In this introductory session, we review the evolution of data and data re-use, looking at how data has been used to solve public problems. Through the framework of the three waves of open data, participants will learn about how views of data use and re-use have changed over time, the impact data re-use has made, and major challenges facing the field.

Following a discussion of the history of the open data movement, we will discuss current approaches to data re-use around the world. We will then shift to the failures of current approaches and the need of current approaches and the need to shift from ad hoc engagements to more systematic, sustainable, and responsible models. We will introduce the role of a data steward, and how they can promote the responsible, systematic and sustainable re-use of data.

After providing the conceptual framework for discussion, we will discuss the first step in a data re-use project: understanding the problem an organization intends to solve and for whom; and how that translates into questions data can answer. Participants will learn approaches for quickly researching complex problems, assessing public interest in identified problems, and segmenting these potential stakeholders according to interests and needs. Using experiences from The GovLab’s 100 Questions Initiative, this session will also describe participatory problem definition, topic mapping and how to formulate effective research questions.

Data re-use requires both relevant data resources and technical capacity. This session will teach participants how to assess both. In the first part of the session, we will explain how participants can find useful data in their organization and outside it. Participants will learn how to conduct data audits, map the location of relevant assets among partner organizations (e.g. companies, nonprofits, and academia), and make use of open data platforms. In the latter part of the session, participants will learn the value of internal capacity reviews and receive recommendations on how they can build internal support for data projects. These explanations will be informed by real-world examples.

Before we bring demand and supply together, it can be helpful to understand the value proposition behind data sharing. This session includes information on the societal and business cases underlying data re-use, as well as the latent risks that exist in the data lifecycle. We will explore tools that can help you measure the costs and benefits of your data re-use project, as well as methods to avoid misusing data. We will also briefly look at the environmental footprint and other externalities of data initiatives.

Building off of our previous sessions focused on demand and supply, we look at how to bring the two sides together. This session will introduce you to different models of data collaboration and how to identify a fit-for-purpose collaborative model for your project. We will also look at the technical aspects of governing a data collaborative, including existing governance frameworks and the role of data-sharing agreements, as well as the technological infrastructure needed to build a sustainable collaborative.

Once you’ve established your data collaborative, it is important to understand its impact on the challenge you initially sought to address and the ecosystem as a whole. This session looks at the use of logic models to measure impact. For a data steward, impact measurement can play a big role in ensuring the sustainability of your project in the form of investment and organizational buy-in.

Data re-use projects can address public problems but their potential is best realized when they can be maintained in the long term. As such, organizations need to make changes in how they operate, ensuring they are positioned to take advantage of future cross-sector data collaborations. In this session, we will demonstrate that systematic, sustainable, and responsible data re-use can be best realized through the creation of a data steward position within an organization. The session will discuss how this role can coordinate efforts investigating where relevant data is, who has it, who needs it, and how it can best be used to tackle the problem. It will also discuss the role of the data steward in assessing human infrastructure, telling organizations what their gaps are and who they need to collaborate with and the priority they should assign to these relationships.