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Understanding contributions more easily
The AI modules from DIPAS_analytics help to quickly structure large amounts of participation feedback, recognize patterns, and identify the need for moderation at an early stage—transparently, comprehensibly, and completely in human control.
Urban planning thrives on feedback from urban society—but evaluating this feedback is often time-consuming and rarely standardized. This is precisely where the DIPAS_analytics project comes in. Since 2023, we have been working on the project in Hamburg to evaluate participation processes more intelligently: with the help of AI and urban data. The aim is to provide project managers with efficient support in monitoring their ongoing processes and in the subsequent evaluation of the participation results – in a transparent, comprehensible, and compatible manner.
During the participation process, the DIPAS_analytics live dashboard helps to maintain an overview and provide targeted moderation. Once the process is complete, DIPAS_analytics Insights helps to pre-structure the textual and georeferenced feedback to enable faster, more structured, and more efficient evaluation.
Combining urban geodata with AI-supported evaluation methods creates a new standard of quality: experiences and perspectives from urban society are systematically linked with administrative data to make decision-making processes targeted, evidence-based, and oriented toward people's needs. The tool supports project managers in evaluating their participation process according to their individual logic and objectives. The final responsibility for the content of the evaluation always remains with humans.
Between 2023 and 2025, important foundations for this were laid in Hamburg. The aim was to systematically use the local knowledge of civil society. To this end, it should be possible to automatically pre-structure, manually check and edit, and meaningfully link this knowledge. The results can then be visually presented – for administration, politics, and the public.