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Assessing the internal quality of PPGIS data: development and testing of a quality assessment framework




TekijätSimola, Anni; Fagerholm, Nora; Klonner, Carolin; Kajosaari, Anna

Julkaisuvuosi2026

Lehti: Cartography and Geographic Information Science

ISSN1523-0406

eISSN1545-0465

DOIhttps://doi.org/10.1080/15230406.2026.2616453

Julkaisun avoimuus kirjaamishetkelläAvoimesti saatavilla

Julkaisukanavan avoimuus Osittain avoin julkaisukanava

Verkko-osoitehttps://doi.org/10.1080/15230406.2026.2616453

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/515546763

Rinnakkaistallenteen lisenssiCC BY

Rinnakkaistallennetun julkaisun versioKustantajan versio


Tiivistelmä

Participatory mapping allows citizens to share place-based values with researchers and planning authorities. Public participation GIS (PPGIS), a common approach of participatory mapping, is used in land use planning to engage citizens via online map-based surveys. Despite known quality issues, the quality of PPGIS data is rarely systematically assessed. Since no guideline exists for assessing PPGIS data quality, we produced a quality assessment framework based on a review of academic literature, focusing on internal data quality. We propose key data quality criteria and measures for spatial PPGIS data. We tested the framework with three PPGIS datasets, finding that some criteria, such as geometric precision and spatial autocorrelation, are straightforward to assess, while others, for example thematic accuracy, could not be assessed due to the subjective nature of PPGIS data. Additionally, the selected PPGIS datasets lacked required information for assessing some criteria, for example mapping effort. Conventional geospatial data quality criteria were particularly challenging to assess, highlighting the need for PPGIS-specific alternative criteria. The proposed framework provides an important basis for establishing systematic quality assessment practices in the PPGIS field and increasing trust in PPGIS data. However, further testing of the framework with diverse PPGIS data is needed.


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Julkaisussa olevat rahoitustiedot
This work was supported by Transformative Cities project (European Union – NextGenerationEU instrument and Research Council of Finland grant number 352943).


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