Summary

work in progress

Objectives

  • Facilitate easy use of data – Maximize benefits from accessing and analyzing data to improve decision-making and efficiency.
  • Promote data-driven innovation – Support systematic data-driven innovation within the city administration and in collaboration with the city society, science, business, and other institutions.
  • Generate high value for the public, economy, and science – Use data to support participation, create livable residential areas, and establish a competitive business environment.
  • Increase transparency – Improve transparency in government actions through the publication and sharing of data.
  • Support climate goals and mobility transformation – Use data to provide insights and drive progress towards climate protection, social justice, and mobility transformation.
  • Ensure data protection and security – Establish effective structures to ensure compliance with data protection and security standards, building trust in digital processes.
  • Implement Open Data successfully – Optimize and freely provide data to create added value for the city society and administration.
  • Provide tools for urban data – Develop adaptable tools to manage dynamic processes.
  • Enable precise forecasts and data-based decisions – Use data to enable more accurate predictions and transparent decision-making.
  • Measure success and ensure continuous improvement – Use data to evaluate the success of decisions and implement continuous control processes.
  • Promote inclusion – Drive inclusion through data and implement metadata-based characteristics for enhanced accessibility.

Fields of action

The strategy lists three fields of action

  • Data governance – Defines guidelines and rules for handling data, setting the strategic framework for ensuring data quality and data security. It includes defining roles and responsibilities for data handling.
  • System level (IT) – Involves the technical implementation of data governance rules, including the Urban Data Platform (UDP). This ensures a unified architecture for data integration and processing.
  • Data management – Covers the operational tasks related to data, including collection, storage, processing, archiving, and deletion. It also sets the guidelines for ensuring data quality and security.

Facts and Links

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