Data Networks: Towards Realizing the Extraordinariness of Data as a Resource

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‘You can’t have your cake and eat it too’ is an expression we are all too familiar with. This makes cake a “rival” good in the language of economics, meaning the use of the good by someone precludes someone else from using it as well. Data on the other hand is a “nonrival” good, which means that it can be used simultaneously by many, making it an extraordinary resource. 

As a driver of innovation, data can generate broad societal benefits and increase well-being. Three days after WHO announced the discovery of the new COVID-19 virus, the full sequence of its genome, as detected in samples from the first known patients, was already being shared. Access to this data enabled the development of diagnostic tests and treatment options, which ultimately led to a vaccine. 

Data has potential to improve humanitarian efforts and safe lives. Mobility patterns and socioeconomic indicators extracted from mobile data can help monitor the effectiveness of lockdown measures, understand how the pandemic is spreading, and optimize supply aid. 

Data powers economic growth. The Human Genome Project, a massive open data project, generated $796 billion in economic impact and created 310,000 jobs with a $3.8 billion investment for example. 

Today however, we are not using data to its full potential. Much of it resides inside the private sector. Companies may be looking to maximize the economic and innovative potential of their data, they may fear creative destruction, they may lack the technical, legal, or organizational means to increase data access, they may fear potential repercussions from broadening access to data, or they may simply lack the (economic) incentives to invest in data access and sharing; whatever the reasons may be, much data remains inaccessible.

There is wariness about increased data access and sharing. Data can be used to undermine liberty, autonomy, and privacy. In response we have seen new laws and regulations including the EU General Data Protection Regulation (GDPR), the European Commission’s proposed Data Governance Act, the California Consumer Privacy Act (CCPA) and the California Privacy Rights Act (CPRA). These may be supplemented by codes of practice or ethics and assessment tools to create social arrangements and pressures for abiding by data protection and privacy rules and principles. Realizing the full potential of data needs to be grounded in respect for rights including the right to liberty, autonomy, and privacy.

There are asymmetries in how the benefits of data are realized today. Current data flows risk deepening existing inequalities at the individual and country level. The benefits of social media data, for example, are realized at the corporate level, not at the individual level of the data subject. Extractive data gathering practices and network dynamics risk conspiring against the inclusive growth potential of data. Asymmetries of knowledge drive concerns about surveillance capitalism and an erosion of public trust. Realizing the full potential of data requires building back trust.

Data networks as new types of data aggregators 

To unlock data as a resource, one solution is new types of data aggregators, trusted intermediaries that bring together public and private data and grant access to data to the right actors for the right reasons whilst protecting liberties and privacy. At UN Global Pulse (and elsewhere), we call these new types of data aggregators data networks.

Data networks are matchmakers. They bring together data providers and data consumers who need data to develop or improve products and services. Data networks are digital infrastructures that make it easy for data providers and data consumers to find one another much like app stores, intermediaries that allow organizations offering products and services to find users and vice versa. As intermediaries, data networks are well positioned to put in place privacy protecting measures, access controls, etc. whilst enabling an open, rich, responsible ecosystem of products and services built atop of data. 

In navigating the needs for data protection and privacy with openness, data networks represent an approach to Digital Public Goods with safeguards as not all data can be open (e.g., healthcare data), and promise to unlock the full potential of data to attain the Sustainable Development Goals (SDGs) in support of the UN Secretary-General’s Roadmap on Digital Cooperation. In low and middle income countries, for example, data networks may act as levelers to access to the data economy providing sustainable growth opportunities in support of the Roadmaps’s Recommendation 1B.

Data networks can take different forms, from data markets, data commons and cooperatives, to data trusts. Data markets are marketplace-like exchanges for data resources where data providers can express their aspirations for the use of their data in the data exchanges they decide to engage in. Data trusts allow individuals to state their aspirations for data use and mandate a trustee to take care of their data in line with these aspirations. Data commons and cooperatives allow individuals to pool their data resources and collectively govern the use of data in line with the collective’s objectives (the Ada Lovelace Institute recently released an overview of these different legal mechanisms for data stewardship). We use the term data networks as a catch all to refer to these more specific types of data governance mechanisms.

Data networks raise old and new questions. Who is the owner of rights over data, who should be the owner of rights over data, and what should one be able to do with one’s data rights? Propertarian approaches to data governance law—the legal regime that regulates how data about people is collected, processed, and used—conceive of data as “object-like” and call for formalizing a right to data as to labour or property. Dignitarian approaches conceive of data as “person-like” and call for stronger protection of data under human or civil rights law. Recent relational or democratic approaches highlight the relational nature of data (your social graph data is about other people, too): traditional bottom-up approaches to data governance via assertion of individual rights may undermine prospects for effective data governance

How might we fund data networks sustainably? To enable an ecosystem of services atop a trusted intermediary, data networks need to provide reliable, trusted access over time. Setup, development, and maintenance requires funds. Who governs the setup, development, and maintenance of data networks?

How does one incentivize data providers and data consumers to come to the data network? How might one overcome fear of creative destruction of private sector companies to increase participation as a data provider? How might one build back trust to encourage data subjects to feel comfortable sharing their personal data?

How does one navigate the currently fragmented data protection and data privacy landscape to ensure compliance nationally and internationally? How might we reduce fragmentation?

Of course, as a digital infrastructure, we need technical means, too, to implement data networks including flexible and secure identity management, access controls for secure data transactions and data exchanges, data storage and processing solutions, data quality guarantees and maintenance, data standards for data interoperability, etc.

We are excited about the many data network-like efforts by the European Union, by the World Economic Forum, the World Bank, UNICEF, other agencies part of our UN Family, the Finnish innovation fund SITRA, and MyData to name just a few. Private sector-led proposals to repurpose tools developed for Decentralized Finance, Distributed Ledger Technology (DLT) and Distributed Autonomous Organizations (DAOs), to “unlock the value of data” are emerging as compelling technical, governance, and economic sustainability solutions for data networks.

New opportunities rarely come without new risks and potential harms. Without examination of data ownership, putting data networks in place risks entrenching current data ownership and unequal distribution of the benefits of data. Data markets, mechanisms to enable the buying and selling of data, may turn privacy into a luxury good (akin to how more expensive smartphones today have better data privacy controls). Data networks increase portability of data, yet, understanding how data was collected, by whom, and under what conditions underpins the responsible use of data. And we have yet to explore the risks and potential harms of DLT based data network solutions and decentralized governance by DAOs.

For us, data networks represent an approach to inclusive and networked multilateralism, a particular articulation of a vision for an accessible, open-with-safeguards, and secure digital commons. Data networks refer to a collection of mechanisms to increase data access and sharing across open and private data in a privacy-protecting and ethical, scalable and resilient, economically and environmentally sustainable manner. To get there, we will probably have to answer a lot more questions than the ones we discussed here. 

If you would like to learn more about our research, we would love to hear from you at info@unglobalpulse.org.

** Contributors to this blog also include: Felicia Vacarelu, Communications and Engagement Lead and Ian Fry, Digital Rights Intern from UN Global Pulse, and Arden Ali, Lead Researcher on Digital Ethics and Governance at the Jain Familty Institute.

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News, thoughts and ideas about big data and AI, data privacy and ethics from across the Pulse Lab Network. Read more on the blog.

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