Towards Effective Participation: A Stakeholder-Centered Evaluation for Aggregating Spatially Explicit Data

As participatory mapping becomes more ingrained into participatory practices, it is vital to understand what makes a method effective. Through the employment of a participatory mapping experiment within an ongoing urban greening initiative, this research aims at validating two established aggregation methods of spatially explicit data points in participatory mapping. Utilizing a paper mapping activity with community residents, the collected spatial data points were analyzed using both democratic and weighted aggregation. Subsequently, a follow-up study was employed to validate the perceived feeling of ownership among both of the methods in terms of the stakeholders’ sense of community representation within the visual outputs. This research introduces a novel approach to the evaluation of participatory mapping practices. A key finding includes the development of a comprehensive methodological model that explores various aspects of a participatory process. Additionally, a new criterion was presented, stakeholder representation, in which to evaluate effectiveness. The difference between the methods was not found to be significant, as the mapping results revealed a consistent overlap in the areas of interest across the stakeholder groups, suggesting a general public consensus on the local development priorities. These insights hold considerable value for local decisions makers, as agreement areas provide a stable foundation for planning. Lastly, this research contributes to the ongoing efforts to evaluate and standardize participatory mapping methods, while also addressing the potential of varied aggregation methods to enhance effectiveness.

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Publication Details

Journal
Land
Published
2024-11-21
DOI
https://doi.org/10.3390/land13121973
Primary Topic
Geographic Information Systems Studies
Type
article
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article

Towards Effective Participation: A Stakeholder-Centered Evaluation for Aggregating Spatially Explicit Data

Eduardo Dias, Susannah M. Leahy
Land
Geographic Information Systems Studies
article

Towards Effective Participation: A Stakeholder-Centered Evaluation for Aggregating Spatially Explicit Data

Eduardo Dias, Susannah M. Leahy
article en

Abstract

As participatory mapping becomes more ingrained into participatory practices, it is vital to understand what makes a method effective. Through the employment of a participatory mapping experiment within an ongoing urban greening initiative, this research aims at validating two established aggregation methods of spatially explicit data points in participatory mapping. Utilizing a paper mapping activity with community residents, the collected spatial data points were analyzed using both democratic and weighted aggregation. Subsequently, a follow-up study was employed to validate the perceived feeling of ownership among both of the methods in terms of the stakeholders’ sense of community representation within the visual outputs. This research introduces a novel approach to the evaluation of participatory mapping practices. A key finding includes the development of a comprehensive methodological model that explores various aspects of a participatory process. Additionally, a new criterion was presented, stakeholder representation, in which to evaluate effectiveness. The difference between the methods was not found to be significant, as the mapping results revealed a consistent overlap in the areas of interest across the stakeholder groups, suggesting a general public consensus on the local development priorities. These insights hold considerable value for local decisions makers, as agreement areas provide a stable foundation for planning. Lastly, this research contributes to the ongoing efforts to evaluate and standardize participatory mapping methods, while also addressing the potential of varied aggregation methods to enhance effectiveness.

LandVol. 13(12)
Amsterdam University College (NL), Vrije Universiteit Amsterdam (NL)
Sustainable cities and communities
Openalex Percentile: Top 66%
Geographic Information Systems Studies
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