DATA STEWARDSHIP

In this introductory session, we review the history of data reuse and the ways it has solved public problems. Through the framework of the three waves of open data, participants will learn about how views of data use and reuse have changed over time, the impact data reuse has made, and major challenges facing the field. This information will be conveyed through paradigmatic examples that illustrate different models of data use.

Following a discussion of the history of the movement, we will discuss current approaches to data reuse around the world. This session will develop the discussion of data models introduced previously—focusing on freedom of information, open government data, and data collaboration. It 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. Participants will receive a detailed explanation of the changes needed to realize a third wave of open data and the ways in which the third wave can produce public value.

After providing the conceptual framework for discussion, we will discuss the first step in a data reuse 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 and agenda setting, processes which require the capacity to listen to all people affected or involved in that particular area inside and outside the organization.

Data reuse 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 data 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 portion 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.

Data reuse efforts can take several forms depending on the operational and organizational needs of supply and demand stakeholders. In this session, we will provide an overview of the forms these relationships can take, focusing on two axes: Engagement and Accessibility. We will also provide guidance on the organizational decisions that data reuse stakeholders must make about how their work is to be governed and maintained.

The use and reuse of data is not without risks to data practitioners, the intended beneficiaries of their projects, and others. In this session, we will review the various dangers that data practitioners need to be aware of, including those related to privacy, data security, poor decision-making, and open washing. Participants will additionally learn about the different risks data reuse poses to individuals, a relatively well-discussed issue, and groups, a relatively under-discussed problem.

Data reuse projects, such as data collaboratives, need principles, practices, and processes to enable stakeholders to interact with the data in an ethical, legal, and responsible manner. In this session, we will seek to demystify the legal and governance elements of data collaboration to support effective and legitimate decision-making address risks identified in the previous section. Participants will learn from a variety of tools, such as the Contractual Wheel of Data Collaboration model, and notable practices in the field to establish a legal basis for their work and deploy fit-for-purpose decision-making strategies across the data life cycle.

Data reuse 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 reuse 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.