Understanding participation though a data-driven approach

Understanding participation though a data-driven approach

Paio, Alexandra; Duering, Serjoscha; Chronis, Angelos; Pappa, Androniki

Full Article:

Participatory models in urban regeneration are increasingly integrated in local agendas. Yet there is still a need for evaluation methodologies of those models and their impact. This paper presents a data-driven and computational methodology to measure the impact of the BIP/ZIP program in Lisbon. Using qualitative coding, data integration, unsupervised machine learning models for data clustering and interactive visualization dashboards the study aims to explore the large and complex dataset of the projects of BIP/ZIP and identify correlation patterns between their data and especially the areas of implementation, the networks of partners and the identified activities. Departing from the pilot-case of BIP/ZIP, the proposed methodology is a first step towards the development of a generalizable evaluation framework for participatory models in urban regeneration, that considers them as urban practices and hence evaluates them based on appropriate urban tools.

Participatory models in urban regeneration are increasingly integrated in local agendas. Yet there is still a need for evaluation methodologies of those models and their impact. This paper presents a data-driven and computational methodology to measure the impact of the BIP/ZIP program in Lisbon. Using qualitative coding, data integration, unsupervised machine learning models for data clustering and interactive visualization dashboards the study aims to explore the large and complex dataset of the projects of BIP/ZIP and identify correlation patterns between their data and especially the areas of implementation, the networks of partners and the identified activities. Departing from the pilot-case of BIP/ZIP, the proposed methodology is a first step towards the development of a generalizable evaluation framework for participatory models in urban regeneration, that considers them as urban practices and hence evaluates them based on appropriate urban tools.

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DOI: 10.5151/sigradi2022-sigradi2022_179

Referências bibliográficas

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Como citar:

Paio, Alexandra; Duering, Serjoscha; Chronis, Angelos; Androniki Pappa; "Understanding participation though a data-driven approach", p-77-88. In: XXVI International Conference of the Iberoamerican Society of Digital Graphics. São Paulo: Blucher, 2023.
ISSN 23186968, DOI 10.5151/sigradi2022-sigradi2022_179