Data collaboratives are a new form of collaboration in which participants from across sectors exchange data to create public value.
The Contracts for Data Collaboration initiative aims to remove barriers that hinder the establishment of data collaboratives, such as high transaction costs and low levels of trust.
22 January 2019: The World Economic Forum (WEF), the Sustainable Development Solutions Network (SDSN) Thematic Research Network on Data and Statistics (TReNDS) and others have launched an initiative to break down barriers to public-private data collaboration. The Contracts for Data Collaboration (C4DC) initiative aims to address the inefficiencies of developing contractual agreements for such collaboration, and thus unlock privately processed data needed to address challenges.
C4DC’s charter members are the GovLab, TReNDS, University of Washington and the World Economic Forum.
The GovLab describes data collaboratives as “a new form of collaboration” in which participants from across sectors exchange data to create public value. This value can manifest as: greater situational awareness and response; public service design and delivery; knowledge creation and transfer; prediction and forecasting; and/or impact assessment and evaluation.
There are six overarching types of data collaboratives:
Difficulties in scaling data collaboration center around ensuring trust and shared responsibility in how data will be handled and used, in part because of the high transaction costs involved in drafting contracts and agreements for sharing. To tackle the high transaction costs and other issues, C4DC will guide those seeking to establish data collaboratives by developing a shared, searchable library of contractual clauses pulled from existing data sharing agreements. The repository will also serve as a hub for use cases, guides and other analyses of common language, patterns and best practices.
Complementing the C4DC initiative’s launch, the GovLab’s Data Collaboratives website also offers a Guide that outlines eight phases for design and implementation, as well as a ‘Data Responsibility Framework’ offering strategies to mitigate risk across the data lifecycle. [Data Collaboratives Website] [Press Release]