Selected Readings on Data Portability


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.

Make good use of big data: A home for everyone


Paper by Khaled Moustafa in Cities: “The ongoing COVID-19 pandemic should teach us some lessons at health, environmental and human levels toward more fairness, human cohesion and environmental sustainability. At a health level, the pandemic raises the importance of housing for everyone particularly vulnerable and homeless people to protect them from the disease and against other similar airborne pandemics. Here, I propose to make good use of big data along with 3D construction printers to construct houses and solve some major and pressing housing needs worldwide. Big data can be used to determine how many people do need accommodation and 3D construction printers to build houses accordingly and swiftly. The combination of such facilities- big data and 3D printers- can help solve global housing crises more efficiently than traditional and unguided construction plans, particularly under environmental and major health crises where health and housing are tightly interrelated….(More)”.

Health Data Privacy under the GDPR: Big Data Challenges and Regulatory Responses


Book edited by Maria Tzanou: “The growth of data collecting goods and services, such as ehealth and mhealth apps, smart watches, mobile fitness and dieting apps, electronic skin and ingestible tech, combined with recent technological developments such as increased capacity of data storage, artificial intelligence and smart algorithms have spawned a big data revolution that has reshaped how we understand and approach health data. Recently the COVID-19 pandemic has foregrounded a variety of data privacy issues. The collection, storage, sharing and analysis of health- related data raises major legal and ethical questions relating to privacy, data protection, profiling, discrimination, surveillance, personal autonomy and dignity.

This book examines health privacy questions in light of the GDPR and the EU’s general data privacy legal framework. The GDPR is a complex and evolving body of law that aims to deal with several technological and societal health data privacy problems, while safeguarding public health interests and addressing its internal gaps and uncertainties. The book answers a diverse range of questions including: What role can the GDPR play in regulating health surveillance and big (health) data analytics? Can it catch up with the Internet age developments? Are the solutions to the challenges posed by big health data to be found in the law? Does the GDPR provide adequate tools and mechanisms to ensure public health objectives and the effective protection of privacy? How does the GDPR deal with data that concern children’s health and academic research?

By analysing a number of diverse questions concerning big health data under the GDPR from various different perspectives, this book will appeal to those interested in privacy, data protection, big data, health sciences, information technology, the GDPR, EU and human rights law….(More)”.

Tool for Surveillance or Spotlight on Inequality? Big Data and the Law


Paper by Rebecca A. Johnson and Tanina Rostain: “The rise of big data and machine learning is a polarizing force among those studying inequality and the law. Big data and tools like predictive modeling may amplify inequalities in the law, subjecting vulnerable individuals to enhanced surveillance. But these data and tools may also serve an opposite function, shining a spotlight on inequality and subjecting powerful institutions to enhanced oversight. We begin with a typology of the role of big data in inequality and the law. The typology asks questions—Which type of individual or institutional actor holds the data? What problem is the actor trying to use the data to solve?—that help situate the use of big data within existing scholarship on law and inequality. We then highlight the dual uses of big data and computational methods—data for surveillance and data as a spotlight—in three areas of law: rental housing, child welfare, and opioid prescribing. Our review highlights asymmetries where the lack of data infrastructure to measure basic facts about inequality within the law has impeded the spotlight function….(More)”.

Interventions to mitigate the racially discriminatory impacts of emerging tech including AI


Joint Civil Society Statement: “As widespread recent protests have highlighted, racial inequality remains an urgent and devastating issue around the world, and this is as true in the context of technology as it is everywhere else. In fact, it may be more so, as algorithmic technologies based on big data are deployed at previously unimaginable scale, reproducing the discriminatory systems that build and govern them.

The undersigned organizations welcome the publication of the report “Racial discrimination and emerging digital technologies: a human rights analysis,” by Special Rapporteur on contemporary forms of racism, racial discrimination, xenophobia and related intolerance, E. Tendayi Achiume, and wish to underscore the importance and timeliness of a number of the recommendations made therein:

  1. Technologies that have had or will have significant racially discriminatory impacts should be banned outright.
    While incremental regulatory approaches may be appropriate in some contexts, where a technology is demonstrably likely to cause racially discriminatory harm, it should not be deployed until that harm can be prevented. Moreover, certain technologies may always have disparate racial impacts, no matter how much their accuracy can be improved. In the present moment, racially discriminatory technologies include facial and affect recognition technology and so-called predictive analytics. We support Special Rapporteur Achiume’s call for mandatory human rights impact assessments as a prerequisite for the adoption of new technologies. We also believe that where such assessments reveal that a technology has a high likelihood of deleterious racially disparate impacts, states should prevent its use through a ban or moratorium. We join the Special Rapporteur in welcoming recent municipal bans, for example, on the use of facial recognition technology, and encourage national governments to adopt similar policies.  Correspondingly, we reiterate our support for states’ imposition of an immediate moratorium on the trade and use of privately developed surveillance tools until such time as states enact appropriate safeguards, and congratulate Special Rapporteur Achiume on joining that call.
  2. Gender mainstreaming and representation along racial, national and other intersecting identities requires radical improvement at all levels of the tech sector.
  3. Technologists cannot solve political, social, and economic problems without the input of domain experts and those personally impacted.
  4. Access to technology is as urgent an issue of racial discrimination as inequity in the design of technologies themselves.
  5. Representative and disaggregated data is a necessary, if not sufficient, condition for racial equity in emerging digital technologies, but it must be collected and managed equitably as well.
  6. States as well as corporations must provide remedies for racial discrimination, including reparations.… (More)”.

Social Research in Times of Big Data: The Challenges of New Data Worlds and the Need for a Sociology of Social Research


Paper by Rainer Diaz-Bone et al: “The phenomenon of big data does not only deeply affect current societies but also poses crucial challenges to social research. This article argues for moving towards a sociology of social research in order to characterize the new qualities of big data and its deficiencies. We draw on the neopragmatist approach of economics of convention (EC) as a conceptual basis for such a sociological perspective.

This framework suggests investigating processes of quantification in their interplay with orders of justifications and logics of evaluation. Methodological issues such as the question of the “quality of big data” must accordingly be discussed in their deep entanglement with epistemic values, institutional forms, and historical contexts and as necessarily implying political issues such as who controls and has access to data infrastructures. On this conceptual basis, the article uses the example of health to discuss the challenges of big data analysis for social research.

Phenomena such as the rise of new and massive privately owned data infrastructures, the economic valuation of huge amounts of connected data, or the movement of “quantified self” are presented as indications of a profound transformation compared to established forms of doing social research. Methodological and epistemological, but also institutional and political, strategies are presented to face the risk of being “outperformed” and “replaced” by big data analysis as they are already done in big US American and Chinese Internet enterprises. In conclusion, we argue that the sketched developments have important implications both for research practices and methods teaching in the era of big data…(More)”.

The European data market


European Commission: “It was the first European Data Market study (SMART 2013/0063) contracted by the European Commission in 2013 that made a first attempt to provide facts and figures on the size and trends of the EU data economy by developing a European data market monitoring tool.

The final report of the updated European Data Market (EDM) study (SMART 2016/0063) now presents in detail the results of the final round of measurement of the updated European Data Market Monitoring Tool contracted for the 2017-2020 period.

Designed along a modular structure, as a first pillar of the study, the European Data Market Monitoring Tool is built around a core set of quantitative indicators to provide a series of assessments of the emerging market of data at present, i.e. for the years 2018 through 2020, and with projections to 2025.

The key areas covered by the indicators measured in this report are:

  • The data professionals and the balance between demand and supply of data skills;
  • The data companies and their revenues;
  • The data user companies and their spending for data technologies;
  • The market of digital products and services (“Data market”);
  • The data economy and its impacts on the European economy.
  • Forecast scenarios of all the indicators, based on alternative market trajectories.

Additionally, as a second major work stream, the study also presents a series of descriptive stories providing a complementary view to the one offered by the Monitoring Tool (for example, “How Big Data is driving AI” or “The Secondary Use of Health Data and Data-driven Innovation in the European Healthcare Industry”), adding fresh, real-life information around the quantitative indicators. By focusing on specific issues and aspects of the data market, the stories offer an initial, indicative “catalogue” of good practices of what is happening in the data economy today in Europe and what is likely to affect the development of the EU data economy in the medium term.

Finally, as a third work stream of the study, a landscaping exercise on the EU data ecosystem was carried out together with some community building activities to bring stakeholders together from all segments of the data value chain. The map containing the results of the landscaping of the EU data economy as well as reports from the webinars organised by the study are available on the www.datalandscape.eu website….(More)”.

Social Distancing and Social Capital: Why U.S. Counties Respond Differently to Covid-19


NBER Paper by Wenzhi Ding et al: Since social distancing is the primary strategy for slowing the spread of many diseases, understanding why U.S. counties respond differently to COVID-19 is critical for designing effective public policies. Using daily data from about 45 million mobile phones to measure social distancing we examine how counties responded to both local COVID-19 cases and statewide shelter-in-place orders. We find that social distancing increases more in response to cases and official orders in counties where individuals historically (1) engaged less in community activities and (2) demonstrated greater willingness to incur individual costs to contribute to social objectives. Our work highlights the importance of these two features of social capital—community engagement and individual commitment to societal institutions—in formulating public health policies….(More)”

Are there laws of history?


Amanda Rees at AEON: “…If big data could enable us to turn big history into mathematics rather than narratives, would that make it easier to operationalise our past? Some scientists certainly think so.

In February 2010, Peter Turchin, an ecologist from the University of Connecticut, predicted that 2020 would see a sharp increase in political volatility for Western democracies. Turchin was responding critically to the optimistic speculations of scientific progress in the journal Nature: the United States, he said, was coming to the peak of another instability spike (regularly occurring every 50 years or so), while the world economy was reaching the point of a ‘Kondratiev wave’ dip, that is, a steep downturn in a growth-driven supercycle. Along with a number of ‘seemingly disparate’ social pointers, all indications were that serious problems were looming. In the decade since that prediction, the entrenched, often vicious, social, economic and political divisions that have increasingly characterised North American and European society, have made Turchin’s ‘quantitative historical analysis’ seem remarkably prophetic.

A couple of years earlier, in July 2008, Turchin had made a series of trenchant claims about the nature and future of history. Totting up in excess of ‘200 explanations’ proposed to account for the fall of the Roman empire, he was appalled that historians were unable to agree ‘which explanations are plausible and which should be rejected’. The situation, he maintained, was ‘as risible as if, in physics, phlogiston theory and thermodynamics coexisted on equal terms’. Why, Turchin wanted to know, were the efforts in medicine and environmental science to produce healthy bodies and ecologies not mirrored by interventions to create stable societies? Surely it was time ‘for history to become an analytical, and even a predictive, science’. Knowing that historians were themselves unlikely to adopt such analytical approaches to the past, he proposed a new discipline: ‘theoretical historical social science’ or ‘cliodynamics’ – the science of history.

Like C P Snow 60 years before him, Turchin wanted to challenge the boundary between the sciences and humanities – even as periodic attempts to apply the theories of natural science to human behaviour (sociobiology, for example) or to subject natural sciences to the methodological scrutiny of the social sciences (science wars, anyone?) have frequently resulted in hostile turf wars. So what are the prospects for Turchin’s efforts to create a more desirable future society by developing a science of history?…

In 2010, Cliodynamics, the flagship journal for this new discipline, appeared, with its very first article (by the American sociologist Randall Collins) focusing on modelling victory and defeat in battle in relation to material resources and organisational morale. In a move that paralleled Comte’s earlier argument regarding the successive stages of scientific complexity (from physics, through chemistry and biology, to sociology), Turchin passionately rejected the idea that complexity made human societies unsuitable for quantitative analysis, arguing that it was precisely that complexity which made mathematics essential. Weather predictions were once considered unreliable because of the sheer complexity of managing the necessary data. But improvements in technology (satellites, computers) mean that it’s now possible to describe mathematically, and therefore to model, interactions between the system’s various parts – and therefore to know when it’s wise to carry an umbrella. With equal force, Turchin insisted that the cliodynamic approach was not deterministic. It would not predict the future, but instead lay out for governments and political leaders the likely consequences of competing policy choices.

Crucially, and again on the back of the abundantly available and cheap computer power, cliodynamics benefited from the surge in interest in the digital humanities. Existing archives were being digitised, uploaded and made searchable: every day, it seemed, more data were being presented in a format that encouraged quantification and enabled mathematical analysis – including the Old Bailey’s online database, of which Wolf had fallen foul. At the same time, cliodynamicists were repositioning themselves. Four years after its initial launch, the subtitle of their flagship journal was renamed, from The Journal of Theoretical and Mathematical History to The Journal of Quantitative History and Cultural Evolution. As Turchin’s editorial stated, this move was intended to position cliodynamics within a broader evolutionary analysis; paraphrasing the Russian-American geneticist Theodosius Dobzhansky, he claimed that ‘nothing in human history makes sense except in the light of cultural evolution’. Given Turchin’s ecological background, this evolutionary approach to history is unsurprising. But given the historical outcomes of making politics biological, it is potentially worrying….

Mathematical, data-driven, quantitative models of human experience that aim at detachment, objectivity and the capacity to develop and test hypotheses need to be balanced by explicitly fictional, qualitative and imaginary efforts to create and project a lived future that enable their audiences to empathically ground themselves in the hopes and fears of what might be to come. Both, after all, are unequivocally doing the same thing: using history and historical experience to anticipate the global future so that we might – should we so wish – avoid civilisation’s collapse. That said, the question of who ‘we’ are does, always, remain open….(More)”.

‘For good measure’: data gaps in a big data world


Paper by Sarah Giest & Annemarie Samuels: “Policy and data scientists have paid ample attention to the amount of data being collected and the challenge for policymakers to use and utilize it. However, far less attention has been paid towards the quality and coverage of this data specifically pertaining to minority groups. The paper makes the argument that while there is seemingly more data to draw on for policymakers, the quality of the data in combination with potential known or unknown data gaps limits government’s ability to create inclusive policies. In this context, the paper defines primary, secondary, and unknown data gaps that cover scenarios of knowingly or unknowingly missing data and how that is potentially compensated through alternative measures.

Based on the review of the literature from various fields and a variety of examples highlighted throughout the paper, we conclude that the big data movement combined with more sophisticated methods in recent years has opened up new opportunities for government to use existing data in different ways as well as fill data gaps through innovative techniques. Focusing specifically on the representativeness of such data, however, shows that data gaps affect the economic opportunities, social mobility, and democratic participation of marginalized groups. The big data movement in policy may thus create new forms of inequality that are harder to detect and whose impact is more difficult to predict….(More)“.