Overview

The project focuses on the development of a Data Governance Model to address the increasing complexity of data-driven urban transformation in Berlin. It tackles fundamental questions of data access, usage, and institutional responsibility in the context of key urban challenges such as climate neutrality, mobility transition, and administrative modernisation. The project was initiated by (at the time Prof.) Jochen Rabe and Prof. Max Grafenstein, recognising the urgent need to bridge the knowledge gap in data governance across the public and private sector. It builds on a precursor project with Siemens, who joined as associate partners.

Approach

The work combines theoretical data governance frameworks with a practice-oriented application case: the deployment of data-driven tools for urban air quality management. A multi-stakeholder approach enables collaboration between public administration, private sector, and civil society, with a strong emphasis on participation mechanisms to manage conflicting interests. The project further develops and tests data modelling methods within real-world policy and planning contexts.

Outcomes

The result is a validated and transferable Data Governance Framework, derived from the continuous alignment of theory and practice. It defines requirements for a data-driven public administration, establishes participatory processes as a core governance component, and advances methods for data use in environmental management. The project demonstrates how transparent, collaborative, and trust-based data ecosystems can be operationalised to support effective urban decision-making.

Publication

Client

City of Berlin (as part of the Smart City Model Projects Programme of the BMWSB)

Partner

Law&Innovation

KWB (project partly delivered during tenure)

Humboldt Institut Für internet und Gesellschaft

Siemens

Timeline

2022-2025