Unlocking Data Flows Through Data Collaboratives

Practical Guide for Data Collaboratives

 

By: Natalia González Alarcón & Stefaan G. Verhulst

The rise of datafication — the transformation of daily life into data for use by both public and private sectors — is happening. Data’s rapid generation across various sectors offers immense opportunities for its application. However, maximizing this potential requires establishing an inclusive data access ecosystem involving all relevant parties and embedding proactive and ethical data management strategies from the start.

Facilitating access to data across different sectors can reveal new, perhaps unrecognized, data value. This potential is particularly evident in data (re)use scenarios, where data collected for one purpose is anonymized, aggregated, and then repurposed for new projects.

On October 11th, 2023, we launched the practical guide to design Data Collaboratives that we jointly developed with the Inter-American Development Bank: “Facilitating Data Flows through Data Collaboratives: A Practical Guide to Designing Valuable, Accessible, and Responsible Data Collaboratives”. The event started with the presentation of the guide by Stefaan Verhulst, Co-Founder and Chief Research, The GovLab. The guide’s presentation was followed by a panel conversation with leaders and experienced data collaborators: Diana Rodríguez, Women’s Secretary at the Mayor’s Office of Bogotá, Alberto Palomo, Chief Data Officer at the Oficina del Dato, State Secretariat for Digitalization and Artificial Intelligence of Spain, Fraser Macdonald, Deputy Director of Data for Children Collaborative at Edinburgh Futures Institute, and Julia Dias, Data Partnership Manager at the Inter-American Development Bank. They shared specific experiences of data collaboration they are leading from different sectors and some references to specific elements that the guide offers.

Stefaan explained how the guide intends to facilitate data exchanges through data collaboratives. The guide acknowledges that digitalization has led to “datification” creating vast amount of data from every digital interaction –the growth in data volume and variety, including non-traditional data from cell phones, mobility, retail, among others that could enhance societal insights. The guide aims to tackle the dual challenge of preventing data misuse while ensuring the reuse of data, by presenting data collaboratives as vehicles for managing data openness and accelerating data flows. There are different types of collaboratives, from public data interfaces to intelligence generation without actual data transfer.

Stefaan outlined the fundamental building blocks that can enable countries, cities and organizations to become more ready as it relates to unlocking data flows through data collaboratives. The approach advocates for an enabling environment and sequential steps for establishing concrete data partnerships. First, the guide provides seven recommendations for decision-makers at government and policy levels:

1. Define underlying values and principles to build impactful collaborations
2. Create regulatory or legal frameworks to foster innovation
3. Build data stewardship capabilities to steer data collaboration
4. Invest in data infrastructure and standards capacities
5. Establish a widespread data culture through leadership
6. Consider governance processes to build systems rather than solutions
7. Guarantee legitimacy through social license

Second, it outlines five steps for practitioners for establishing a data collaborative:

1. Define the need to address a problem
2. Define the supply of data needed
3. Define the value proposition behind data access and re-use
4. Match demand and supply
5. Design an M&E framework to measure impact

Regarding the recommendations and operational steps, the panel refers back to many of them but especially to the importance of creating regulatory or legal frameworks, the need to consider governance processes rather than solutions, the critical role of establishing a widespread data culture, and the importance of well-defining the problem to solve.

Alberto Palomo, Chief Data Officer at the Oficina del Dato of Spain, highlighted the importance of having regulatory frameworks and provided a governance approach when considering data collaboration schemes. He talked about the European data strategy and how Spain is putting it into practice by implementing an instrument of data spaces. He described the governance framework established by Spain’s National Data Office, designed to standardize data management across sectors. This framework aims to unify data handling in public administration and private industry, fostering value creation from data. The ultimate goal is to facilitate economic and industrial transformation by building collaborative bridges for data utilization. Alberto stated that the National Data Office is trying to build sovereign federated data ecosystems that could create a sense of community, facilitate communications, interconnect data domains, and foster transparency and trust among the different stakeholders to create social and economic value. Underneath there is the idea of data spaces, which creates ecosystems of data that are not just data sets but data services, that are not a physical infrastructure but a network of people connecting.

Alberto outlined the three-tiered governance structure for data spaces and noted the overarching regulatory layer defined by recently passed laws, such as the EU data legislation. From the top, the layers comprise the EU and international bodies, followed by national member state policies and instances, and finally, the individual data space or project level. He emphasized that “the governance model aims to provide common rules for people and organizations to run projects in a way that it’s interconnected”. The debate in Europe centers on whether a top-down or bottom-up approach is most effective. Alberto argued that “you need to combine both because the European laws have been generated but the European laws are not going to create any projects. The projects are created by the data space initiatives. So, the critical factor is defining a governance model that effectively enables data sharing among stakeholders.”

Fraser Macdonald, Deputy Director of Data for Children Collaborative, underscored the critical role of partnerships and having a systemic approach to governance processes rather than only designing by-demand solutions. Data for Children Collaborative is an initiative created from a collaboration between the Scottish Government, UNICEF and Edinburgh University that is focusing on how to harness data in boosting child welfare outcomes. Central to the Collaborative’s approach is fostering robust partnerships to leverage data in delivering tangible results. Data for Children Collaborative aims to create the good conditions for combining data and expertise, by building a systematic methodology that enhances cooperation among academia, the private sector, and public and third sectors. This approach started, as the guide suggests, by defining the problem and collaborating with varied partners to pinpoint thematic needs. This collective intelligence is crucial for addressing complex challenges affecting children that require data driven solutions.

To illustrate the process and the role of partnerships, Fraser shared insights about a collaboration with UNICEF tackling the disproportionate effects of climate change on children. Lacking the necessary in-house expertise to analyze extensive climate data, UNICEF sought to combine data on hazards and vulnerability to create a climate risk index for children. By convening a multidisciplinary team from various universities and the Foreign and Commonwealth Office, they produced an index that not only provides evidence but also supports global advocacy efforts for change. Fraser encapsulated the essence of the Collaborative’s work: “data for children is about the value of collaboration”. It’s not just about the collective endeavor but also about understanding the mutual benefits such partnerships bring.

Julia Dias, Data Partnership Manager at the Inter-American Development Bank, highlighted the value of establishing a widespread data culture and shared a specific example of a Data Collaborative. Her role oversees a consortium amongst international and development organizations that aims to unlock access to tech companies’ proprietary data for development efforts. The overarching goal is to provide strategic data goods for countries we support and aid governments in crafting and executing more effective policies, leveraging high-quality data. The consortium’s model is built on the willingness of tech companies to share their data free of charge, with the aim of lowering the transaction costs associated with this data sharing. This model benefits companies by simplifying the process, encouraging them to contribute their data for societal purposes.

A key feature of the consortium is its unified approach. It operates on a common data agreement among all participating development organizations, providing a single marketplace and a shared data governance framework. This creates a streamlined platform where all partners can view and access available datasets. Organizations within the consortium can then explore these datasets, formulate proposals detailing the specific problems they aim to tackle, and explain how they intend to use the data for these purposes. Julia emphasizes that having a common governance framework facilitates the private companies to share their proprietary data for development. This, in turn, provides governments with critical insights, often beyond their usual reach, thereby enabling better-informed decision-making.

Regarding the most operational approach the guide offers, Diana Rodríguez, Women’s Secretary at the Mayor’s Office of Bogotá, shared the process she is leading to build a data collaborative that integrates gender, care, and mobility. This project is part of the broader Care Blocks initiative, which establishes zones in the city dedicated to supporting caregivers and their families. These zones provide essential services that caregivers often forgo due to their care burden. They include educational opportunities, health and wellness activities, technological training, and access to psychological and legal assistance. Additionally, the initiative offers the needs of care receivers, offering care services for children, individuals with disabilities, and the elderly. It also conducts workshops to foster cultural change among men and their families. Although the Care Blocks offer their services in one area to facilitate access, Diana emphasized the importance of understanding access dynamics to the Care Blocks in Bogotá that became the priority for Bogota: How are people accessing Care Blocks? Can we improve access? The priority is to determine the factors influencing access to these services. To address this, Bogotá has adopted a data-driven strategy comprising three phases. The first phase involves identifying the core problem and formulating pertinent questions, followed by defining the required data to provide answers. In the second phase, lab sessions with diverse stakeholders and data users were conducted to explore available data sources and devise strategies for accessing and leveraging them. The third phase implemented pilot actions for data integration and collection. Notably, the Secretary has initiated a data collection pilot with both users and non-users in collaboration with the Bogotá Innovation Lab (iBO). This aims to gain insights into who is using the Care Blocks and how they are accessing them.

Diana underscored that “the potential of data collaboratives is that it gets everybody at the table and forces us to think outside the box by bringing in new ideas and questions and new data sources, colleagues, and partners. And at the same time, it’s a good practice to start implementing things to test if what you’re coming up with in the data collaborative is applicable and will indeed happen.”

In conclusion, the rise of datafication and the corresponding surge in data generation across various sectors indicate a new era of opportunity and challenge. The “Practical Guide to Designing Valuable, Accessible, and Responsible Data Collaboratives”, jointly developed with the Inter-American Development Bank, serves as a crucial tool in navigating this landscape. It offers a roadmap for establishing data collaboratives that prioritize responsible data management, governance approaches, and proactive strategies. The insights shared by leaders in data collaboration during the panel discussion underscore the importance of these recommendations. Their experiences highlight the need of fostering an ecosystem where data is not only accessible but also responsibly managed and effectively utilized for societal purposes. The guide’s recommendations for decision-makers and practitioners provide a practical framework for harnessing the power of data collaboratives, ensuring that the wealth of data available today is translated into tangible societal benefits.

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This guide was presented as part of the AbreLatam ConDatos Conference in Montevideo, Uruguay, and at the Festival de Datos in Punta del Este, Uruguay.

To learn more about the guide, please visit the publication here.