Demystifying the Role of Data Interoperability in the Access and Sharing Debate

Curated on Posted on by Stefaan Verhulst

Paper by Jörg Hoffmann and Begoña Gonzalez Otero: “In the current data access and sharing debate, data interoperability is widely proclaimed as being key for efficiently reaping the economic welfare enhancing effects of further data re-use. Although, we agree, we found that the current law and policy framework pertaining data interoperability was missing a groundworks analysis. Without a clear understanding of the notions of interoperability, the role of data standards and application programming interfaces (APIs) to achieve this ambition, and the IP and trade secrets protection potentially hindering it, any regulatory analysis within the data access discussion will be incomplete. Any attempt at untangling the role of data interoperability in the access and sharing regimes requires a thorough understanding of the underlying technology and a common understanding of the different notions of data interoperability.

The paper firstly explains the technical complexity of interoperability and its enablers, namely data standards and application programming interfaces. It elaborates on the reasons data interoperability counts with different levels and puts emphasis on the fact that data interoperability is indirectly tangled to the data access right. Since data interoperability may be part of the legal obligations correlating to the access right, the scope of interoperability is and has already been subject to courts’ interpretation. While this may give some manoeuvre for balanced decision-making, it may not guarantee the ambition of efficient re-usability of data. This is why data governance market regulation under a public law approach is becoming more favourable. Yet, and this is elaborated in a second step, the paper builds on the assumption that interoperability should not become another policy on its own. This is followed by a competition economics assessment, taking into account that data interoperability is always a matter of degree and a lack of data interoperability does not necessarily lead to a market foreclosure of competitors and to causing harm to consumer welfare. Additionally, parts of application programming interfaces (APIs) may be protected under IP rights and trade secrets, which might conflict with data access rights. Instead of further solving the conflicting regimes within the respective legal regimes of the exclusive rights the paper concludes by suggesting that (sector-specific) data governance solutions should deal with this issue and align the different interests implied. This may provide for better, practical and well-balanced solutions instead of impractical and dysfunctional exceptions and limitations within the IP and trade secrets regimes….(More)”.

Leveraging Telecom Data to Aid Humanitarian Efforts

Curated on Posted on by Stefaan Verhulst

Data Collaborative Case Study by Michelle Winowatan, Andrew J. Zahuranec, Andrew Young, and Stefaan Verhulst: “Following the 2015 earthquake in Nepal, Flowminder, a data analytics nonprofit, and NCell, a mobile operator in Nepal, formed a data collaborative. Using call detail records (CDR, a type of mobile operator data) provided by NCell, Flowminder estimated the number of people displaced by the earthquake and their location. The result of the analysis was provided to various humanitarian agencies responding to the crisis in Nepal to make humanitarian aid delivery more efficient and targeted.

Data Collaboratives Model: Based on our typology of data collaborative practice areas, the initiative follows the trusted intermediary model of data collaboration, specifically a third-party analytics approach. Third-party analytics projects involve trusted intermediaries — such as Flowminder — who access private-sector data, conduct targeted analysis, and share insights with public or civil sector partners without sharing the underlying data. This approach enables public interest uses of private-sector data while retaining strict access control. It brings outside data expertise that would likely not be available otherwise using direct bilateral collaboration between data holders and users….(More)”.

If data is 21st century oil, could foundations be the right owners?

Curated on Posted on by Stefaan Verhulst

Felix Oldenburg at Alliance: “What are the best investments for a foundation? This important question is one many foundation professionals are revisiting in light of low interest rates, high market volatility, and fears of deep economic trouble ahead. While stories of success certainly exist and are worth learning from, even the notorious lack of data cannot obscure the inconvenient truth that the idea of traditional endowments is in trouble.

I would argue that in order to unleash the potential of foundations, we should turn the question around, perhaps back on its feet: For which assets are foundations the best owners?

In the still dawning digital age, one fascinating answer may stare you right in the face as you read this. How much is your personal data worth? Your social media information, search and purchase history, they are the source of much of the market value of the fastest growing sector of our time. A rough estimate of market valuation of the major social platforms divided by their active users arrives at more than $1,000 USD per user, not differentiating by location or other factors. This sum is more than the median per capita wealth in about half the world’s countries. And if the trend continues, this value may continue to grow – and with it the big question of how to put one of the most valuable resource of our time to use for the good of all.

Acting as guardians of digital commons, data-endowed foundations could negotiate conditions for the commercial use of its assets, and invest the income to create equal digital opportunities, power 21st century education, and fight climate change.

Foundation ownership in the data sector may sound like a wild idea at first. Yet foundations and their predecessors have played the role of purpose-driven owners of critical assets and infrastructures throughout history. Monasteries (called ‘Stifte’ in German, the root of the German word for foundations) have protected knowledge and education in libraries, and secured health care in hospitals. Trusts have created affordable much of the social housing in the exploding cities of the 19th century. The German Marshall Plan created an endowment for economic recovery that is still in existence today.

The proposition is simple: Independent ownership for the good of all, beyond the commercial or national interests of individual corporations of governments, in perpetuity. Acting as guardians of digital commons, data-endowed foundations could negotiate conditions for the commercial use of its assets, and invest the income to create equal digital opportunities, power 21st century education, and fight climate change. An ideal model of ownership would also include a form of governance exercised by the users themselves through digital participation and elections. A foundation really only relies on one thing, a stable frame of rights in its legal home country. This is far from a trivial condition, but again history shows how many foundations have survived depressions, wars, and revolutions….(More)”

How to fix the GDPR’s frustration of global biomedical research

Curated on Posted on by Stefaan Verhulst

Jasper Bovenberg, David Peloquin, Barbara Bierer, Mark Barnes, and Bartha Maria Knoppers at Science: “Since the advent of the European Union (EU) General Data Protection Regulation (GDPR) in 2018, the biomedical research community has struggled to share data with colleagues and consortia outside the EU, as the GDPR limits international transfers of personal data. A July 2020 ruling of the Court of Justice of the European Union (CJEU) reinforced obstacles to sharing, and even data transfer to enable essential research into coronavirus disease 2019 (COVID-19) has been restricted in a recent Guidance of the European Data Protection Board (EDPB). We acknowledge the valid concerns that gave rise to the GDPR, but we are concerned that the GDPR’s limitations on data transfers will hamper science globally in general and biomedical science in particular (see the text box) (1)—even though one stated objective of the GDPR is that processing of personal data should serve humankind, and even though the GDPR explicitly acknowledges that the right to the protection of personal data is not absolute and must be considered in relation to its function in society and be balanced against other fundamental rights. We examine whether there is room under the GDPR for EU biomedical researchers to share data from the EU with the rest of the world to facilitate biomedical research. We then propose solutions for consideration by either the EU legislature, the EU Commission, or the EDPB in its planned Guidance on the processing of health data for scientific research. Finally, we urge the EDPB to revisit its recent Guidance on COVID-19 research….(More)“.

Essential Requirements for Establishing and Operating Data Trusts

Curated on Posted on by Stefaan Verhulst

Paper by P Alison Paprica et al: “Increasingly, the label “data trust” is being applied to repeatable mechanisms or approaches to sharing data in a timely, fair, safe and equitable way. However, there is a gap in terms of practical guidance about how to establish and operate a data trust.

In December 2019, the Canadian Institute for Health Information and the Vector Institute for Artificial Intelligence convened a working meeting of 19 people representing 15 Canadian organizations/initiatives involved in data sharing, most of which focus on public sector health data. The objective was to identify essential requirements for the establishment and operation of data trusts. Preliminary findings were presented during the meeting then refined as participants and co-authors identified relevant literature and contributed to this manuscript.

Twelve (12) minimum specification requirements (“min specs”) for data trusts were identified. The foundational min spec is that data trusts must meet all legal requirements, including legal authority to collect, hold or share data. In addition, there was agreement that data trusts must have (i) an accountable governing body which ensures the data trust advances its stated purpose and is transparent, (ii) comprehensive data management including responsible parties and clear processes for the collection, storage, access, disclosure and use of data, (iii) training and accountability requirements for all data users and (iv) ongoing public and stakeholder engagement.

Based on a review of the literature and advice from participants from 15 Canadian organizations/initiatives, practical guidance in the form of twelve min specs for data trusts were agreed on. Public engagement and continued exchange of insights and experience is recommended on this evolving topic…(More)”.

Private Sector Data for Humanitarian Response: Closing the Gaps

Curated on Posted on by Stefaan Verhulst

Jos Berens at Bloomberg New Economy Forum: “…Despite these and other examples, data sharing between the private sector and humanitarian agencies is still limited. Out of 281 contributing organizations on HDX, only a handful come from the private sector. 

So why don’t we see more use of private sector data in humanitarian response? One obvious set of challenges concerns privacy, data protection and ethics. Companies and their customers are often wary of data being used in ways not related to the original purpose of data collection. Such concerns are understandable, especially given the potential legal and reputational consequences of personal data breaches and leaks.

Figuring out how to use this type of sensitive data in an already volatile setting seems problematic, and it is — negotiations between public and private partners in the middle of a crisis often get hung up on a lack of mutual understanding. Data sharing partnerships negotiated during emergencies often fail to mature beyond the design phase. This dynamic creates a loop of inaction due to a lack of urgency in between crises, followed by slow and halfway efforts when action is needed most.

To ensure that private sector data is accessible in an emergency, humanitarian organizations and private sector companies need to work together to build partnerships before a crisis. They can do this by taking the following actions: 

  • Invest in relationships and build trust. Both humanitarian organizations and private sector organizations should designate focal points who can quickly identify potentially useful data during a humanitarian emergency. A data stewards network which identifies and connects data responsibility leaders across organizations, as proposed by the NYU Govlab, is a great example of how such relations could look. Efforts to build trust with the general public regarding private sector data use for humanitarian response should also be strengthened, primarily through transparency about the means and purpose of such collaborations. This is particularly important in the context of COVID-19, as noted in the UN Comprehensive Response to COVID-19 and the World Economic Forum’s ‘Great Reset’ initiative…(More)”.

Improving data access democratizes and diversifies science

Curated on Posted on by Stefaan Verhulst

Research article by Abhishek Nagaraj, Esther Shears, and Mathijs de Vaan: “Data access is critical to empirical research, but past work on open access is largely restricted to the life sciences and has not directly analyzed the impact of data access restrictions. We analyze the impact of improved data access on the quantity, quality, and diversity of scientific research. We focus on the effects of a shift in the accessibility of satellite imagery data from Landsat, a NASA program that provides valuable remote-sensing data. Our results suggest that improved access to scientific data can lead to a large increase in the quantity and quality of scientific research. Further, better data access disproportionately enables the entry of scientists with fewer resources, and it promotes diversity of scientific research….(More)”

Smart Rural: The Open Data Gap

Curated on Posted on by Stefaan Verhulst

Paper by Johanna Walker et al: “The smart city paradigm has underpinned a great deal of thevuse and production of open data for the benefit of policymakers and citizens. This paper posits that this further enhances the existing urban rural divide. It investigates the availability and use of rural open data along two parameters: pertaining to rural populations, and to key parts of the rural economy (agriculture, fisheries and forestry). It explores the relationship between key statistics of national / rural economies and rural open data; and the use and users of rural open data where it is available. It finds that although countries with more rural populations are not necessarily earlier in their Open Data Maturity journey, there is still a lack of institutionalisation of open data in rural areas; that there is an apparent gap between the importance of agriculture to a country’s GDP and the amount of agricultural data published openly; and lastly, that the smart
city paradigm cannot simply be transferred to the rural setting. It suggests instead the adoption of the emerging ‘smart region’ paradigm as that most likely to support the specific data needs of rural areas….(More)”.

Emerging models of data governance in the age of datafication

Curated on Posted on by Stefaan Verhulst

Paper by Marina Micheli et al: “The article examines four models of data governance emerging in the current platform society. While major attention is currently given to the dominant model of corporate platforms collecting and economically exploiting massive amounts of personal data, other actors, such as small businesses, public bodies and civic society, take also part in data governance. The article sheds light on four models emerging from the practices of these actors: data sharing pools, data cooperatives, public data trusts and personal data sovereignty. We propose a social science-informed conceptualisation of data governance. Drawing from the notion of data infrastructure we identify the models as a function of the stakeholders’ roles, their interrelationships, articulations of value, and governance principles. Addressing the politics of data, we considered the actors’ competitive struggles for governing data. This conceptualisation brings to the forefront the power relations and multifaceted economic and social interactions within data governance models emerging in an environment mainly dominated by corporate actors. These models highlight that civic society and public bodies are key actors for democratising data governance and redistributing value produced through data. Through the discussion of the models, their underpinning principles and limitations, the article wishes to inform future investigations of socio-technical imaginaries for the governance of data, particularly now that the policy debate around data governance is very active in Europe….(More)”.

Models and Modeling in the Sciences: A Philosophical Introduction

Curated on Posted on by Stefaan Verhulst

Book by Stephen M. Downes: “Biologists, climate scientists, and economists all rely on models to move their work forward. In this book, Stephen M. Downes explores the use of models in these and other fields to introduce readers to the various philosophical issues that arise in scientific modeling. Readers learn that paying attention to models plays a crucial role in appraising scientific work.　

This book first presents a wide range of models from a number of different scientific disciplines. After assembling some illustrative examples, Downes demonstrates how models shed light on many perennial issues in philosophy of science and in philosophy in general. Reviewing the range of views on how models represent their targets introduces readers to the key issues in debates on representation, not only in science but in the arts as well. Also, standard epistemological questions are cast in new and interesting ways when readers confront the question, “What makes for a good (or bad) model?”…(More)’.