Accelerating Valuable, Accessible, & Responsible Data

Takeaways from Conversations with Representatives from the Public and Private Sectors

Panel 1: Emerging Data Policy Models

  • Dominique Duval-Diop, Deputy Chief Data Scientist for the U.S. Office of Science and Technology Policy
  • Peter Fatelnig, Minister Counsellor for Digital Economy Policy for the Delegation of the EU to the U.S.
  • Hyejeong Lim, Senior Manager at the National Information Society Agency of Korea
  • Luisa Medina, Deputy Director for Digital Public Capacities at the Ministry of ICT of Colombia

Panel 2: Innovative Operational Models from a Sectoral Approach

Takeaway 1: Government data flows allow for a spectrum of data access and (re)use for internal and external partners.

Many governments around the world have turned their attention toward policy and other instruments seeking to make more of their data resources. However, their priorities vary within a wide range of approaches. In the case of the U.S., first with the Evidence Act in 2018 and then with the Federal Data Strategy in 2019, the focus has been to put data at the center of the decision-making and program design across government agencies, facilitating stronger G2G data flows. This might reveal a more internal approach, as confirmed by Dominique Duval-Diop, Deputy Chief Data Scientist for the U.S. Office of Science and Technology Policy. She noted how the U.S. federal data strategy aims at changing the data culture within agencies and establishing a government-wide vision of how agencies should consistently manage and use their data. Here, it is clear that building internal data literacy and capacity, as well as increasing their use of equitable data, are of particular importance for data (re)use initiatives to enable rigorous assessment of government programs and yield consistently informed, fair, and just treatment of data.

Takeaway 2: Regulatory frameworks may act as an important enabler to use and innovate with data.

There is a well-known and longstanding debate between innovation and regulation. Despite their tensions, they work best together to reduce uncertainty about government oversight and delineate avenues for entrepreneurial endeavors. Indeed, Peter Fatelnig noted that although Europe has spent a lot of time working on regulatory mechanisms, the E.U. realized an innovation approach always needs to go hand in hand with these policies to foster better G2B interactions. He stressed the need for a minimum legal framework for data sharing to encourage different actors to use shared data and expand projects beyond their company walls. For instance, he mentioned how the E.U. created a regulatory approach on top of the GDPR to harness European health data during the COVID-19 pandemic to incentivize companies to develop tools and means for using this data to address the health crisis.

Takeaway 3: Leadership and access to expertise are key to ensuring the sustainability of data strategies.

Leadership has a critical role in unlocking boundaries among stakeholders and triggering innovation. Attracting data talent and promoting data stewardship is key for national data strategies to ensure that both the systems and skillsets needed for data interoperability can withstand turnover in leadership or political administrations and foster a culture of data collaboration within governments.

Takeaway 4: Institutionalizing processes enable the translation of principles into practice in an inclusive manner.

Principles of transparency, accountability, and equity can only go as far as the mechanisms and processes by which they are operationalized. National data strategies need to design processes for data governance and oversight.

Takeaway 5: Data collaboration is a process, not just a technological solution.

Data collaboration should be methodologically driven around the people and processes they seek to serve in order to manage the gap between an idea’s potential impact and the availability of data actually to answer the question at hand. In other words, data demand needs to drive data supply for useful and purposeful data stocks and flows. Matt Gee, President of BrightHive, and Alex Hutchison, Director of the Data for Children Collaborative, both pointed out the importance of defining the purpose of an initiative and concentrating on the sustainability and replicability of the methods applied to achieve it.

Takeaway 6: There is a lot to learn from experimentation with new operational and governance models, such as data commons and data trusts.

Under the lead of private initiatives, there have been multiple experiments related to innovative data collaboration models. Many of these have opened opportunities for the public sector to adopt lessons from corporate practices. Matt emphasized that building on prior practices and experiences accelerates the design and implementation of new data collaboration models since they provide some evidence that it has been successfully done before. For example, the Data Trust for the State of Virginia has served as a model to show that when different local agencies share their data under a controlled instance, they can better identify their targeted population and improve overall service allocation.

Takeaway 7: New methods are needed to establish a social license and govern data in the public interest.

Most of today’s data discussions focus on protecting individuals’ privacy and how the state needs to protect citizens’ data from (mostly private sector) exploitation. Yet these debates fail to consider the agency of data subjects. Mara Balestrini, Data Lead Specialist at the IDB Lab, stated that nowadays, “people are more educated and more connected” around data and data issues, presenting “ample opportunities for mass collaboration and the creation of enormous impact based on purpose and altruism.” As The GovLab previously explored in its Data Assembly, wherein we held mini-publics to understand public opinion over C2G data (re)use by the government to address COVID-19, people are willing to contribute their data for the common good.

About The Governance Lab

The Governance Lab’s mission is to improve people’s lives by changing the way we govern. Our goal at The GovLab is to strengthen the ability of institutions — including but not limited to governments — and people to work more openly, collaboratively, effectively, and legitimately to make better decisions and solve public problems. We believe that increased availability and use of data, new ways to leverage the capacity, intelligence, and expertise of people in the problem-solving process, combined with new advances in technology and science, can transform governance. We approach each challenge and opportunity in an interdisciplinary, collaborative way, irrespective of the problem, sector, geography, and level of government. For more information, visit

About the Inter-American Development Bank

The IDB is the main source of multilateral financing and expertise for sustainable economic, social, and institutional development in Latin America and the Caribbean. The IDB Group is the leading source of development finance for Latin America and the Caribbean. The group comprises the IDB, which has worked with governments for 60 years; IDB Invest, which serves the private sector; and IDB Lab, which tests innovative ways to enable more inclusive growth.



Responsible Data Leadership to Address the Challenges of the 21st Century

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