A report by SDSN TReNDS and DataReady Limited on behalf of Contracts4DataCollaboration: “Building upon issues discussed in the C4DC report, “Laying the Foundation for Effective Partnerships: An Examination of Data Sharing Agreements,” this brief examines the potential of sunset clauses or sunset provisions to be a legally binding, enforceable, and accountable way of ensuring COVID-19 related data sharing agreements are wound down responsibly at the end of the pandemic. The brief is divided into four substantive parts: Part I introduces sunset clauses as legislative tools, highlighting a number of examples of how they have been used in both COVID-19 related and other contexts; Part II discusses sunset provisions in the context of data sharing agreements and attempts to explain the complex interrelationship between data ownership, intellectual property, and sunset provisions; Part III identifies some key issues policymakers should consider when assessing the utility and viability of sunset provisions within their data sharing agreements and arrangements; and Part IV highlights the value of a memorandum of understanding (MoU) as a viable vehicle for sunset provisions in contexts where data sharing agreements are either non-existent or not regularly used….(More)“.(Contracts 4 Data Collaboration Framework).
The CARE Principles for Indigenous Data Governance
Paper by Stephanie Russo Carroll et al: “Concerns about secondary use of data and limited opportunities for benefit-sharing have focused attention on the tension that Indigenous communities feel between (1) protecting Indigenous rights and interests in Indigenous data (including traditional knowledges) and (2) supporting open data, machine learning, broad data sharing, and big data initiatives. The International Indigenous Data Sovereignty Interest Group (within the Research Data Alliance) is a network of nation-state based Indigenous data sovereignty networks and individuals that developed the ‘CARE Principles for Indigenous Data Governance’ (Collective Benefit, Authority to Control, Responsibility, and Ethics) in consultation with Indigenous Peoples, scholars, non-profit organizations, and governments. The CARE Principles are people– and purpose-oriented, reflecting the crucial role of data in advancing innovation, governance, and self-determination among Indigenous Peoples. The Principles complement the existing data-centric approach represented in the ‘FAIR Guiding Principles for scientific data management and stewardship’ (Findable, Accessible, Interoperable, Reusable). The CARE Principles build upon earlier work by the Te Mana Raraunga Maori Data Sovereignty Network, US Indigenous Data Sovereignty Network, Maiam nayri Wingara Aboriginal and Torres Strait Islander Data Sovereignty Collective, and numerous Indigenous Peoples, nations, and communities. The goal is that stewards and other users of Indigenous data will ‘Be FAIR and CARE.’ In this first formal publication of the CARE Principles, we articulate their rationale, describe their relation to the FAIR Principles, and present examples of their application….(More)” See also Selected Readings on Indigenous Data Sovereignty.
Trace Labs
Trace Labs is a nonprofit organization whose mission is to accelerate
the family reunification of missing persons while training members in
the trade craft of open source intelligence (OSINT)….We crowdsource open source intelligence through both the Trace Labs OSINT Search Party CTFs and Ongoing Operations with our global community. Our highly skilled intelligence analysts then triage the data collected to produce actionable intelligence reports on each missing persons subject. These intelligence reports allow the law enforcement agencies that we work with the ability to quickly see any new details required to reopen a cold case and/or take immediate action on a missing subject.(More)”
The Potential Role Of Open Data In Mitigating The COVID-19 Pandemic: Challenges And Opportunities
Essay by Sunyoung Pyo, Luigi Reggi and Erika G. Martin: “…There is one tool for the COVID-19 response that was not as robust in past pandemics: open data. For about 15 years, a “quiet open data revolution” has led to the widespread availability of governmental data that are publicly accessible, available in multiple formats, free of charge, and with unlimited use and distribution rights. The underlying logic of open data’s value is that diverse users including researchers, practitioners, journalists, application developers, entrepreneurs, and other stakeholders will synthesize the data in novel ways to develop new insights and applications. Specific products have included providing the public with information about their providers and health care facilities, spotlighting issues such as high variation in the cost of medical procedures between facilities, and integrating food safety inspection reports into Yelp to help the public make informed decisions about where to dine. It is believed that these activities will in turn empower health care consumers and improve population health.
Here, we describe several use cases whereby open data have already been used globally in the COVID-19 response. We highlight major challenges to using these data and provide recommendations on how to foster a robust open data ecosystem to ensure that open data can be leveraged in both this pandemic and future public health emergencies…(More)” See also Repository of Open Data for Covid19 (OECD/TheGovLab)
Open Infrastructure Map
“Open Infrastructure Map is a view of the world’s hidden infrastructure mapped in the OpenStreetMap database.
By and large, this data isn’t exposed on the main OSM map, so I built Open Infrastructure Map to visualise it…(More).”
Learning like a State: Statecraft in the Digital Age
Essay by Marion Fourcade and Jeff Gordon: “…Recent books have argued that we live in an age of “informational” or “surveillance” capitalism, a new form of market governance marked by the accumulation and assetization of information, and by the dominance of platforms as sites of value extraction. Over the last decade-plus, both actual and idealized governance have been transformed by a combination of neoliberal ideology, new technologies for tracking and ranking populations, and the normative model of the platform behemoths, which carry the banner of technological modernity. In concluding a review of Julie Cohen’s and Shoshana Zuboff’s books, Amy Kapcyznski asks how we might build public power sufficient to govern the new private power. Answering that question, we believe, requires an honest reckoning with how public power has been warped by the same ideological, technological, and legal forces that brought about informational capitalism.
In our contribution to the inaugural JLPE issue, we argue that governments and their agents are starting to conceive of their role differently than in previous techno-social moments. Our jumping-off point is the observation that what may first appear as mere shifts in the state’s use of technology—from the “open data” movement to the NSA’s massive surveillance operation—actually herald a deeper transformation in the nature of statecraft itself. By “statecraft,” we mean the state’s mode of learning about society and intervening in it. We contrast what we call the “dataist” state with its high modernist predecessor, as portrayed memorably by the anthropologist James C. Scott, and with neoliberal governmentality, described by, among others, Michel Foucault and Wendy Brown.
The high modernist state expanded the scope of sovereignty by imposing borders, taking censuses, and coercing those on the outskirts of society into legibility through broad categorical lenses. It deployed its power to support large public projects, such as the reorganization of urban infrastructure. As the ideological zeitgeist evolved toward neoliberalism in the 1970s, however, the priority shifted to shoring up markets, and the imperative of legibility trickled down to the individual level. The poor and working class were left to fend for their rights and benefits in the name of market fitness and responsibility, while large corporations and the wealthy benefited handsomely.
As a political rationality, dataism builds on both of these threads by pursuing a project of total measurement in a neoliberal fashion—that is, by allocating rights and benefits to citizens and organizations according to (questionable) estimates of moral desert, and by re-assembling a legible society from the bottom up. Weakened by decades of anti-government ideology and concomitantly eroded capacity, privatization, and symbolic degradation, Western states have determined to manage social problems as they bubble up into crises rather than affirmatively seeking to intervene in their causes. The dataist state sets its sights on an expanse of emergent opportunities and threats. Its focus is not on control or competition, but on “readiness.” Its object is neither the population nor a putative homo economicus, but (as Gilles Deleuze put it) “dividuals,” that is, discrete slices of people and things (e.g. hospital visits, police stops, commuting trips). Under dataism, a well-governed society is one where events (not persons) are aligned to the state’s models and predictions, no matter how disorderly in high modernist terms or how irrational in neoliberal terms….(More)”.
Third Wave of Open Data
Paper (and site) by Stefaan G. Verhulst, Andrew Young, Andrew J. Zahuranec, Susan Ariel Aaronson, Ania Calderon, and Matt Gee on “How To Accelerate the Re-Use of Data for Public Interest Purposes While Ensuring Data Rights and Community Flourishing”: “The paper begins with a description of earlier waves of open data. Emerging from freedom of information laws adopted over the last half century, the First Wave of Open Data brought about newfound transparency, albeit one only available on request to an audience largely composed of journalists, lawyers, and activists.
The Second Wave of Open Data, seeking to go beyond access to public records and inspired by the open source movement, called upon national governments to make their data open by default. Yet, this approach too had its limitations, leaving many data silos at the subnational level and in the private sector untouched..
The Third Wave of Open Data seeks to build on earlier successes and take into account lessons learned to help open data realize its transformative potential. Incorporating insights from various data experts, the paper describes the emergence of a Third Wave driven by the following goals:
- Publishing with Purpose by matching the supply of data with the demand for it, providing assets that match public interests;
- Fostering Partnerships and Data Collaboration by forging relationships with community-based organizations, NGOs, small businesses, local governments, and others who understand how data can be translated into meaningful real-world action;
- Advancing Open Data at the Subnational Level by providing resources to cities, municipalities, states, and provinces to address the lack of subnational information in many regions.
- Prioritizing Data Responsibility and Data Rights by understanding the risks of using (and not using) data to promote and preserve the public’s general welfare.
Riding the Wave
Achieving these goals will not be an easy task and will require investments and interventions across the data ecosystem. The paper highlights eight actions that decision and policy makers can take to foster more equitable, impactful benefits… (More) (PDF) “
Data to Go: The Value of Data Portability as a Means to Data Liquidity
Juliet McMurren and Stefaan G. Verhulst at Data & Policy: “If data is the “new oil,” why isn’t it flowing? For almost two decades, data management in fields such as government, healthcare, finance, and research has aspired to achieve a state of data liquidity, in which data can be reused where and when it is needed. For the most part, however, this aspiration remains unrealized. The majority of the world’s data continues to stagnate in silos, controlled by data holders and inaccessible to both its subjects and others who could use it to create or improve services, for research, or to solve pressing public problems.
Efforts to increase liquidity have focused on forms of voluntary institutional data sharing such as data pools or other forms of data collaboratives. Although useful, these arrangements can only advance liquidity so far. Because they vest responsibility and control over liquidity in the hands of data holders, their success depends on data holders’ willingness and ability to provide access to their data for the greater good. While that willingness exists in some fields, particularly medical research, a willingness to share data is much less likely where data holders are commercial competitors and data is the source of their competitive advantage. And even where willingness exists, the ability of data holders to share data safely, securely, and interoperably may not. Without a common set of secure, standardized, and interoperable tools and practices, the best that such bottom-up collaboration can achieve is a disconnected patchwork of initiatives, rather than the data liquidity proponents are seeking.
Data portability is one potential solution to this problem. As enacted in the EU General Data Protection Regulation (2018) and the California Consumer Privacy Act (2018), the right to data portability asserts that individuals have a right to obtain, copy, and reuse their personal data and transfer it between platforms or services. In so doing, it shifts control over data liquidity to data subjects, obliging data holders to release data whether or not it is in their commercial interests to do so. Proponents of data portability argue that, once data is unlocked and free to move between platforms, it can be combined and reused in novel ways and in contexts well beyond those in which it was originally collected, all while enabling greater individual control.
To date, however, arguments for the benefits of the right to data portability have typically failed to connect this rights-based approach with the larger goal of data liquidity and how portability might advance it. This failure to connect these principles and to demonstrate their collective benefits to data subjects, data holders, and society has real-world consequences. Without a clear view of what can be achieved, policymakers are unlikely to develop interventions and incentives to advance liquidity and portability, individuals will not exercise their rights to data portability, and industry will not experiment with use cases and develop the tools and standards needed to make portability and liquidity a reality.
Toward these ends, we have been exploring the current literature on data portability and liquidity, searching for lessons and insights into the benefits that can be unlocked when data liquidity is enabled through the right to data portability. Below we identify some of the greatest potential benefits for society, individuals, and data-holding organizations. These benefits are sometimes in conflict with one another, making the field a contentious one that demands further research on the trade-offs and empirical evidence of impact. In the final section, we also discuss some barriers and challenges to achieving greater data liquidity….(More)”.
Ethical issues of crowdsourcing in education
Paper by Katerina Zdravkova: “Crowdsourcing has become a fruitful solution for many activities, promoting the joined power of the masses. Although not formally recognised as an educational model, the first steps towards embracing crowdsourcing as a form of formal learning and teaching have recently emerged. Before taking a dramatic step forward, it should be estimated whether it is feasible, sustainable and socially responsible.
A nice initiative, which intends to set a groundwork for responsible research and innovation and actively implement crowdsourcing for language learning of all citizens regardless of their diversified social, educational, and linguistic backgrounds is enetCollect.
In order to achieve these goals, a sound framework that embraces the ethical and legal considerations should be established. The framework is intended for all the current and prospective creators of crowd-oriented educational systems. It incorporates the ethical issues affecting the three stakeholders: collaborative content creators, prospective users, as well as the institutions intending to implement the approach for educational purposes. The proposed framework offers a practical solution intending to overcome the revealed barriers, which might increase the risk of compromising its main educational goals. If carefully designed and implemented, crowdsourcing might become a very helpful, and at the same time, a very reliable educational model….(More)”.
Using Data and Respecting Users
“Three technical and legal approaches that create value from data and foster user trust” by Marshall Van Alstyne and Alisa Dagan Lenart: “Transaction data is like a friendship tie: both parties must respect the relationship and if one party exploits it the relationship sours. As data becomes increasingly valuable, firms must take care not to exploit their users or they will sour their ties. Ethical uses of data cover a spectrum: at one end, using patient data in healthcare to cure patients is little cause for concern. At the other end, selling data to third parties who exploit users is a serious cause for concern. Between these two extremes lies a vast gray area where firms need better ways to frame data risks and rewards in order to make better legal and ethical choices. This column provides a simple framework and threeways to respectfully improve data use….(More)”