.”…(More)”

Prioritizing COVID-19 tests based on participatory surveillance and spatial scanning

Curated on September 9, 2020September 9, 2020 by Stefaan Verhulst

Paper by O.B Leal-Neto et al: “Participatory surveillance has shown promising results from its conception to its application in several public health events. The use of a collaborative information pathway provides a rapid way for the data collection on symptomatic individuals in the territory, to complement traditional health surveillance systems. In Brazil, this methodology has been used at the national level since 2014 during mass gatherings events since they have great importance for monitoring public health emergencies.

With the occurrence of the COVID-19 pandemic, and the limitation of the main non-pharmaceutical interventions for epidemic control – in this case, testing and social isolation – added to the challenge of existing underreporting of cases and delay of notifications, there is a demand on alternative sources of up to date information to complement the current system for disease surveillance. Several studies have demonstrated the benefits of participatory surveillance in coping with COVID-19, reinforcing the opportunity to modernize the way health surveillance has been carried out. Additionally, spatial scanning techniques have been used to understand syndromic scenarios, investigate outbreaks, and analyze epidemiological risk, constituting relevant tools for health management. While there are limitations in the quality of traditional health systems, the data generated by participatory surveillance reveals an interesting application combining traditional techniques to clarify epidemiological risks that demand urgency in decision-making. Moreover, with the limitations of testing available, the identification of priority areas for intervention is an important activity in the early response to public health emergencies. This study aimed to describe and analyze priority areas for COVID-19 testing combining data from participatory surveillance and traditional surveillance for respiratory syndromes….(More)”.

Selected Readings on Data Portability

Curated on September 3, 2020September 4, 2020 by Andrew Young

By Juliet McMurren, Andrew Young, and Stefaan G. Verhulst

As part of an ongoing effort to build a knowledge base for the field of improving governance through technology, The GovLab publishes a series of Selected Readings, which provide an annotated and curated collection of recommended works on themes such as open data, data collaboration, and civic technology.

In this edition, we explore selected literature on data portability.

To suggest additional readings on this or any other topic, please email info@thelivinglib.org. All our Selected Readings can be found here.

Context

Data today exists largely in silos, generating problems and inefficiencies for the individual, business and society at large. These include:

difficulty switching (data) between competitive service providers;
delays in sharing data for important societal research initiatives;
barriers for data innovators to reuse data that could generate insights to inform individuals’ decision making; and
inhibitions to scale data donation.

Data portability — the principle that individuals have a right to obtain, copy, and reuse their own personal data and to transfer it from one IT platform or service to another for their own purposes — is positioned as a solution to these problems. When fully implemented, it would make data liquid, giving individuals the ability to access their own data in a usable and transferable format, transfer it from one service provider to another, or donate data for research and enhanced data analysis by those working in the public interest.

Some companies, including Google, Apple, Twitter and Facebook, have sought to advance data portability through initiatives like the Data Transfer Project, an open source software project designed to facilitate data transmittals. Newly enacted data protection legislation such as Europe’s General Data Protection Regulation (2018) and the California Consumer Privacy Act (2018) give data holders a right to data portability. However, despite the legal and technical advances made, many questions toward scaling up data liquidity and portability responsibly and systematically remain. These new data rights have generated complex and as yet unanswered questions about the limits of data ownership, the implications for privacy, security and intellectual property rights, and the practicalities of how, when, and to whom data can be transferred.

In this edition of the GovLab’s Selected Readings series, we examine the emerging literature on data portability to provide a foundation for future work on the value proposition of data portability. Readings are listed in alphabetical order.

Selected readings

Cho, Daegon, Pedro Ferreira, and Rahul Telang, The Impact of Mobile Number Portability on Price and Consumer Welfare (2016)

In this paper, the authors analyze how Mobile Number Portability (MNP) — the ability for consumers to maintain their phone number when changing providers, thus reducing switching costs — affected the relationship between switching costs, market price and consumer surplus after it was introduced in most European countries in the early 2000s.
Theory holds that when switching costs are high, market leaders will enjoy a substantial advantage and are able to keep prices high. Policy makers will therefore attempt to decrease switching costs to intensify competition and reduce prices to consumers.
The study reviewed quarterly data from 47 wireless service providers in 15 EU countries between 1999 and 2006. The data showed that MNP simultaneously decreased market price by over four percent and increased consumer welfare by an average of at least €2.15 per person per quarter. This increase amounted to a total of €880 million per quarter across the 15 EU countries analyzed in this paper and accounted for 15 percent of the increase in consumer surplus observed over this time.

CtrlShift, Data Mobility: The data portability growth opportunity for the UK economy (2018)

Commissioned by the UK Department of Digital, Culture, Media and Sport (DCMS), this study was intended to identify the potential of personal data portability for the UK economy.
Its scope went beyond the legal right to data portability envisaged by the GDPR, to encompass the current state of personal data portability and mobility, requirements for safe and secure data sharing, and the potential economic benefits through stimulation of innovation, productivity and competition.
The report concludes that increased personal data mobility has the potential to be a vital stimulus for the development of the digital economy, driving growth by empowering individuals to make use of their own data and consent to others using it to create new data-driven services and technologies.
However, the report concludes that there are significant challenges to be overcome, and new risks to be addressed, before the value of personal data can be realized. Much personal data remains locked in organizational silos, and systemic issues related to data security and governance and the uneven sharing of benefits need to be resolved.

Data Guidance and Future of Privacy Forum, Comparing Privacy Laws: GDPR v. CCPA (2018)

This paper compares the provisions of the GDPR with those of the California Consumer Privacy Act (2018).
Both article 20 of the GDPR and section 1798 of the CCPA recognize a right to data portability. Both also confer on data subjects the right to receive data from controllers free of charge upon request, and oblige controllers to create mechanisms to provide subjects with their data in portable and reusable form so that it can be transmitted to third parties for reuse.
In the CCPA, the right to data portability is an extension of the right to access, and only confers on data subjects the right to apply for data collected within the past 12 months and have it delivered to them. The GDPR does not impose a time limit, and allows data to be transferred from one data controller to another, but limits the right to automatically collected personal data provided by the data subject themselves through consent or contract.

Data Transfer Project, Data Transfer Project Overview and Fundamentals (2018)

The paper presents an overview of the goals, principles, architecture, and system components of the Data Transfer Project. The intent of the DTP is to increase the number of services offering data portability and provide users with the ability to transfer data directly in and out of participating providers through systems that are easy and intuitive to use, private and secure, reciprocal between services, and focused on user data. The project, which is supported by Microsoft, Google, Twitter and Facebook, is an open-source initiative that encourages the participation of other providers to reduce the infrastructure burden on providers and users.
In addition to benefits to innovation, competition, and user choice, the authors point to benefits to security, through allowing users to backup, organize, or archive their data, recover from account hijacking, and retrieve their data from deprecated services.
The DTP’s remit was to test concepts and feasibility for the transfer of specific types of user data between online services using a system of adapters to transfer proprietary formats into canonical formats that can be used to transfer data while allowing providers to maintain control over the security of their service. While not resolving all formatting or support issues, this approach would allow substantial data portability and encourage ecosystem sustainability.

Deloitte, How to Flourish in an Uncertain Future: Open Banking(2017)

This report addresses the innovative and disruptive potential of open banking, in which data is shared between members of the banking ecosystem at the authorization of the customer, with the potential to increase competition and facilitate new products and services. In the resulting marketplace model, customers could use a single banking interface to access products from multiple players, from established banks to newcomers and fintechs.
The report’s authors identify significant threats to current banking models. Banks that failed to embrace open banking could be relegated to a secondary role as an infrastructure provider, while third parties — tech companies, fintech, and price comparison websites — take over the customer relationship.
The report identifies four overlapping operating models banks could adopt within an open banking model: full service providers, delivering proprietary products through their own interface with little or no third-party integration; utilities, which provide other players with infrastructure without customer-facing services; suppliers, which offer proprietary products through third-party interfaces; and interfaces,which provide distribution services through a marketplace interface. To retain market share, incumbents are likely to need to adopt a combination of these roles, offering their own products and services and those of third parties through their own and others’ interfaces.

Digital Competition Expert Panel Unlocking Digital Competition(2019)

This report captures the findings of the UK Digital Competition Expert Panel, which was tasked in 2018 with considering opportunities and challenges the digital economy might pose for competition and competition policy and to recommend any necessary changes. The panel focused on the impact of big players within the sector, appropriate responses to mergers or anticompetitive practices, and the impact on consumers.
The panel found that the digital economy is creating many benefits, but that digital markets are subject to tipping, in which emerging winners can scoop much of the market. This concentration can give rise to substantial costs, especially to consumers, and cannot be solved by competition alone. However, government policy and regulatory solutions have limitations, including the slowness of policy change, uneven enforcement and profound informational asymmetries between companies and government.
The panel proposed the creation of a digital markets unit that would be tasked with developing a code of competitive conduct, enabling greater personal data mobility and systems designed with open standards, and advancing access to non-personal data to reduce barriers to market entry.
The panel’s model of data mobility goes beyond data portability, which involves consumers being able to request and transfer their own data from one provider to another. Instead, the panel recommended empowering consumers to instigate transfers of data between a business and a third party in order to access price information, compare goods and services, or access tailored advice and recommendations. They point to open banking as an example of how this could function in practice.
It also proposed updating merger policy to make it more forward-looking to better protect consumers and innovation and preserve the competitiveness of the market. It recommended the creation of antitrust policy that would enable the implementation of interim measures to limit damage to competition while antitrust cases are in process.

Egan, Erin, Charting a Way Forward: Data Portability and Privacy(2019)

This white paper by Facebook’s VP and Chief Privacy Officer, Policy, represents an attempt to advance the conversation about the relationship between data portability, privacy, and data protection. The author sets out five key questions about data portability: what is it, whose and what data should be portable, how privacy should be protected in the context of portability, and where responsibility for data misuse or improper protection should lie.
The paper finds that definitions of data portability still remain imprecise, particularly with regard to the distinction between data portability and data transfer. In the interest of feasibility and a reasonable operational burden on providers, it proposes time limits on providers’ obligations to make observed data portable.
The paper concludes that there are strong arguments both for and against allowing users to port their social graph — the map of connections between that user and other users of the service — but that the key determinant should be a capacity to ensure the privacy of all users involved. Best-practice data portability protocols that would resolve current differences of approach as to what, how and by whom information should be made available would help promote broader portability, as would resolution of liability for misuse or data exposure.

Engels, Barbara, Data portability among online platforms (2016)

The article examines the effects on competition and innovation of data portability among online platforms such as search engines, online marketplaces, and social media, and how relations between users, data, and platform services change in an environment of data portability.
The paper finds that the benefits to competition and innovation of portability are greatest in two kinds of environments: first, where platforms offer complementary products and can realize synergistic benefits by sharing data; and secondly, where platforms offer substitute or rival products but the risk of anti-competitive behaviour is high, as for search engines.
It identifies privacy and security issues raised by data portability. Portability could, for example, allow an identity fraudster to misuse personal data across multiple platforms, compounding the harm they cause.
It also suggests that standards for data interoperability could act to reduce innovation in data technology, encouraging data controllers to continue to use outdated technologies in order to comply with inflexible, government-mandated standards.

Graef, Inge, Martin Husovec and Nadezhda Purtova, Data Portability and Data Control: Lessons for an Emerging Concept in EU Law (2018)

This paper situates the data portability right conferred by the GDPR within rights-based data protection law. The authors argue that the right to data portability should be seen as a new regulatory tool aimed at stimulating competition and innovation in data-driven markets.
The authors note the potential for conflicts between the right to data portability and the intellectual property rights of data holders, suggesting that the framers underestimated the potential impact of such conflicts on copyright, trade secrets and sui generis database law.
Given that the right to data portability is being replicated within consumer protection law and the regulation of non-personal data, the authors argue framers of these laws should consider the potential for conflict and the impact of such conflict on incentives to innovate.

Mohsen, Mona Omar and Hassan A. Aziz The Blue Button Project: Engaging Patients in Healthcare by a Click of a Button (2015)

This paper provides a literature review on the Blue Button initiative, an early data portability project which allows Americans to access, view or download their health records in a variety of formats.
Originally launched through the Department of Veterans’ Affairs in 2010, the Blue Button initiative had expanded to more than 500 organizations by 2014, when the Department of Health and Human Services launched the Blue Button Connector to facilitate both patient access and development of new tools.
The Blue Button has enabled the development of tools such as the Harvard-developed Growth-Tastic app, which allows parents to check their child’s growth by submitting their downloaded pediatric health data. Pharmacies across the US have also adopted the Blue Button to provide patients with access to their prescription history.

More than Data and Mission: Smart, Got Data? The Value of Energy Data to Customers (2016)

This report outlines the public value of the Green Button, a data protocol that provides customers with private and secure access to their energy use data collected by smart meters.
The authors outline how the use of the Green Button can help states meet their energy and climate goals by enabling them to structure renewables and other distributed energy resources (DER) such as energy efficiency, demand response, and solar photovoltaics. Access to granular, near real time data can encourage innovation among DER providers, facilitating the development of applications like “virtual energy audits” that identify efficiency opportunities, allowing customers to reduce costs through time-of-use pricing, and enabling the optimization of photovoltaic systems to meet peak demand.
Energy efficiency receives the greatest boost from initiatives like the Green Button, with studies showing energy savings of up to 18 percent when customers have access to their meter data. In addition to improving energy conservation, access to meter data could improve the efficiency of appliances by allowing devices to trigger sleep modes in response to data on usage or price. However, at the time of writing, problems with data portability and interoperability were preventing these benefits from being realized, at a cost of tens of millions of dollars.
The authors recommend that commissions require utilities to make usage data available to customers or authorized third parties in standardized formats as part of basic utility service, and tariff data to developers for use in smart appliances.

MyData, Understanding Data Operators (2020)

MyData is a global movement of data users, activists and developers with a common goal to empower individuals with their personal data to enable them and their communities to develop knowledge, make informed decisions and interact more consciously and efficiently.
This introductory paper presents the state of knowledge about data operators, trusted data intermediaries that provide infrastructure for human-centric personal data management and governance, including data sharing and transfer. The operator model allows data controllers to outsource issues of legal compliance with data portability requirements, while offering individual users a transparent and intuitive way to manage the data transfer process.
The paper examines use cases from 48 “proto-operators” from 15 countries who fulfil some of the functions of an operator, albeit at an early level of maturity. The paper finds that operators offer management of identity authentication, data transaction permissions, connections between services, value exchange, data model management, personal data transfer and storage, governance support, and logging and accountability. At the heart of these functions is the need for minimum standards of data interoperability.
The paper reviews governance frameworks from the general (legislative) to the specific (operators), and explores proto-operator business models. In keeping with an emerging field, business models are currently unclear and potentially unsustainable, and one of a number of areas, including interoperability requirements and governance frameworks, that must still be developed.

National Science and Technology Council Smart Disclosure and Consumer Decision Making: Report of the Task Force on Smart Disclosure (2013)

This report summarizes the work and findings of the 2011–2013 Task Force on Smart Disclosure: Information and Efficiency, an interagency body tasked with advancing smart disclosure, through which data is made more available and accessible to both consumers and innovators.
The Task Force recognized the capacity of smart disclosure to inform consumer choices, empower them through access to useful personal data, enable the creation of new tools, products and services, and promote efficiency and growth. It reviewed federal efforts to promote smart disclosure within sectors and in data types that crosscut sectors, such as location data, consumer feedback, enforcement and compliance data and unique identifiers. It also surveyed specific public-private partnerships on access to data, such as the Blue and Green Button and MyData initiatives in health, energy and education respectively.
The Task Force reviewed steps taken by the Federal Government to implement smart disclosure, including adoption of machine readable formats and standards for metadata, use of APIs, and making data available in an unstructured format rather than not releasing it at all. It also reviewed “choice engines” making use of the data to provide services to consumers across a range of sectors.
The Task Force recommended that smart disclosure should be a core component of efforts to institutionalize and operationalize open data practices, with agencies proactively identifying, tagging, and planning the release of candidate data. It also recommended that this be supported by a government-wide community of practice.

Nicholas, Gabriel Taking It With You: Platform Barriers to Entry and the Limits of Data Portability (2020)

This paper considers whether, as is often claimed, data portability offers a genuine solution to the lack of competition within the tech sector.
It concludes that current regulatory approaches to data portability, which focus on reducing switching costs through technical solutions such as one-off exports and API interoperability, are not sufficient to generate increased competition. This is because they fail to address other barriers to entry, including network effects, unique data access, and economies of scale.
The author proposes an alternative approach, which he terms collective portability, which would allow groups of users to coordinate the transfer of their data to a new platform. This model raises questions about how such collectives would make decisions regarding portability, but would enable new entrants to successfully target specific user groups and scale rapidly without having to reach users one by one.

OECD, Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across Societies (2019)

This background paper to a 2017 expert workshop on risks and benefits of data reuse considers data portability as one strategy within a data openness continuum that also includes open data, market-based B2B contractual agreements, and restricted data-sharing agreements within research and data for social good applications.
It considers four rationales offered for data portability. These include empowering individuals towards the “informational self-determination” aspired to by GDPR, increased competition within digital and other markets through reductions in information asymmetries between individuals and providers, switching costs, and barriers to market entry; and facilitating increased data flows.
The report highlights the need for both syntactic and semantic interoperability standards to ensure data can be reused across systems, both of which may be fostered by increased rights to data portability. Data intermediaries have an important role to play in the development of these standards, through initiatives like the Data Transfer Project, a collaboration which brought together Facebook, Google, Microsoft, and Twitter to create an open-source data portability platform.

Personal Data Protection Commission Singapore Response to Feedback on the Public Consultation on Proposed Data Portability and Data Innovation Provisions (2020)

The report summarizes the findings of the 2019 PDPC public consultation on proposals to introduce provisions on data portability and data innovation in Singapore’s Personal Data Protection Act.
The proposed provision would oblige organizations to transmit an individual’s data to another organization in a commonly used machine-readable format, upon the individual’s request. The obligation does not extend to data intermediaries or organizations that do not have a presence in Singapore, although data holders may choose to honor those requests.
The obligation would apply to electronic data that is either provided by the individual or generated by the individual’s activities in using the organization’s service or product, but not derived data created by the processing of other data by the data holder. Respondents were concerned that including derived data could harm organizations’ competitiveness.
Respondents were concerned about how to honour data portability requests where the data of third parties was involved, as in the case of a joint account holder, for example. The PDPC opted for a “balanced, reasonable, and pragmatic approach,” allowing data involving third parties to be ported where it was under the requesting individual’s control, was to be used for domestic and personal purposes, and related only to the organization’s product or service.

Quinn, Paul Is the GDPR and Its Right to Data Portability a Major Enabler of Citizen Science? (2018)

This article explores the potential of data portability to advance citizen science by enabling participants to port their personal data from one research project to another. Citizen science — the collection and contribution of large amounts of data by private individuals for scientific research — has grown rapidly in response to the development of new digital means to capture, store, organize, analyze and share data.
The GDPR right to data portability aids citizen science by requiring transfer of data in machine-readable format and allowing data subjects to request its transfer to another data controller. This requirement of interoperability does not amount to compatibility, however, and data thus transferred would probably still require cleaning to be usable, acting as a disincentive to reuse.
The GDPR’s limitation of transferability to personal data provided by the data subject excludes some forms of data that might possess significant scientific potential, such as secondary personal data derived from further processing or analysis.
The GDPR right to data portability also potentially limits citizen science by restricting the grounds for processing data to which the right applies to data obtained through a subject’s express consent or through the performance of a contract. This limitation excludes other forms of data processing described in the GDPR, such as data processing for preventive or occupational medicine, scientific research, or archiving for reasons of public or scientific interest. It is also not clear whether the GDPR compels data controllers to transfer data outside the European Union.

Wong, Janis and Tristan Henderson, How Portable is Portable? Exercising the GDPR’s Right to Data Portability (2018)

This paper presents the results of 230 real-world requests for data portability in order to assess how — and how well — the GDPR right to data portability is being implemented. The authors were interested in establishing the kinds of file formats that were returned in response to requests, and to identify practical difficulties encountered in making and interpreting requests, over a three month period beginning on the day the GDPR came into effect.
The findings revealed continuing problems around ensuring portability for both data controllers and data subjects. Of the 230 requests, only 163 were successfully completed.
Data controllers frequently had difficulty understanding the requirements of GDPR, providing data in incomplete or inappropriate formats: only 40 percent of the files supplied were in a fully compliant format. Additionally, some data controllers were confused between the right to data portability and other rights conferred by the GDPR, such as the right to access or erasure.

Business-to-Business Data Sharing: An Economic and Legal Analysis

Curated on September 2, 2020September 2, 2020 by Stefaan Verhulst

Paper by Bertin Martens et al: “The European Commission announced in its Data Strategy (2020) its intentions to propose an enabling legislative framework for the governance of common European data spaces, to review and operationalize data portability, to prioritize standardization activities and foster data interoperability and to clarify usage rights for co-generated IoT data. This Strategy starts from the premise that there is not enough data sharing and that much data remain locked up and are not available for innovative re-use. The Commission will also consider the adoption of a New Competition Tool as well as the adoption of ex ante regulation for large online gate-keeping platforms as part of the announced Digital Services Act Package . In this context, the goal of this report is to examine the obstacles to Business-to-Business (B2B) data sharing: what keeps businesses from sharing or trading more of their data with other businesses and what can be done about it? For this purpose, this report uses the well-known tools of legal and economic thinking about market failures. It starts from the economic characteristics of data and explores to what extent private B2B data markets result in a socially optimal degree of data sharing, or whether there are market failures in data markets that might justify public policy intervention.

It examines the conditions under which monopolistic data market failures may occur. It contrasts these welfare losses with the welfare gains from economies of scope in data aggregation in large pools. It also discusses other potential sources of B2B data market failures due to negative externalities, risks and transaction costs and asymmetric information situations. In a next step, the paper explores solutions to overcome these market failures. Private third-party data intermediaries may be in a position to overcome market failures due to high transactions costs and risks. They can aggregate data in large pools to harvest the benefits of economies of scale and scope in data. Where third-party intervention fails, regulators can step in, with ex-post competition instruments and with ex-ante regulation. The latter includes data portability rights for personal data and mandatory data access rights….(More)”.

How Integrated Data Can Support COVID-19 Crisis and Recovery

Curated on September 1, 2020September 1, 2020 by Stefaan Verhulst

Blog by Actionable Intelligence for Social Policy (AISP): “…State and local leaders are called upon to respond to the immediate harms of COVID-19. Yet with a looming recession threatening to undo gains among marginalized groups — particularly the Black middle class — tools to understand and disrupt long-term impacts on economic mobility and well-being are also urgently needed.

Administrative data[3] — the information collected during the course of routine service delivery, program administration, and business operations — provide an essential tool to help policymakers, community leaders, and researchers understand short- and long-term impacts of the pandemic. Several jurisdictions now have the capacity to link administrative data across programs in order to better understand how individuals interact with multiple systems, study longitudinal outcomes, and identify vulnerable subpopulations. As the COVID-19 crisis reveals weaknesses in the U.S. social safety net, states and localities with integrated administrative data infrastructure can use their capacity to identify populations and needs otherwise overlooked. Youth who “age out” of the child welfare system or individuals experiencing chronic homelessness often remain invisible when using traditional methods, aggregate data, or administrative records from a single source.

This blogpost demonstrates how nimble state and local data integration efforts have leveraged their capacity to quickly respond to and understand the impacts of COVID-19, while also reflecting on what can be done to mitigate harm and shift thinking about social welfare and the safety net….(More)”.

Applying new models of data stewardship to health and care data

Curated on August 31, 2020September 2, 2020 by Stefaan Verhulst

Report by the Open Data Institute: “The outbreak of the coronavirus (Covid-19) has amplified and accelerated the need for an effective technology ecosystem that benefits everyone’s health. This report explores models of ‘data stewardship’ (the collection, maintenance and sharing of data) required to enable better evaluation

The pandemic has been accompanied by a marked increase in the use of digital technology, including introduction of remote consultation in general practice, new data flows to support the distribution of food and other essentials, and applications to support digital contact tracing.

This report explores models of ‘data stewardship’ (the collection, maintenance and sharing of data) required to enable better evaluation. It argues everybody involved in technology has a shared responsibility to enable evaluation, whether that means innovators sharing data for evaluation purposes, or healthcare providers being clearer, from the outset, about what data is needed to support effective evaluation.

This report re-envisages the role of evaluators as data stewards, who could use their positions as intermediaries to encourage stakeholders to share data, and help increase access to data for public benefit…(More)”.

Internet Searches for Acute Anxiety During the Early Stages of the COVID-19 Pandemic

Curated on August 25, 2020August 25, 2020 by Stefaan Verhulst

Paper by John W. Ayers et al: “There is widespread concern that the coronavirus disease 2019 (COVID-19) pandemic may harm population mental health, chiefly owing to anxiety about the disease and its societal fallout. But traditional population mental health surveillance (eg, telephone surveys, medical records) is time consuming, expensive, and may miss persons who do not participate or seek care. To evaluate the association of COVID-19 with anxiety on a population basis, we examined internet searches indicative of acute anxiety during the early stages of the COVID-19 pandemic.Methods

The analysis relied on nonidentifiable, aggregate, public data and was exempted by the University of California San Diego Human Research Protections Program. Acute anxiety, including colloquially called anxiety attacks or panic attacks, was monitored because of its higher prevalence relative to other mental health problems. It can lead to other mental health problems (including depression), it is triggered by outside stressors, and it is socially contagious. Using Google Trends (https://trends.google.com/trends) we monitored the daily fraction of all internet searches (thereby adjusting the results for any change in total queries) that included the terms anxiety or panic in combination with attack (including panic attack, signs of anxiety attack, anxiety attack symptoms) that originated from the US from January 1, 2004, through May 4, 2020. Raw search counts were inferred using Comscore estimates (comscore.com).

We compared search volumes after President Trump declared a national COVID-19 emergency on March 13, 2020, with expected search volumes if COVID-19 had not occurred, thereby taking into account the historical trend and periodicity in the data. Expected volumes were computed using an autoregressive integrated moving average model,⁴ based on historical trends from January 1, 2004 to March 12, 2020, to predict counterfactual trends for March 13, 2020 to May 9, 2020. The expected volumes with prediction intervals (PIs) and ratio of observed and expected volumes with bootstrap CIs were computed using R statistical software (version 3.5.3, R Foundation). The results were similar if we varied our interruption date plus or minus 1 week….(More)”.